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Harrington RM, Kristinsson S, Wilmskoetter J, Busby N, den Ouden D, Rorden C, Fridriksson J, Bonilha L. Dissociating reading and auditory comprehension in persons with aphasia. Brain Commun 2024; 6:fcae102. [PMID: 38585671 PMCID: PMC10998352 DOI: 10.1093/braincomms/fcae102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 01/10/2024] [Accepted: 03/21/2024] [Indexed: 04/09/2024] Open
Abstract
Language comprehension is often affected in individuals with post-stroke aphasia. However, deficits in auditory comprehension are not fully correlated with deficits in reading comprehension and the mechanisms underlying this dissociation remain unclear. This distinction is important for understanding language mechanisms, predicting long-term impairments and future development of treatment interventions. Using comprehensive auditory and reading measures from a large cohort of individuals with aphasia, we evaluated the relationship between aphasia type and reading comprehension impairments, the relationship between auditory versus reading comprehension deficits and the crucial neuroanatomy supporting the dissociation between post-stroke reading and auditory deficits. Scores from the Western Aphasia Battery-Revised from 70 participants with aphasia after a left-hemisphere stroke were utilized to evaluate both reading and auditory comprehension of linguistically equivalent stimuli. Repeated-measures and univariate ANOVA were used to assess the relationship between auditory comprehension and aphasia types and correlations were employed to test the relationship between reading and auditory comprehension deficits. Lesion-symptom mapping was used to determine the dissociation of crucial brain structures supporting reading comprehension deficits controlling for auditory deficits and vice versa. Participants with Broca's or global aphasia had the worst performance on reading comprehension. Auditory comprehension explained 26% of the variance in reading comprehension for sentence completion and 44% for following sequential commands. Controlling for auditory comprehension, worse reading comprehension performance was independently associated with damage to the inferior temporal gyrus, fusiform gyrus, posterior inferior temporal gyrus, inferior occipital gyrus, lingual gyrus and posterior thalamic radiation. Auditory and reading comprehension are only partly correlated in aphasia. Reading is an integral part of daily life and directly associated with quality of life and functional outcomes. This study demonstrated that reading performance is directly related to lesioned areas in the boundaries between visual association regions and ventral stream language areas. This behavioural and neuroanatomical dissociation provides information about the neurobiology of language and mechanisms for potential future treatment interventions.
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Affiliation(s)
- Rachael M Harrington
- Department of Communication Sciences and Disorders and Center for Research on the Challenges of Acquiring Language and Literacy, Georgia State University, Atlanta, GA 30310, USA
| | - Sigfus Kristinsson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29464, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Dirk den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Leonardo Bonilha
- School of Medicine Columbia, University of South Carolina, Columbia, SC 29208, USA
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Chen J, Ngo A, Rodríguez-Cruces R, Royer J, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Yasuda CL, Alvim MKM, Bonilha L, Gleichgerrcht E, Focke NK, Kreilkamp B, Domin M, von Podewils F, Langner S, Rummel C, Wiest R, Martin P, Kotikalapudi R, Bender B, O’Brien TJ, Sinclair B, Vivash L, Kwan P, Desmond PM, Lui E, Duma GM, Bonanni P, Ballerini A, Vaudano AE, Meletti S, Tondelli M, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Rüber T, Bauer T, Weber B, Caldairou B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Pardoe H, Severino M, Striano P, Tortora D, Kaestner E, Hatton SN, Arienzo D, Vos SB, Ryten M, Taylor PN, Duncan JS, Whelan CD, Galovic M, Winston GP, Thomopoulos SI, Thompson PM, Sisodiya SM, Labate A, McDonald CR, Caciagli L, Bernasconi N, Bernasconi A, Larivière S, Schrader D, Bernhardt BC. A WORLDWIDE ENIGMA STUDY ON EPILEPSY-RELATED GRAY AND WHITE MATTER COMPROMISE ACROSS THE ADULT LIFESPAN. bioRxiv 2024:2024.03.02.583073. [PMID: 38496668 PMCID: PMC10942350 DOI: 10.1101/2024.03.02.583073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Objectives Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments. Methods We studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves. Results In TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions. Conclusions This study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.
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Affiliation(s)
- Judy Chen
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
- Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Fernando Cendes
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | - Marina K. M. Alvim
- Department of Neurology, University of Campinas-–UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K. Focke
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Barbara Kreilkamp
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewils
- Department of Neurology, University Medicine Greifswald, Epilepsy Center, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Germany
| | - Terence J. O’Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patrick Kwan
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M. Desmond
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Elaine Lui
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Gian Marco Duma
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Paolo Bonanni
- Scientific Institute IRCCS E.Medea, Epilepsy Unit, Conegliano (TV), Italy
| | - Alice Ballerini
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
- Primary Care Department, Azienda Sanitaria Locale di Modena, Modena, Italy
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Colin P. Doherty
- Department of Neurology, St James’ Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L. Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D. Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne VIC 3010, Australia
| | - Rhys H. Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Contol and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Cognitive Science Department, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Meyer Children’s Hospital IRCCS, Florence, Italy
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Italy
| | | | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK
| | - Theodor Rüber
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Tobias Bauer
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Hôpital Universitaire de Bruxelles (HUB), Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J. A. Carr
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Eugenio Abela
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Mark P. Richardson
- School of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | - Heath Pardoe
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, United States
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Erik Kaestner
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sean N. Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Donatello Arienzo
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Sjoerd B. Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Mina Ryten
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Peter N. Taylor
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- CNNP Lab, ICOS group, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - John S. Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Christopher D. Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Marian Galovic
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zürich, Zürich, Switzerland
| | - Gavin P. Winston
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, ON, Canada
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Angelo Labate
- Neurophysiopathology and Movement Disorders Clinic, Regional Epilepsy Center, University of Messina, Italy
| | - Carrie R. McDonald
- Department of Radiation Medicine and Applied Sciences; Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, United States
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Bucks, UK
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Center for Brain Circuit Therapeutics, Brigham and Women’s Hospital, Harvard University, Boston, MA, USA
| | - Dewi Schrader
- BC Children’s Hospital, University of British Columbia, Vancouver, BC, Canada
| | - Boris C. Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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Bonilha L, Rorden C, Roth R, Sen S, George MS, Fridriksson J. Improved naming in patients with Broca's aphasia with tDCS. J Neurol Neurosurg Psychiatry 2024; 95:273-276. [PMID: 38071545 DOI: 10.1136/jnnp-2023-331541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 08/23/2023] [Indexed: 12/22/2023]
Abstract
BACKGROUND Language impairment (aphasia) is a common neurological deficit after strokes. For individuals with chronic aphasia (beyond 6 months after the stroke), language improvements with speech therapy (ST) are often limited. Transcranial direct current stimulation (tDCS) is a promising approach to complement language recovery but interindividual variability in treatment response is common after tDCS, suggesting a possible relationship between tDCS and type of linguistic impairment (aphasia type). METHODS This current study is a subgroup analysis of a randomised controlled phase II futility design clinical trial on tDCS in chronic post-stroke aphasia. All participants received ST coupled with tDCS (n=31) vs sham tDCS (n=39). Confrontation naming was tested at baseline, and 1, 4, and 24 weeks post-treatment. RESULTS Broca's aphasia was associated with maximal adjunctive benefit of tDCS, with an average improvement of 10 additional named items with tDCS+ST compared with ST alone at 4 weeks post-treatment. In comparison, tDCS was not associated with significant benefits for other aphasia types F(1)=4.23, p=0.04. Among participants with Broca's aphasia, preservation of the perilesional posterior inferior temporal cortex was associated with higher treatment benefit (R=0.35, p=0.03). CONCLUSIONS These results indicate that adjuvant tDCS can enhance ST to treat naming in Broca's aphasia, and this may guide intervention approaches in future studies.
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Affiliation(s)
- Leonardo Bonilha
- Neurology, University of South Carolina School of Medicine, Columbia, South Carolina, USA
| | - Chris Rorden
- Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - Rebecca Roth
- Neurology, Emory University, Atlanta, Georgia, USA
| | - Souvik Sen
- Neurology, University of South Carolina School of Medicine, Columbia, South Carolina, USA
| | - Mark S George
- Psychiatry, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Julius Fridriksson
- Communication Sciences and Disorders, University of South Carolina, Columbia, South Carolina, USA
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Stasenko A, Lin C, Bonilha L, Bernhardt BC, McDonald CR. Neurobehavioral and Clinical Comorbidities in Epilepsy: The Role of White Matter Network Disruption. Neuroscientist 2024; 30:105-131. [PMID: 35193421 PMCID: PMC9393207 DOI: 10.1177/10738584221076133] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Epilepsy is a common neurological disorder associated with alterations in cortical and subcortical brain networks. Despite a historical focus on gray matter regions involved in seizure generation and propagation, the role of white matter (WM) network disruption in epilepsy and its comorbidities has sparked recent attention. In this review, we describe patterns of WM alterations observed in focal and generalized epilepsy syndromes and highlight studies linking WM disruption to cognitive and psychiatric comorbidities, drug resistance, and poor surgical outcomes. Both tract-based and connectome-based approaches implicate the importance of extratemporal and temporo-limbic WM disconnection across a range of comorbidities, and an evolving literature reveals the utility of WM patterns for predicting outcomes following epilepsy surgery. We encourage new research employing advanced analytic techniques (e.g., machine learning) that will further shape our understanding of epilepsy as a network disorder and guide individualized treatment decisions. We also address the need for research that examines how neuromodulation and other treatments (e.g., laser ablation) affect WM networks, as well as research that leverages larger and more diverse samples, longitudinal designs, and improved magnetic resonance imaging acquisitions. These steps will be critical to ensuring generalizability of current research and determining the extent to which neuroplasticity within WM networks can influence patient outcomes.
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Affiliation(s)
- Alena Stasenko
- Department of Psychiatry, University of California, San Diego, CA, USA
| | - Christine Lin
- School of Medicine, University of California, San Diego, CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Boris C Bernhardt
- Departments of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Carrie R McDonald
- Department of Psychiatry, University of California, San Diego, CA, USA
- Department of Radiation Medicine & Applied Sciences, University of California, San Diego, CA, USA
- Center for Multimodal Imaging and Genetics (CMIG), University of California, San Diego, CA, USA
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Johnson L, Newman-Norlund R, Teghipco A, Rorden C, Bonilha L, Fridriksson J. Progressive lesion necrosis is related to increasing aphasia severity in chronic stroke. Neuroimage Clin 2024; 41:103566. [PMID: 38280310 PMCID: PMC10835598 DOI: 10.1016/j.nicl.2024.103566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 01/08/2024] [Accepted: 01/08/2024] [Indexed: 01/29/2024]
Abstract
BACKGROUND Volumetric investigations of cortical damage resulting from stroke indicate that lesion size and shape continue to change even in the chronic stage of recovery. However, the potential clinical relevance of continued lesion growth has yet to be examined. In the present study, we investigated the prevalence of lesion expansion and the relationship between expansion and changes in aphasia severity in a large sample of individuals in the chronic stage of aphasia recovery. METHODS Retrospective structural MRI scans from 104 S survivors with at least 2 observations (k = 301 observations; mean time between scans = 31 months) were included. Lesion demarcation was performed using an automated lesion segmentation software and lesion volumes at each timepoint were subsequently calculated. A linear mixed effects model was conducted to investigate the effect of days between scan on lesion expansion. Finally, we investigated the association between lesion expansion and changes on the Western Aphasia Battery (WAB) in a group of participants assessed and scanned at 2 timepoints (N = 54) using a GLM. RESULTS Most participants (81 %) showed evidence of lesion expansion. The mixed effects model revealed lesion volumes significantly increase, on average, by 0.02 cc each day (7.3 cc per year) following a scan (p < 0.0001). Change on language performance was significantly associated with change in lesion volume (p = 0.025) and age at stroke (p = 0.031). The results suggest that with every 10 cc increase in lesion size, language performance decreases by 0.9 points, and for every 10-year increase in age at stroke, language performance decreases by 1.9 points. CONCLUSIONS The present study confirms and extends prior reports that lesion expansion occurs well into the chronic stage of stroke. For the first time, we present evidence that expansion is predictive of longitudinal changes in language performance in individuals with aphasia. Future research should focus on the potential mechanisms that may lead to necrosis in areas surrounding the chronic stroke lesion.
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Kaestner E, Stasenko A, Schadler A, Roth R, Hewitt K, Reyes A, Qiu D, Bonilha L, Voets N, Hu R, Willie J, Pedersen N, Shih J, Ben-Haim S, Gross R, Drane D, McDonald CR. Impact of white matter networks on risk for memory decline following resection versus ablation in temporal lobe epilepsy. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332682. [PMID: 38212059 DOI: 10.1136/jnnp-2023-332682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/19/2023] [Indexed: 01/13/2024]
Abstract
BACKGROUND With expanding neurosurgical options in epilepsy, it is important to characterise each options' risk for postoperative cognitive decline. Here, we characterise how patients' preoperative white matter (WM) networks relates to postoperative memory changes following different epilepsy surgeries. METHODS Eighty-nine patients with temporal lobe epilepsy with T1-weighted and diffusion-weighted imaging as well as preoperative and postoperative verbal memory scores (prose recall) underwent either anterior temporal lobectomy (ATL: n=38) or stereotactic laser amygdalohippocampotomy (SLAH; n=51). We computed laterality indices (ie, asymmetry) for volume of the hippocampus and fractional anisotropy (FA) of two deep WM tracts (uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF)). RESULTS Preoperatively, left-lateralised FA of the ILF was associated with higher prose recall (p<0.01). This pattern was not observed for the UF or hippocampus (ps>0.05). Postoperatively, right-lateralised FA of the UF was associated with less decline following left ATL (p<0.05) but not left SLAH (p>0.05), while right-lateralised hippocampal asymmetry was associated with less decline following both left ATL and SLAH (ps<0.05). After accounting for preoperative memory score, age of onset and hippocampal asymmetry, the association between UF and memory decline in left ATL remained significant (p<0.01). CONCLUSIONS Asymmetry of the hippocampus is an important predictor of risk for memory decline following both surgeries. However, asymmetry of UF integrity, which is only severed during ATL, is an important predictor of memory decline after ATL only. As surgical procedures and pre-surgical mapping evolve, understanding the role of frontal-temporal WM in memory networks could help to guide more targeted surgical approaches to mitigate cognitive decline.
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Affiliation(s)
- Erik Kaestner
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Alena Stasenko
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Adam Schadler
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Rebecca Roth
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Kelsey Hewitt
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Anny Reyes
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
| | - Deqiang Qiu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Leonardo Bonilha
- Department of Neurology, University of South Carolina System, Columbia, South Carolina, USA
| | | | - Ranliang Hu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Jon Willie
- Neurosurgery, Washington University in St Louis, St Louis, Missouri, USA
| | | | - Jerry Shih
- Neurosciences, University of California, San Diego, La Jolla, California, USA
| | - Sharona Ben-Haim
- Neurosurgery, University of California, San Diego, La Jolla, California, USA
| | - Robert Gross
- Department of Neurological Surgery, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Daniel Drane
- Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Carrie R McDonald
- Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California, USA
- Psychiatry, University of California, San Diego, La Jolla, California, USA
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7
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Conrad EC, Lucas A, Ojemann WK, Aguila CA, Mojena M, LaRocque JJ, Pattnaik AR, Gallagher R, Greenblatt A, Tranquille A, Parashos A, Gleichgerrcht E, Bonilha L, Litt B, Sinha S, Ungar L, Davis KA. Interictal intracranial EEG asymmetry lateralizes temporal lobe epilepsy. medRxiv 2023:2023.12.13.23299907. [PMID: 38168158 PMCID: PMC10760281 DOI: 10.1101/2023.12.13.23299907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Patients with drug-resistant temporal lobe epilepsy often undergo intracranial EEG recording to capture multiple seizures in order to lateralize the seizure onset zone. This process is associated with morbidity and often ends in postoperative seizure recurrence. Abundant interictal (between-seizure) data is captured during this process, but these data currently play a small role in surgical planning. Our objective was to predict the laterality of the seizure onset zone using interictal (between-seizure) intracranial EEG data in patients with temporal lobe epilepsy. We performed a retrospective cohort study (single-center study for model development; two-center study for model validation). We studied patients with temporal lobe epilepsy undergoing intracranial EEG at the University of Pennsylvania (internal cohort) and the Medical University of South Carolina (external cohort) between 2015 and 2022. We developed a logistic regression model to predict seizure onset zone laterality using interictal EEG. We compared the concordance between the model-predicted seizure onset zone laterality and the side of surgery between patients with good and poor surgical outcomes. 47 patients (30 women; ages 20-69; 20 left-sided, 10 right-sided, and 17 bilateral seizure onsets) were analyzed for model development and internal validation. 19 patients (10 women; ages 23-73; 5 left-sided, 10 right-sided, 4 bilateral) were analyzed for external validation. The internal cohort cross-validated area under the curve for a model trained using spike rates was 0.83 for a model predicting left-sided seizure onset and 0.68 for a model predicting right-sided seizure onset. Balanced accuracies in the external cohort were 79.3% and 78.9% for the left- and right-sided predictions, respectively. The predicted concordance between the laterality of the seizure onset zone and the side of surgery was higher in patients with good surgical outcome. In conclusion, interictal EEG signatures are distinct across seizure onset zone lateralities. Left-sided seizure onsets are easier to distinguish than right-sided onsets. A model trained on spike rates accurately identifies patients with left-sided seizure onset zones and predicts surgical outcome.
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Affiliation(s)
- Erin C. Conrad
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alfredo Lucas
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William K.S. Ojemann
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Carlos A. Aguila
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marissa Mojena
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joshua J. LaRocque
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Akash R. Pattnaik
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ryan Gallagher
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Greenblatt
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Ashley Tranquille
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra Parashos
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | | | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30325, USA
| | - Brian Litt
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Saurabh Sinha
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lyle Ungar
- Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathryn A. Davis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
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8
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Busby N, Newman-Norlund R, Wilmskoetter J, Johnson L, Rorden C, Gibson M, Roth R, Wilson S, Fridriksson J, Bonilha L. Longitudinal Progression of White Matter Hyperintensity Severity in Chronic Stroke Aphasia. Arch Rehabil Res Clin Transl 2023; 5:100302. [PMID: 38163020 PMCID: PMC10757197 DOI: 10.1016/j.arrct.2023.100302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
Objective To determine whether longitudinal progression of small vessel disease in chronic stroke survivors is associated with longitudinal worsening of chronic aphasia severity. Design A longitudinal retrospective study. Severity of white matter hyperintensities (WMHs) as a marker for small vessel disease was assessed on fluid-attenuated inversion recovery (FLAIR) scans using the Fazekas scale, with ratings for deep WMHs (DWMHs) and periventricular WMHs (PVHs). Setting University research laboratories. Participants This study includes data from 49 chronic stroke survivors with aphasia (N=49; 15 women, 34 men, age range=32-81 years, >6 months post-stroke, stroke type: [46 ischemic, 3 hemorrhagic], community dwelling). All participants completed the Western Aphasia Battery-Revised (WAB) and had FLAIR scans at 2 timepoints (average years between timepoints: 1.87 years, SD=3.21 years). Interventions Not applicable. Main Outcome Measures Change in white matter hyperintensity severity (calculated using the Fazekas scale) and change in aphasia severity (difference in Western Aphasia Battery scores) were calculated between timepoints. Separate stepwise regression models were used to identify predictors of WMH severity change, with lesion volume, age, time between timepoints, body mass index (BMI), and presence of diabetes as independent variables. Additional stepwise regression models investigated predictors of change in aphasia severity, with PVH change, DWMH change, lesion volume, time between timepoints, and age as independent predictors. Results 22.5% of participants (11/49) had increased WMH severity. Increased BMI was associated with increases in PVH severity (P=.007), whereas the presence of diabetes was associated with increased DWMH severity (P=.002). Twenty-five percent of participants had increased aphasia severity which was significantly associated with increased severity of PVH (P<.001, 16.8% variance explained). Conclusion Increased small vessel disease burden is associated with contributing to chronic changes in aphasia severity. These findings support the idea that good cardiovascular risk factor control may play an important role in the prevention of long-term worsening of aphasic symptoms.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | | | - Janina Wilmskoetter
- Department of Neurology, Medical University of South Carolina, Charleston, SC
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC
| | - Makayla Gibson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA
| | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
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9
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Chang AJ, Roth RW, Gong R, Gross RE, Harmsen I, Parashos A, Revell A, Davis KA, Bonilha L, Gleichgerrcht E. Network coupling and surgical treatment response in temporal lobe epilepsy: A proof-of-concept study. Epilepsy Behav 2023; 149:109503. [PMID: 37931391 PMCID: PMC10842155 DOI: 10.1016/j.yebeh.2023.109503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/29/2023] [Accepted: 10/20/2023] [Indexed: 11/08/2023]
Abstract
OBJECTIVE This proof-of-concept study aimed to examine the overlap between structural and functional activity (coupling) related to surgical response. METHODS We studied intracranial rest and ictal stereoelectroencephalography (sEEG) recordings from 77 seizures in thirteen participants with temporal lobe epilepsy (TLE) who subsequently underwent resective/laser ablation surgery. We used the stereotactic coordinates of electrodes to construct functional (sEEG electrodes) and structural connectomes (diffusion tensor imaging). A Jaccard index was used to assess the similarity (coupling) between structural and functional connectivity at rest and at various intraictal timepoints. RESULTS We observed that patients who did not become seizure free after surgery had higher connectome coupling recruitment than responders at rest and during early and mid seizure (and visa versa). SIGNIFICANCE Structural networks provide a backbone for functional activity in TLE. The association between lack of seizure control after surgery and the strength of synchrony between these networks suggests that surgical intervention aimed to disrupt these networks may be ineffective in those that display strong synchrony. Our results, combined with findings of other groups, suggest a potential mechanism that explains why certain patients benefit from epilepsy surgery and why others do not. This insight has the potential to guide surgical planning (e.g., removal of high coupling nodes) following future research.
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Affiliation(s)
- Allen J Chang
- College of Graduate Studies, Neuroscience Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Rebecca W Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Ruxue Gong
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University, Atlanta, GA, USA
| | - Irene Harmsen
- College of Graduate Studies, Neuroscience Institute, Medical University of South Carolina, Charleston, SC, USA
| | - Alexandra Parashos
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Andrew Revell
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn A Davis
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Leonardo Bonilha
- Department of Neurology, University of South Carolina, Columbia, SC, USA
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10
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Rodriguez‐Porcel F, Schwen Blackett D, Hickok G, Bonilha L, Turner TH. Bridging the Gap: Association between Objective and Subjective Outcomes of Communication Performance in People with Parkinson's Disease Evaluated for Deep Brain Stimulation. Mov Disord Clin Pract 2023; 10:1795-1799. [PMID: 38094653 PMCID: PMC10715351 DOI: 10.1002/mdc3.13921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 09/28/2023] [Accepted: 10/29/2023] [Indexed: 02/01/2024] Open
Abstract
Background Decrements in verbal fluency following deep brain stimulation (DBS) in people with Parkinson's disease (PwP) are common. As such, verbal fluency tasks are used in assessing DBS candidacy and target selection. However, the correspondence between testing performance and the patient's perception of communication abilities is not well-established. Methods The Communication Participation Item Bank (CPIB) was administered to 85 PwP during pre-DBS neuropsychological evaluations. Central tendencies for CPIB responses and correlations between CPIB total scores, clinical and demographic factors, and language-based tasks were examined. Results Most PwP indicated some degree of communication interference on the CPIB. Worse scores on semantic fluency and greater motor impairment were associated with more communication interference. Conclusions Our findings suggest an incomplete correspondence between commonly used language-based tests and patient-reported outcomes of communication abilities. The need for a functional communication instrument that reflects the different aspects of communication abilities in functional contexts is emphasized.
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Affiliation(s)
| | - Deena Schwen Blackett
- Department of OtolaryngologyMedical University of South CarolinaCharlestonSCUSA
- Division of Speech‐Language Pathology, Department of Rehabilitation SciencesMedical University of South CarolinaCharlestonSCUSA
| | - Gregory Hickok
- Department of Language ScienceUniversity of California, IrvineIrvineCAUSA
| | | | - Travis H. Turner
- Department of NeurologyMedical University of South CarolinaCharlestonSCUSA
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11
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Busby N, Wilson S, Wilmskoetter J, Newman-Norlund R, Sayers S, Newman-Norlund S, Roth R, Rorden C, Fridriksson J, Bonilha L. White matter hyperintensity load mediates the relationship between age and cognition. Neurobiol Aging 2023; 132:56-66. [PMID: 37729770 DOI: 10.1016/j.neurobiolaging.2023.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 08/14/2023] [Accepted: 08/21/2023] [Indexed: 09/22/2023]
Abstract
To elucidate the relationship between age and cognitive decline, it is important to consider structural brain changes such as white matter hyperintensities (WMHs), which are common in older age and may affect behavior. Therefore, we aimed to investigate if WMH load is a mediator of the relationship between age and cognitive decline. Healthy participants (N = 166, 20-80 years) completed the Montreal Cognitive Assessment (MoCA). WMHs were manually delineated on FLAIR scans. Mediation analysis was conducted to determine if WMH load mediates the relationship between age and cognition. Older age was associated with worse cognition (p < 0.001), but this was an indirect effect: older participants had more WMHs, and, in turn, increased WMH load was associated with worse MoCA scores. WMH load mediates the relationship between age and cognitive decline. Importantly, this relationship was not moderated by age (i.e., increased WMH severity is associated with poorer MoCA scores irrespective of age). Across all ages, high cholesterol was associated with increased WMH severity.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC, USA
| | | | - Sara Sayers
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Sarah Newman-Norlund
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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12
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Wilmskoetter J, Roth R, McDowell K, Munsell B, Fontenot S, Andrews K, Chang A, Johnson LP, Sangtian S, Behroozmand R, van Mierlo P, Fridriksson J, Bonilha L. Semantic Categorization of Naming Responses Based on Prearticulatory Electrical Brain Activity. J Clin Neurophysiol 2023; 40:608-615. [PMID: 37931162 PMCID: PMC10628367 DOI: 10.1097/wnp.0000000000000933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE Object naming requires visual decoding, conceptualization, semantic categorization, and phonological encoding, all within 400 to 600 ms of stimulus presentation and before a word is spoken. In this study, we sought to predict semantic categories of naming responses based on prearticulatory brain activity recorded with scalp EEG in healthy individuals. METHODS We assessed 19 healthy individuals who completed a naming task while undergoing EEG. The naming task consisted of 120 drawings of animate/inanimate objects or abstract drawings. We applied a one-dimensional, two-layer, neural network to predict the semantic categories of naming responses based on prearticulatory brain activity. RESULTS Classifications of animate, inanimate, and abstract responses had an average accuracy of 80%, sensitivity of 72%, and specificity of 87% across participants. Across participants, time points with the highest average weights were between 470 and 490 milliseconds after stimulus presentation, and electrodes with the highest weights were located over the left and right frontal brain areas. CONCLUSIONS Scalp EEG can be successfully used in predicting naming responses through prearticulatory brain activity. Interparticipant variability in feature weights suggests that individualized models are necessary for highest accuracy. Our findings may inform future applications of EEG in reconstructing speech for individuals with and without speech impairments.
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Affiliation(s)
- Janina Wilmskoetter
- Department of Rehabilitation Sciences, College of Health
Professions, Medical University of South Carolina; Charleston, SC 29425, USA
| | - Rebecca Roth
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
| | - Konnor McDowell
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
| | - Brent Munsell
- Department of Computer Science, College of Arts and
Sciences; University of North Carolina-Chapel Hill; Chapel Hill, NC 27599, USA
| | - Skyler Fontenot
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
| | - Keeghan Andrews
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
| | - Allen Chang
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
| | - Lorelei Phillip Johnson
- Department of Communication Sciences and Disorders;
University of South Carolina; Columbia, SC 29208, USA
| | - Stacey Sangtian
- Department of Communication Sciences and Disorders;
University of South Carolina; Columbia, SC 29208, USA
| | - Roozbeh Behroozmand
- Department of Communication Sciences and Disorders;
University of South Carolina; Columbia, SC 29208, USA
| | | | - Julius Fridriksson
- Department of Communication Sciences and Disorders;
University of South Carolina; Columbia, SC 29208, USA
| | - Leonardo Bonilha
- Department of Neurology, College of Medicine; Medical
University of South Carolina; Charleston, SC 29425, USA
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13
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Busby N, Newman-Norlund S, Sayers S, Newman-Norlund R, Wilmskoetter J, Rorden C, Nemati S, Wilson S, Riccardi N, Roth R, Johnson L, den Ouden DB, Fridriksson J, Bonilha L. Lower socioeconomic status is associated with premature brain aging. Neurobiol Aging 2023; 130:135-140. [PMID: 37506551 DOI: 10.1016/j.neurobiolaging.2023.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 06/06/2023] [Accepted: 06/19/2023] [Indexed: 07/30/2023]
Abstract
BACKGROUND Premature age-related brain changes may be influenced by physical health factors. Lower socioeconomic status (SES) is often associated with poorer physical health. In this study, we aimed to investigate the relationship between SES and premature brain aging. METHODS Brain age was estimated from T1-weighted images using BrainAgeR in 217 participants from the ABC@UofSC Repository. The difference between brain and chronological age (BrainGAP) was calculated. Multiple regression models were used to predict BrainGAP with age, SES, body mass index, diabetes, hypertension, sex, race, and education as predictors. SES was calculated from size-adjusted household income and the cost of living. RESULTS Fifty-five participants (25.35%) had greater brain age than chronological age (premature brain aging). Multiple regression models revealed that age, sex, and SES were significant predictors of BrainGAP with lower SES associated with greater BrainGAP (premature brain aging). CONCLUSIONS This study demonstrates that lower SES is an independent contributor to premature brain aging. This may provide additional insight into the mechanisms associated with brain health, cognition, and resilience to neurological injury.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Sarah Newman-Norlund
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Sara Sayers
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | | | - Janina Wilmskoetter
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Samaneh Nemati
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Nicholas Riccardi
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Dirk B den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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14
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Stockbridge MD, Faria AV, Fridriksson J, Rorden C, Bonilha L, Hillis AE. Subacute aphasia recovery is associated with resting-state connectivity within and beyond the language network. Ann Clin Transl Neurol 2023; 10:1525-1532. [PMID: 37403712 PMCID: PMC10502663 DOI: 10.1002/acn3.51842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 06/23/2023] [Indexed: 07/06/2023] Open
Abstract
OBJECTIVE To examine changes to connectivity after aphasia treatment in the first 3 months after stroke. METHODS Twenty people experiencing aphasia within the first 3 months of stroke completed MRI before and immediately following 15 hours of language treatment. They were classified based on their response to treatment on a naming test of nouns as either high responders (10% improvement or more), or low responders (<10% improvement). Groups were similar in age, gender distribution, education, days since stroke, stroke volume, and baseline severity. Resting-state functional connectivity analysis was limited to the connectivity of the left fusiform gyrus with the bilateral inferior frontal gyrus, supramarginal gyrus, angular gyrus, and superior, middle, and inferior temporal gyrus, based on previous studies showing the importance of left fusiform gyrus in naming performance. RESULTS Baseline ipsilateral connectivity between the left fusiform gyrus and the language network was similar between high and low responders to therapy when controlling for stroke volume. Following therapy, change in connectivity was significantly greater among high responders between the left fusiform gyrus and the ipsilateral and contralateral pars triangularis, ipsilateral pars opercularis and superior temporal gyrus, and contralateral angular gyrus when compared with low responders. INTERPRETATION An account of these findings incorporates primarily proximal connectivity restoration, but also potentially reflects select contralateral compensatory reorganization. The latter is often associated with chronic recovery, reflecting the transitional nature of the subacute period.
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Affiliation(s)
- Melissa D. Stockbridge
- Department of NeurologyJohns Hopkins University School of MedicineBaltimore21287MarylandUSA
| | - Andreia V. Faria
- Department of Radiology and Radiological ScienceJohns Hopkins University School of MedicineBaltimore21287MarylandUSA
| | - Julius Fridriksson
- Department of Communication Sciences and DisordersUniversity of South CarolinaColumbia29208South CarolinaUSA
| | - Chris Rorden
- Department of Communication Sciences and DisordersUniversity of South CarolinaColumbia29208South CarolinaUSA
| | - Leonardo Bonilha
- Department of NeurologyEmory University School of MedicineAtlanta30322GeorgiaUSA
| | - Argye E. Hillis
- Department of NeurologyJohns Hopkins University School of MedicineBaltimore21287MarylandUSA
- Department of Physical Medicine and RehabilitationJohns Hopkins University School of MedicineBaltimore21287MarylandUSA
- Department of Cognitive Science, Krieger School of Arts and SciencesJohns Hopkins UniversityBaltimore21218MarylandUSA
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15
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Lekoubou A, Ssentongo P, Maffie J, Debroy K, Kwon M, Nguyen C, Pelton M, Watt B, Ceasar J, Dinunno N, Satyasi V, Pascal Kengne A, Bonilha L, Chinchilli VM. Associations of small vessel disease and acute symptomatic seizures in ischemic stroke patients. Epilepsy Behav 2023; 145:109233. [PMID: 37329856 DOI: 10.1016/j.yebeh.2023.109233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 04/21/2023] [Accepted: 04/23/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND AND PURPOSE Cerebral microbleeds (CMBs), markers of small vessel disease are frequent in ischemic stroke, yet the association with acute symptomatic seizures (ASS) has not been well characterized. METHODS A retrospective cohort of hospitalized patients with anterior circulation ischemic stroke. The association of CMBs with acute symptomatic seizures was assessed using a logistic regression model and causal mediation analysis. RESULTS Of 381 patients, 17 developed seizures. Compared with patients without CMBs, those with CMBs had a three-fold higher unadjusted odds of seizures (unadjusted OR: 3.84, 95% 1.16-12.71, p = 0.027). After adjusting for confounders such as stroke severity, cortical infarct location, and hemorrhagic transformation, the association between CMBs and ASS was attenuated (adjusted OR: 3.11, 95%CI: 0.74-11.03, p = 0.09). The association was not mediated by stroke severity. CONCLUSION In this cohort of hospitalized patients with anterior circulation ischemic stroke, CMBs were more likely to be found in patients with ASS than those without ASS, an association that was attenuated when accounting for stroke severity, cortical infarct location, and hemorrhagic transformation. Evaluation of the long-term risk of seizures associated with CMBs and other markers of small vessel disease is warranted.
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Affiliation(s)
- Alain Lekoubou
- Department of Neurology, Penn State University, Hershey Medical Center, Hershey, PA, USA; Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
| | - Paddy Ssentongo
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
| | - Jonathon Maffie
- Department of Radiology, Penn State College of Medicine, Hershey, PA, USA.
| | - Kunal Debroy
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Michelle Kwon
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Clever Nguyen
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Matthew Pelton
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Benjamin Watt
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Justin Ceasar
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Nadia Dinunno
- College of Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Vivek Satyasi
- Department of Neurology, Penn State University, Hershey Medical Center, Hershey, PA, USA.
| | - Andre Pascal Kengne
- University of Cape Town & South African Medical Research Council, Cape Town, South Africa.
| | | | - Vernon M Chinchilli
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA.
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16
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Hannan J, Wilmskoetter J, Fridriksson J, Hillis AE, Bonilha L, Busby N. Brain health imaging markers, post-stroke aphasia and Cognition: A scoping review. Neuroimage Clin 2023; 39:103480. [PMID: 37536153 PMCID: PMC10412866 DOI: 10.1016/j.nicl.2023.103480] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 08/05/2023]
Abstract
For the past decade, brain health has been an emerging line of scientific inquiry assessing the impact of age-related neurostructural changes on cognitive decline and recovery from brain injury. Typically, compromised brain health is attributed to the presence of small vessel disease (SVD) and brain tissue atrophy, which are represented by various neuroimaging features. However, to date, the relationship between brain health markers and chronic aphasia severity remains unclear. Thus, the goal of this scoping review was to assess the current body of evidence regarding the relationship between SVD-related brain health biomarkers and post-stroke aphasia and cognition. In all, 187 articles were identified from 3 databases, of which 16 articles met the criteria for inclusion. Among these studies, 11 focused on cognition rather than aphasia, while 2 investigated both. Of the 10 studies that used white matter hyperintensities (WMHs) as an indicator of SVD severity, 8 studies (80%) demonstrated a relationship between WMH load and worse cognition in stroke patients. Interestingly, among the studies that specifically investigated aphasia, all 5 studies (100%) demonstrated a relationship between SVD and worse language performance. They also indicated that factors other than brain health (e.g., lesion, age, time post onset) played an important role in determining aphasia severity at a single timepoint. These findings suggest that brain health is likely a crucial factor in the context of aphasia recovery, possibly indicating the necessity of cognitive reserve thresholds for the multimodal cognitive demands associated with language recovery. While SVD and structural brain health are not commonly considered as predictors of aphasia severity, more comprehensive models incorporating brain health have the potential to improve prognosis of post-stroke cognitive and language deficits. Given the variability in the existing literature, a uniform grading system for overall SVD would be beneficial for future research on the mechanisms related to brain networks and neuroplasticity, and their translational impact.
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Affiliation(s)
- Jade Hannan
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Physical Medicine, Rehabilitation, and Cognitive Science, Johns Hopkins University, Baltimore, MD, USA
| | | | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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17
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Kaestner E, Rao J, Chang AJ, Wang ZI, Busch RM, Keller SS, Rüber T, Drane DL, Stoub T, Gleichgerrcht E, Bonilha L, Hasenstab K, McDonald C. Convolutional Neural Network Algorithm to Determine Lateralization of Seizure Onset in Patients With Epilepsy: A Proof-of-Principle Study. Neurology 2023; 101:e324-e335. [PMID: 37202160 PMCID: PMC10382265 DOI: 10.1212/wnl.0000000000207411] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 03/30/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. In this study, we explored the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input. METHODS Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared with a randomized model (comparison with chance) and a hippocampal volume logistic regression (comparison with current clinically available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients. RESULTS Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD = 5.1%) of runs with the best-performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification. DISCUSSION These extratemporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extrahippocampal regions that may require additional radiologic attention. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MRI can correctly classify seizure laterality.
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Affiliation(s)
- Erik Kaestner
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Jun Rao
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Allen J Chang
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Zhong Irene Wang
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Robyn M Busch
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Simon S Keller
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Theodor Rüber
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Daniel L Drane
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Travis Stoub
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Ezequiel Gleichgerrcht
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Leonardo Bonilha
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Kyle Hasenstab
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA
| | - Carrie McDonald
- From the University of California San Diego (E.K., J.R., C.M.), CA; Medical University of South Carolina (A.J.C., E.G.), Charleston; Cleveland Clinic (Z.I.W., R.M.B.), OH; University of Liverpool (S.S.K.), United Kingdom; University of Bonn (T.R.), DE; University of Emory (D.L.D., L.B.), Atlanta, GA; Rush University (T.S.), Chicago, IL; and San Diego State University (K.H.), San Diego, CA.
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18
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Wilmskoetter J, Busby N, He X, Caciagli L, Roth R, Kristinsson S, Davis KA, Rorden C, Bassett DS, Fridriksson J, Bonilha L. Dynamic network properties of the superior temporal gyrus mediate the impact of brain age gap on chronic aphasia severity. Commun Biol 2023; 6:727. [PMID: 37452209 PMCID: PMC10349039 DOI: 10.1038/s42003-023-05119-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 07/07/2023] [Indexed: 07/18/2023] Open
Abstract
Brain structure deteriorates with aging and predisposes an individual to more severe language impairments (aphasia) after a stroke. However, the underlying mechanisms of this relation are not well understood. Here we use an approach to model brain network properties outside the stroke lesion, network controllability, to investigate relations among individualized structural brain connections, brain age, and aphasia severity in 93 participants with chronic post-stroke aphasia. Controlling for the stroke lesion size, we observe that lower average controllability of the posterior superior temporal gyrus (STG) mediates the relation between advanced brain aging and aphasia severity. Lower controllability of the left posterior STG signifies that activity in the left posterior STG is less likely to yield a response in other brain regions due to the topological properties of the structural brain networks. These results indicate that advanced brain aging among individuals with post-stroke aphasia is associated with disruption of dynamic properties of a critical language-related area, the STG, which contributes to worse aphasic symptoms. Because brain aging is variable among individuals with aphasia, our results provide further insight into the mechanisms underlying the variance in clinical trajectories in post-stroke aphasia.
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Affiliation(s)
- Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA.
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Xiaosong He
- Department of Psychology, University of Science and Technology of China, Beijing, China
| | - Lorenzo Caciagli
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA, USA
| | - Sigfus Kristinsson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Kathryn A Davis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Dani S Bassett
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics & Astronomy, School of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, New Mexico, NM, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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19
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Teghipco A, Newman-Norlund R, Fridriksson J, Rorden C, Bonilha L. Distinct brain morphometry patterns revealed by deep learning improve prediction of aphasia severity. Res Sq 2023:rs.3.rs-3126126. [PMID: 37461696 PMCID: PMC10350198 DOI: 10.21203/rs.3.rs-3126126/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Emerging evidence suggests that post-stroke aphasia severity depends on the integrity of the brain beyond the stroke lesion. While measures of lesion anatomy and brain integrity combine synergistically to explain aphasic symptoms, significant interindividual variability remains unaccounted for. A possible explanatory factor may be the spatial distribution of brain atrophy beyond the lesion. This includes not just the specific brain areas showing atrophy, but also distinct three-dimensional patterns of atrophy. Here, we tested whether deep learning with Convolutional Neural Networks (CNN) on whole brain morphometry (i.e., segmented tissue volumes) and lesion anatomy can better predict which individuals with chronic stroke (N=231) have severe aphasia, and whether encoding spatial dependencies in the data might be capable of improving predictions by identifying unique individualized spatial patterns. We observed that CNN achieves significantly higher accuracy and F1 scores than Support Vector Machine (SVM), even when the SVM is nonlinear or integrates linear and nonlinear dimensionality reduction techniques. Performance parity was only achieved when the SVM was directly trained on the latent features learned by the CNN. Saliency maps demonstrated that the CNN leveraged widely distributed patterns of brain atrophy predictive of aphasia severity, whereas the SVM focused almost exclusively on the area around the lesion. Ensemble clustering of CNN saliency maps revealed distinct morphometry patterns that were unrelated to lesion size, highly consistent across individuals, and implicated unique brain networks associated with different cognitive processes as measured by the wider neuroimaging literature. Individualized predictions of severity depended on both ipsilateral and contralateral features outside of the location of stroke. Our findings illustrate that three-dimensional network distributions of atrophy in individuals with aphasia are directly associated with aphasia severity, underscoring the potential for deep learning to improve prognostication of behavioral outcomes from neuroimaging data, and highlighting the prospective benefits of interrogating spatial dependence at different scales in multivariate feature space.
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20
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Roth R, Busby N, Wilmskoetter J, Schwen Blackett D, Gleichgerrcht E, Johnson L, Rorden C, Newman-Norlund R, Hillis AE, den Ouden DB, Fridriksson J, Bonilha L. Diabetes, brain health, and treatment gains in post-stroke aphasia. Cereb Cortex 2023; 33:8557-8564. [PMID: 37139636 PMCID: PMC10321080 DOI: 10.1093/cercor/bhad140] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 03/31/2023] [Accepted: 04/01/2023] [Indexed: 05/05/2023] Open
Abstract
In post-stroke aphasia, language improvements following speech therapy are variable and can only be partially explained by the lesion. Brain tissue integrity beyond the lesion (brain health) may influence language recovery and can be impacted by cardiovascular risk factors, notably diabetes. We examined the impact of diabetes on structural network integrity and language recovery. Seventy-eight participants with chronic post-stroke aphasia underwent six weeks of semantic and phonological language therapy. To quantify structural network integrity, we evaluated the ratio of long-to-short-range white matter fibers within each participant's whole brain connectome, as long-range fibers are more susceptible to vascular injury and have been linked to high level cognitive processing. We found that diabetes moderated the relationship between structural network integrity and naming improvement at 1 month post treatment. For participants without diabetes (n = 59), there was a positive relationship between structural network integrity and naming improvement (t = 2.19, p = 0.032). Among individuals with diabetes (n = 19), there were fewer treatment gains and virtually no association between structural network integrity and naming improvement. Our results indicate that structural network integrity is associated with treatment gains in aphasia for those without diabetes. These results highlight the importance of post-stroke structural white matter architectural integrity in aphasia recovery.
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Affiliation(s)
- Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Janina Wilmskoetter
- Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Deena Schwen Blackett
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Ezequiel Gleichgerrcht
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | | | - Argye E Hillis
- Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD 21218 USA
| | - Dirk B den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
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21
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Athreya A, Matthews RE, Drane DL, Bonilha L, Willie JT, Gross RE, Karakis I. Withdrawal of antiseizure medications after MRI-Guided laser interstitial thermal therapy in extra-temporal lobe epilepsy. Seizure 2023; 110:86-92. [PMID: 37331198 DOI: 10.1016/j.seizure.2023.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 05/16/2023] [Accepted: 06/12/2023] [Indexed: 06/20/2023] Open
Abstract
PURPOSE This study investigated the success rate of antiseizure medications (ASMs) withdrawal following MRI Guided Laser Interstitial Thermal Therapy (MRg-LITT) for extra-temporal lobe epilepsy (ETLE), and identified predictors of seizure recurrence. METHODS We retrospectively assessed 27 patients who underwent MRg-LITT for ETLE. Patients' demographics, disease characteristics, and post-surgical outcomes were evaluated for their potential to predict seizure recurrence associated with ASMs withdrawal. RESULTS The median period of observation post MRg-LITT was 3 years (range 18 - 96 months) and the median period to initial ASMs reduction was 0.5 years (range 1-36 months). ASMs reduction was attempted in 17 patients (63%), 5 (29%) of whom had seizure recurrence after initial reduction. Nearly all patient who relapsed regained seizure control after reinstitution of their ASMs regimen. Pre-operative seizure frequency (p = 0.002) and occurrence of acute post-operative seizures (p = 0.01) were associated with increased risk for seizure recurrence post ASMs reduction. At the end of the observation period, 11% of patients were seizure free without drugs, 52% were seizure free with drugs and 37% still experienced seizures despite ASMs. Compared with pre-operative status, the number of ASMs was reduced in 41% of patients, unchanged in 55% of them and increased in only 4% of them. CONCLUSIONS Successful MRg-LITT for ETLE allows for ASMs reduction in a significant portion of patients and complete ASMs withdrawal in a subset of them. Patients with higher pre-operative seizure frequency or occurrence of acute post operative seizures exhibit higher chances relapse post ASMs reduction.
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Affiliation(s)
- Arjun Athreya
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Rebecca E Matthews
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Daniel L Drane
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology, University of Washington, Seattle, WA, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jon T Willie
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA; Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Ioannis Karakis
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
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22
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Tager D, Panjeti-Moore D, Yang JC, Rivera-Cruz A, Loring DW, Staikova E, Block C, Bullinger KL, Rodriguez-Ruiz AA, Cabaniss BT, Winkel D, Bonilha L, Willie JT, Gross RE, Drane DL, Karakis I. The effect of responsive neurostimulation (RNS) on neuropsychiatric and psychosocial outcomes in drug-resistant epilepsy. Epilepsy Behav 2023; 142:109207. [PMID: 37075511 PMCID: PMC10314372 DOI: 10.1016/j.yebeh.2023.109207] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 03/05/2023] [Accepted: 03/30/2023] [Indexed: 04/21/2023]
Abstract
OBJECTIVE The impact of responsive neurostimulation (RNS) on neuropsychiatric and psychosocial outcomes has not been extensively evaluated outside of the original clinical trials and post-approval studies. The goal of this study was to ascertain the potential real-world effects of RNS on cognitive, psychiatric, and quality of life (QOL) outcomes in relation to seizure outcomes by examining 50 patients undergoing RNS implantation for drug-resistant epilepsy (DRE). METHODS We performed a retrospective review of all patients treated at our institution with RNS for DRE with at least 12 months of follow-up. In addition to baseline demographic and disease-related characteristics, we collected cognitive (Full-Scale Intelligence Quotient, Verbal Comprehension, and Perceptual Reasoning Index), psychiatric (Beck Depression and Anxiety Inventory Scores), and QOL (QOLIE-31) outcomes at 6 and 12 months after RNS implantation and correlated them with seizure outcomes. RESULTS Fifty patients (median age 39.5 years, 64% female) were treated with RNS for DRE in our institution from 2005 to 2020. Of the 37 of them who had well-documented pre and post-implantation seizure diaries, the 6-month median seizure frequency reduction was 88%, the response rate (50% or greater seizure frequency reduction) was 78%, and 32% of patients were free of disabling seizures in this timeframe. There was no statistically significant difference at a group level in any of the evaluated cognitive, psychiatric, and QOL outcomes at 6 and 12 months post-implantation compared to the pre-implantation baseline, irrespective of seizure outcomes, although a subset of patients experienced a decline in mood or cognitive variables. SIGNIFICANCE Responsive neurostimulation does not appear to have a statistically significant negative or positive impact on neuropsychiatric and psychosocial status at the group level. We observed significant variability in outcome, with a minority of patients experiencing worse behavioral outcomes, which seemed related to RNS implantation. Careful outcome monitoring is required to identify the subset of patients experiencing a poor response and to make appropriate adjustments in care.
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Affiliation(s)
- Dale Tager
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Deepa Panjeti-Moore
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Neurology Consultants of Dallas, Dallas, TX, USA
| | - Jimmy C Yang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurosurgery, Ohio State University, Columbus, OH, USA
| | - Angelica Rivera-Cruz
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology, University of South Florida, Tampa, FL, USA
| | - David W Loring
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Ekaterina Staikova
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Cady Block
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Katie L Bullinger
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | - Brian T Cabaniss
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Daniel Winkel
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jon T Willie
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Daniel L Drane
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology, University of Washington, Seattle, WA, USA.
| | - Ioannis Karakis
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
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Lucas A, Cornblath EJ, Sinha N, Hadar P, Caciagli L, Keller SS, Bonilha L, Shinohara RT, Stein JM, Das S, Gleichgerrcht E, Davis KA. Resting state functional connectivity demonstrates increased segregation in bilateral temporal lobe epilepsy. Epilepsia 2023; 64:1305-1317. [PMID: 36855286 DOI: 10.1111/epi.17565] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/26/2023] [Accepted: 02/27/2023] [Indexed: 03/02/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). METHODS In this study, using a multicenter resting state functional magnetic resonance imaging (rs-fMRI) data set, we constructed whole-brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration-segregation axis," by combining whole-brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)-based dimensionality reduction. RESULTS Compared to UTLE, BiTLE had decreased global efficiency (p = .031), and decreased whole brain average participation coefficient across a range of network densities (p = .019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p = .020). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration-segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. SIGNIFICANCE Increased interictal whole-brain network segregation, as measured by rs-fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non-invasively identifying this patient population prior to intracranial electroencephalography or device implantation.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Eli J Cornblath
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nishant Sinha
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Peter Hadar
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, Georgia, USA
| | - Russell T Shinohara
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Joel M Stein
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sandhitsu Das
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ezequiel Gleichgerrcht
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Kathryn A Davis
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Zhu H, Fitzhugh MC, Keator LM, Johnson L, Rorden C, Bonilha L, Fridriksson J, Rogalsky C. How can graph theory inform the dual-stream model of speech processing? a resting-state fMRI study of post-stroke aphasia. bioRxiv 2023:2023.04.17.537216. [PMID: 37131756 PMCID: PMC10153155 DOI: 10.1101/2023.04.17.537216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The dual-stream model of speech processing has been proposed to represent the cortical networks involved in speech comprehension and production. Although it is arguably the prominent neuroanatomical model of speech processing, it is not yet known if the dual-stream model represents actual intrinsic functional brain networks. Furthermore, it is unclear how disruptions after a stroke to the functional connectivity of the dual-stream model's regions are related to specific types of speech production and comprehension impairments seen in aphasia. To address these questions, in the present study, we examined two independent resting-state fMRI datasets: (1) 28 neurotypical matched controls and (2) 28 chronic left-hemisphere stroke survivors with aphasia collected at another site. Structural MRI, as well as language and cognitive behavioral assessments, were collected. Using standard functional connectivity measures, we successfully identified an intrinsic resting-state network amongst the dual-stream model's regions in the control group. We then used both standard functional connectivity analyses and graph theory approaches to determine how the functional connectivity of the dual-stream network differs in individuals with post-stroke aphasia, and how this connectivity may predict performance on clinical aphasia assessments. Our findings provide strong evidence that the dual-stream model is an intrinsic network as measured via resting-state MRI, and that weaker functional connectivity of the hub nodes of the dual-stream network defined by graph theory methods, but not overall average network connectivity, is weaker in the stroke group than in the control participants. Also, the functional connectivity of the hub nodes predicted specific types of impairments on clinical assessments. In particular, the relative strength of connectivity of the right hemisphere's homologues of the left dorsal stream hubs to the left dorsal hubs versus right ventral stream hubs is a particularly strong predictor of post-stroke aphasia severity and symptomology.
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25
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Schranz C, Srivastava S, Seamon BA, Marebwa B, Bonilha L, Ramakrishnan V, Wilmskoetter J, Neptune RR, Kautz SA, Seo NJ. Different aspects of hand grip performance associated with structural connectivity of distinct sensorimotor networks in chronic stroke. Physiol Rep 2023; 11:e15659. [PMID: 37020411 PMCID: PMC10076692 DOI: 10.14814/phy2.15659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 03/12/2023] [Accepted: 03/14/2023] [Indexed: 04/07/2023] Open
Abstract
Knowledge regarding the neural origins of distinct upper extremity impairments may guide the choice of interventions to target neural structures responsible for specific impairments. This cross-sectional pilot study investigated whether different brain networks explain distinct aspects of hand grip performance in stroke survivors. In 22 chronic stroke survivors, hand grip performance was characterized as grip strength, reaction, relaxation times, and control of grip force magnitude and direction. In addition, their brain structural connectomes were constructed from diffusion tensor MRI. Prominent networks were identified based on a two-step factor analysis using the number of streamlines among brain regions relevant to sensorimotor function. We used regression models to estimate the predictive value of sensorimotor network connectivity for hand grip performance measures while controlling for stroke lesion volumes. Each hand grip performance measure correlated with the connectivity of distinct brain sensorimotor networks. These results suggest that different brain networks may be responsible for different aspects of hand grip performance, which leads to varying clinical presentations of upper extremity impairment following stroke. Understanding the brain network correlates for different hand grip performances may facilitate the development of personalized rehabilitation interventions to directly target the responsible brain network for specific impairments in individual patients, thus improving outcomes.
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Affiliation(s)
- Christian Schranz
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Shraddha Srivastava
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Bryant A Seamon
- Division of Physical Therapy, Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
- Ralph H. Johnson VA Health Care System, Charleston, South Carolina, USA
| | - Barbara Marebwa
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, Georgia, USA
| | - Viswanathan Ramakrishnan
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Janina Wilmskoetter
- Division of Speech-Language Pathology, Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Richard R Neptune
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas, USA
| | - Steve A Kautz
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, South Carolina, USA
- Division of Physical Therapy, Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
- Ralph H. Johnson VA Health Care System, Charleston, South Carolina, USA
| | - Na Jin Seo
- Department of Health Sciences and Research, Medical University of South Carolina, Charleston, South Carolina, USA
- Ralph H. Johnson VA Health Care System, Charleston, South Carolina, USA
- Division of Occupational Therapy, Department of Rehabilitation Sciences, Medical University of South Carolina, Charleston, South Carolina, USA
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26
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Salazar CA, Feng W, Bonilha L, Kautz S, Jensen JH, George MS, Rowland NC. Transcranial Direct Current Stimulation for Chronic Stroke: Is Neuroimaging the Answer to the Next Leap Forward? J Clin Med 2023; 12:2601. [PMID: 37048684 PMCID: PMC10094806 DOI: 10.3390/jcm12072601] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 03/31/2023] Open
Abstract
During rehabilitation, a large proportion of stroke patients either plateau or begin to lose motor skills. By priming the motor system, transcranial direct current stimulation (tDCS) is a promising clinical adjunct that could augment the gains acquired during therapy sessions. However, the extent to which patients show improvements following tDCS is highly variable. This variability may be due to heterogeneity in regions of cortical infarct, descending motor tract injury, and/or connectivity changes, all factors that require neuroimaging for precise quantification and that affect the actual amount and location of current delivery. If the relationship between these factors and tDCS efficacy were clarified, recovery from stroke using tDCS might be become more predictable. This review provides a comprehensive summary and timeline of the development of tDCS for stroke from the viewpoint of neuroimaging. Both animal and human studies that have explored detailed aspects of anatomy, connectivity, and brain activation dynamics relevant to tDCS are discussed. Selected computational works are also included to demonstrate how sophisticated strategies for reducing variable effects of tDCS, including electric field modeling, are moving the field ever closer towards the goal of personalizing tDCS for each individual. Finally, larger and more comprehensive randomized controlled trials involving tDCS for chronic stroke recovery are underway that likely will shed light on how specific tDCS parameters, such as dose, affect stroke outcomes. The success of these collective efforts will determine whether tDCS for chronic stroke gains regulatory approval and becomes clinical practice in the future.
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Affiliation(s)
- Claudia A. Salazar
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
- Center for Biomedical Imaging, University of South Carolina, Columbia, SC 29208, USA
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Wuwei Feng
- Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Leonardo Bonilha
- Department of Neurology, College of Medicine, Emory University, Atlanta, GA 30322, USA
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Steven Kautz
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC 29425, USA
- Ralph H. Johnson VA Medical Center, Charleston, SC 29401, USA
| | - Jens H. Jensen
- Center for Biomedical Imaging, University of South Carolina, Columbia, SC 29208, USA
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC 29425, USA
- Department of Radiology and Radiological Science, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Mark S. George
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC 29425, USA
- Ralph H. Johnson VA Medical Center, Charleston, SC 29401, USA
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Nathan C. Rowland
- Department of Neurosurgery, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
- Center for Biomedical Imaging, University of South Carolina, Columbia, SC 29208, USA
- Department of Neuroscience, College of Graduate Studies, Medical University of South Carolina, Charleston, SC 29425, USA
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC 29425, USA
- Ralph H. Johnson VA Medical Center, Charleston, SC 29401, USA
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Lekoubou A, Colon YP, Bishu KG, Ngonde AT, Bonilha L, Ovbiagele B. Prevalence and prognosis of seizures among patients undergoing mechanical thrombectomy for acute ischemic stroke: A look at pre-2015 aha/asa guidelines update regarding endovascular treatment. J Stroke Cerebrovasc Dis 2023; 32:107049. [PMID: 36934518 DOI: 10.1016/j.jstrokecerebrovasdis.2023.107049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 03/19/2023] Open
Abstract
BACKGROUND Mechanical Thrombectomy (MT) is standard of care for eligible patients with Acute Ischemic Stroke (AIS) due to large vessel occlusion (LVO). With increasing use of MT, clinicians are more likely to encounter seizures, a potential complication of AIS treated with MT. Tracking future trends in the burden of post-stroke seizure associated with MT will require baseline pre-approval benchmark estimates of its frequency and outcomes. METHODS All patients with AIS who underwent MT (International Classification of Diseases, Ninth Revision, Clinical Modification; ICD-9-CM procedure code: 39.74) were identified from the National Inpatient Sample (NIS) 2006-2014, using appropriate ICD-9-CM codes. We identified a subset of patients with seizures using ICD-9-CM secondary discharge diagnoses codes 780.3x and 345.x. We computed the rate of seizures overall and across pre-specified demographic, clinical, and healthcare system-related variables. Finally, we assessed the independent association of mortality with seizures using a multivariable logistic regression model. RESULTS Of 30137 (weighted) patients with AIS who underwent MT, 1,363 (4.5%) had seizures. Patients who had seizures were younger, privately insured, or Medicaid beneficiaries, and frequently died in the hospital. There were no statistically significant differences between the seizures and no-seizures groups by race, sex, IV thrombolysis with recombinant tissue plasminogen activator, length of stay, and the number of medical comorbidities. However, patients who underwent MT and developed seizures had 75% higher odds of in-hospital mortality (adjusted OR 95% CI 1.75; 1.22-2.49). CONCLUSION In this nationwide sample, prior to the 2015 AHA/ASA guidelines update supporting MT use, seizures occurred in one of twenty patients with AIS treated with MT, and occurrence of seizure was independently associated with a nearly two-fold increase in the odds of in-hospitality death.
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Affiliation(s)
- Alain Lekoubou
- Department of Neurology, Penn State University, Hershey Medical Center, Hershey, PA, USA; Department of Public Health Sciences, Penn State University, Hershey, PA, USA.
| | - Yael Pinero Colon
- Department of Neurology, Penn State University, Hershey Medical Center, Hershey, PA, USA
| | - Kinfe G Bishu
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA; Health Equity and Rural Outreach Innovation Center (HEROIC), Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| | - Ajah T Ngonde
- Faculty of Medicine and Biomedical Sciences, University of Yaounde, Yaounde, Cameroon
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Bruce Ovbiagele
- Department of Neurology, University of California, San Francisco, CA, USA
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28
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Busby N, Wilmskoetter J, Gleichgerrcht E, Rorden C, Roth R, Newman-Norlund R, Hillis AE, Keller SS, de Bezenac C, Kristinsson S, Fridriksson J, Bonilha L. Advanced Brain Age and Chronic Poststroke Aphasia Severity. Neurology 2023; 100:e1166-e1176. [PMID: 36526425 PMCID: PMC10074460 DOI: 10.1212/wnl.0000000000201693] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/31/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Chronic poststroke language impairment is typically worse in older individuals or those with large stroke lesions. However, there is unexplained variance that likely depends on intact tissue beyond the lesion. Brain age is an emerging concept, which is partially independent from chronologic age. Advanced brain age is associated with cognitive decline in healthy older adults; therefore, we aimed to investigate the relationship with stroke aphasia. We hypothesized that advanced brain age is a significant factor associated with chronic poststroke language impairments, above and beyond chronologic age, and lesion characteristics. METHODS This cohort study retrospectively evaluated participants from the Predicting Outcomes of Language Rehabilitation in Aphasia clinical trial (NCT03416738), recruited through local advertisement in South Carolina (US). Primary inclusion criteria were left hemisphere stroke and chronic aphasia (≥12 months after stroke). Participants completed baseline behavioral testing including the Western Aphasia Battery-Revised (WAB-R), Philadelphia Naming Test (PNT), Pyramids and Palm Trees Test (PPTT), and Wechsler Adult Intelligence Scale Matrices subtest, before completing 6 weeks of language therapy. The PNT was repeated 1 month after therapy. We leveraged modern neuroimaging techniques to estimate brain age and computed a proportional difference between chronologic age and estimated brain age. Multiple linear regression models were used to evaluate the relationship between proportional brain age difference (PBAD) and behavior. RESULTS Participants (N = 93, 58 males and 35 females, average age = 61 years) had estimated brain ages ranging from 14 years younger to 23 years older than chronologic age. Advanced brain age predicted performance on semantic tasks (PPTT) and language tasks (WAB-R). For participants with advanced brain aging (n = 47), treatment gains (improvement on the PNT) were independently predicted by PBAD (T = -2.0474, p = 0.0468, 9% of variance explained). DISCUSSION Through the application of modern neuroimaging techniques, advanced brain aging was associated with aphasia severity and performance on semantic tasks. Notably, therapy outcome scores were also associated with PBAD, albeit only among participants with advanced brain aging. These findings corroborate the importance of brain age as a determinant of poststroke recovery and underscore the importance of personalized health factors in determining recovery trajectories, which should be considered during the planning or implementation of therapeutic interventions.
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Affiliation(s)
- Natalie Busby
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom.
| | - Janina Wilmskoetter
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Ezequiel Gleichgerrcht
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Chris Rorden
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Rebecca Roth
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Roger Newman-Norlund
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Argye Elizabeth Hillis
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Simon S Keller
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Christophe de Bezenac
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Sigfus Kristinsson
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Julius Fridriksson
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
| | - Leonardo Bonilha
- From the Departments of Communication Sciences and Disorders (N.B., J.F.), and Psychology (C.R., R.N.N.), University of South Carolina, Columbia; Department of Health and Rehabilitation Sciences (J.W., E.G., S.K., J.F.), Medical University of South Carolina, Charleston; Department of Neurology (R.R., L.B.), Emory University, Atlanta, GA; Department of Neurology (A.E.H.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Pharmacology and Therapeutics (S.S.K., C.d.B.), Institute of Systems, Molecular and Integrative Biology, University of Liverpool, United Kingdom; The Walton Centre NHS Foundation Trust (S.S.K., C.d.B.), Liverpool, United Kingdom
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Kristinsson S, Basilakos A, den Ouden DB, Cassarly C, Spell LA, Bonilha L, Rorden C, Hillis AE, Hickok G, Johnson L, Busby N, Walker GM, McLain A, Fridriksson J. Predicting Outcomes of Language Rehabilitation: Prognostic Factors for Immediate and Long-Term Outcomes After Aphasia Therapy. J Speech Lang Hear Res 2023; 66:1068-1084. [PMID: 36827514 PMCID: PMC10205105 DOI: 10.1044/2022_jslhr-22-00347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 10/23/2022] [Accepted: 11/30/2022] [Indexed: 05/25/2023]
Abstract
BACKGROUND Aphasia therapy is an effective approach to improve language function in chronic aphasia. However, it remains unclear what prognostic factors facilitate therapy response at the individual level. Here, we utilized data from the POLAR (Predicting Outcomes of Language Rehabilitation in Aphasia) trial to (a) determine therapy-induced change in confrontation naming and long-term maintenance of naming gains and (b) examine the extent to which aphasia severity, age, education, time postonset, and cognitive reserve predict naming gains at 1 week, 1 month, and 6 months posttherapy. METHOD A total of 107 participants with chronic (≥ 12 months poststroke) aphasia underwent extensive case history, cognitive-linguistic testing, and a neuroimaging workup prior to receiving 6 weeks of impairment-based language therapy. Therapy-induced change in naming performance (measured as raw change on the 175-item Philadelphia Naming Test [PNT]) was assessed 1 week after therapy and at follow-up time points 1 month and 6 months after therapy completion. Change in naming performance over time was evaluated using paired t tests, and linear mixed-effects models were constructed to examine the association between prognostic factors and therapy outcomes. RESULTS Naming performance was improved by 5.9 PNT items (Cohen's d = 0.56, p < .001) 1 week after therapy and by 6.4 (d = 0.66, p < .001) and 7.5 (d = 0.65, p < .001) PNT items at 1 month and 6 months after therapy completion, respectively. Aphasia severity emerged as the strongest predictor of naming improvement recovery across time points; mild (ß = 5.85-9.02) and moderate (ß = 9.65-11.54) impairment predicted better recovery than severe (ß = 1.31-3.37) and very severe (ß = 0.20-0.32) aphasia. Age was an emergent prognostic factor for recovery 1 month (ß = -0.14) and 6 months (ß = -0.20) after therapy, and time postonset (ß = -0.05) was associated with retention of naming gains at 6 months posttherapy. CONCLUSIONS These results suggest that therapy-induced naming improvement is predictable based on several easily measurable prognostic factors. Broadly speaking, these results suggest that prognostication procedures in aphasia therapy can be improved and indicate that personalization of therapy is a realistic goal in the near future. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.22141829.
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Affiliation(s)
- Sigfus Kristinsson
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Alexandra Basilakos
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Dirk B. den Ouden
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Christy Cassarly
- Department of Public Health Sciences, Medical University of South Carolina, Charleston
| | - Leigh Ann Spell
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia
| | - Argye E. Hillis
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, MD
- Department of Cognitive Science, Johns Hopkins University, Baltimore, MD
| | - Gregory Hickok
- Department of Cognitive Sciences, School of Social Sciences, University of California, Irvine
| | - Lisa Johnson
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Natalie Busby
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
| | - Grant M. Walker
- Department of Cognitive Sciences, School of Social Sciences, University of California, Irvine
| | - Alexander McLain
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia
| | - Julius Fridriksson
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia
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Chang AJ, Roth R, Bougioukli E, Ruber T, Keller SS, Drane DL, Gross RE, Welsh J, Abrol A, Calhoun V, Karakis I, Kaestner E, Weber B, McDonald C, Gleichgerrcht E, Bonilha L. MRI-based deep learning can discriminate between temporal lobe epilepsy, Alzheimer's disease, and healthy controls. Commun Med (Lond) 2023; 3:33. [PMID: 36849746 PMCID: PMC9970972 DOI: 10.1038/s43856-023-00262-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 02/10/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications of artificial intelligence (AI) assisted technologies. METHOD We assessed the ability of a convolutional neural network (CNN) algorithm to classify TLE vs. patients with AD vs. healthy controls using T1-weighted magnetic resonance imaging (MRI) scans. We used feature visualization techniques to identify regions the CNN employed to differentiate disease types. RESULTS We show the following classification results: healthy control accuracy = 81.54% (SD = 1.77%), precision = 0.81 (SD = 0.02), recall = 0.85 (SD = 0.03), and F1-score = 0.83 (SD = 0.02); TLE accuracy = 90.45% (SD = 1.59%), precision = 0.86 (SD = 0.03), recall = 0.86 (SD = 0.04), and F1-score = 0.85 (SD = 0.04); and AD accuracy = 88.52% (SD = 1.27%), precision = 0.64 (SD = 0.05), recall = 0.53 (SD = 0.07), and F1 score = 0.58 (0.05). The high accuracy in identification of TLE was remarkable, considering that only 47% of the cohort had deemed to be lesional based on MRI alone. Model predictions were also considerably better than random permutation classifications (p < 0.01) and were independent of age effects. CONCLUSIONS AI (CNN deep learning) can classify and distinguish TLE, underscoring its potential utility for future computer-aided radiological assessments of epilepsy, especially for patients who do not exhibit easily identifiable TLE associated MRI features (e.g., hippocampal sclerosis).
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Affiliation(s)
- Allen J Chang
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Rebecca Roth
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Eleni Bougioukli
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Theodor Ruber
- Department of Epileptology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Daniel L Drane
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Robert E Gross
- Department of Neurosurgery, Emory University Hospital, Atlanta, GA, USA
| | - James Welsh
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Anees Abrol
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Vince Calhoun
- School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ioannis Karakis
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Erik Kaestner
- Department of Psychology, University of California, San Diego, CA, USA
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Carrie McDonald
- Department of Psychology, University of California, San Diego, CA, USA
| | | | - Leonardo Bonilha
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
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Wiesen D, Bonilha L, Rorden C, Karnath HO. Disconnectomics to unravel the network underlying deficits of spatial exploration and attention. Sci Rep 2022; 12:22315. [PMID: 36566307 PMCID: PMC9789971 DOI: 10.1038/s41598-022-26491-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 12/15/2022] [Indexed: 12/25/2022] Open
Abstract
Spatial attention and exploration are related to a predominantly right hemispheric network structure. However, the areas of the brain involved and their exact role is still debated. Spatial neglect following right hemispheric stroke lesions has been frequently viewed as a model to study these processes in humans. Previous investigations on the anatomical basis on spatial neglect predominantly focused on focal brain damage and lesion-behaviour mapping analyses. This approach might not be suited to detect remote areas structurally spared but which might contribute to the behavioural deficit. In the present study of a sample of 203 right hemispheric stroke patients, we combined connectome lesion-symptom mapping with multivariate support vector regression to unravel the complex and disconnected network structure in spatial neglect. We delineated three central nodes that were extensively disconnected from other intrahemispheric areas, namely the right superior parietal lobule, the insula, and the temporal pole. Additionally, the analysis allocated central roles within this network to the inferior frontal gyrus (pars triangularis and opercularis), right middle temporal gyrus, right temporal pole and left and right orbitofrontal cortices, including interhemispheric disconnection. Our results suggest that these structures-although not necessarily directly damaged-might play a role within the network underlying spatial neglect in humans.
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Affiliation(s)
- Daniel Wiesen
- Centre of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076, Tübingen, Germany.
| | | | | | - Hans-Otto Karnath
- Centre of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tübingen, 72076, Tübingen, Germany
- Department of Psychology, University of South Carolina, Columbia, USA
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Matchin W, den Ouden DB, Hickok G, Hillis AE, Bonilha L, Fridriksson J. Reply: The Wernicke conundrum is misinterpreted. Brain 2022; 146:e23-e24. [PMID: 36549676 DOI: 10.1093/brain/awac483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Affiliation(s)
- William Matchin
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Dirk-Bart den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Gregory Hickok
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697, USA.,Department of Language Science, University of California, Irvine, Irvine, CA 92697, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA.,Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA.,Department of Cognitive Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
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Gleichgerrcht E, Dumitru M, Hartmann DA, Munsell BC, Kuzniecky R, Bonilha L, Sameni R. Seizure forecasting using machine learning models trained by seizure diaries. Physiol Meas 2022; 43:10.1088/1361-6579/aca6ca. [PMID: 36541513 PMCID: PMC9940727 DOI: 10.1088/1361-6579/aca6ca] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 11/28/2022] [Indexed: 11/30/2022]
Abstract
Objectives.People with refractory epilepsy are overwhelmed by the uncertainty of their next seizures. Accurate prediction of future seizures could greatly improve the quality of life for these patients. New evidence suggests that seizure occurrences can have cyclical patterns for some patients. Even though these cyclicalities are not intuitive, they can be identified by machine learning (ML), to identify patients with predictable vs unpredictable seizure patterns.Approach.Self-reported seizure logs of 153 patients from the Human Epilepsy Project with more than three reported seizures (totaling 8337 seizures) were used to obtain inter-seizure interval time-series for training and evaluation of the forecasting models. Two classes of prediction methods were studied: (1) statistical approaches using Bayesian fusion of population-wise and individual-wise seizure patterns; and (2) ML-based algorithms including least squares, least absolute shrinkage and selection operator, support vector machine (SVM) regression, and long short-term memory regression. Leave-one-person-out cross-validation was used for training and evaluation, by training on seizure diaries of all except one subject and testing on the left-out subject.Main results.The leading forecasting models were the SVM regression and a statistical model that combined the median of population-wise seizure time-intervals with a test subject's prior seizure intervals. SVM was able to forecast 50%, 70%, 81%, 84%, and 87% of seizures of unseen subjects within 0, 1, 2, 3 to 4 d of mean absolute forecasting error, respectively. The subject-wise performances show that patients with more frequent seizures were generally better predicted.Significance.ML models can leverage non-random patterns within self-reported seizure diaries to forecast future seizures. While diary-based seizure forecasting alone is only one of many aspects of clinical care of patients with epilepsy, studying the level of predictability across seizures and patients paves the path towards a better understanding of predictable vs unpredictable seizures on individualized and population-wise bases.
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Affiliation(s)
| | - Mircea Dumitru
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA
| | - David A. Hartmann
- Department of Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, CA
| | - Brent C. Munsell
- Department of Computer Science, University of North Carolina, Chapel Hill, NC
| | | | - Leonardo Bonilha
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA
| | - Reza Sameni
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA
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Nemati S, Newman‐Norlund R, Newman‐Norlund S, Sayers S, Busby N, Bonilha L, Fridriksson J. Neuroimaging‐based Biomarkers of Brain Aging in Healthy Older Adults. Alzheimers Dement 2022. [DOI: 10.1002/alz.064909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | - Sara Sayers
- University of South Carolina Columbia SC USA
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Busby N, Newman‐Norlund S, Sayers S, Newman‐Norlund R, Nemati S, Bonilha L, Fridriksson J. Language Fluency and Premature Brain Aging. Alzheimers Dement 2022. [DOI: 10.1002/alz.063916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | - Sara Sayers
- University of South Carolina Columbia SC USA
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Busby N, Newman-Norlund S, Sayers S, Newman-Norlund R, Wilson S, Nemati S, Rorden C, Wilmskoetter J, Riccardi N, Roth R, Fridriksson J, Bonilha L. White matter hyperintensity load is associated with premature brain aging. Aging (Albany NY) 2022; 14:9458-9465. [PMID: 36455869 PMCID: PMC9792198 DOI: 10.18632/aging.204397] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 11/14/2022] [Indexed: 12/05/2022]
Abstract
BACKGROUND Brain age is an MRI-derived estimate of brain tissue loss that has a similar pattern to aging-related atrophy. White matter hyperintensities (WMHs) are neuroimaging markers of small vessel disease and may represent subtle signs of brain compromise. We tested the hypothesis that WMHs are independently associated with premature brain age in an original aging cohort. METHODS Brain age was calculated using machine-learning on whole-brain tissue estimates from T1-weighted images using the BrainAgeR analysis pipeline in 166 healthy adult participants. WMHs were manually delineated on FLAIR images. WMH load was defined as the cumulative volume of WMHs. A positive difference between estimated brain age and chronological age (BrainGAP) was used as a measure of premature brain aging. Then, partial Pearson correlations between BrainGAP and volume of WMHs were calculated (accounting for chronological age). RESULTS Brain and chronological age were strongly correlated (r(163)=0.932, p<0.001). There was significant negative correlation between BrainGAP scores and chronological age (r(163)=-0.244, p<0.001) indicating that younger participants had higher BrainGAP (premature brain aging). Chronological age also showed a positive correlation with WMH load (r(163)=0.506, p<0.001) indicating older participants had increased WMH load. Controlling for chronological age, there was a statistically significant relationship between premature brain aging and WMHs load (r(163)=0.216, p=0.003). Each additional year in brain age beyond chronological age corresponded to an additional 1.1mm3 in WMH load. CONCLUSIONS WMHs are an independent factor associated with premature brain aging. This finding underscores the impact of white matter disease on global brain integrity and progressive age-like brain atrophy.
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Affiliation(s)
- Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | - Sarah Newman-Norlund
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | - Sara Sayers
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | | | - Sarah Wilson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | - Samaneh Nemati
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29201, USA
| | - Janina Wilmskoetter
- Department of Health and Rehabilitation Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Nicholas Riccardi
- Department of Psychology, University of South Carolina, Columbia, SC 29201, USA
| | - Rebecca Roth
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29201, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
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Walker GM, Fridriksson J, Hillis AE, den Ouden DB, Bonilha L, Hickok G. The Severity-Calibrated Aphasia Naming Test. Am J Speech Lang Pathol 2022; 31:2722-2740. [PMID: 36332139 PMCID: PMC9911092 DOI: 10.1044/2022_ajslp-22-00071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
PURPOSE We present a 20-item naming test, the Severity-Calibrated Aphasia Naming Test (SCANT), that can serve as a proxy measure for an aphasia severity scale that is derived from a thorough test battery of connected speech production, single-word production, speech repetition, and auditory verbal comprehension. METHOD We use lasso regression and cross-validation to identify an optimal subset from a set of 174 pictures to be named for prediction of aphasia severity, based on data from 200 participants with left-hemisphere stroke who were quasirandomly selected to represent the full impairment scale. Data from 20 healthy controls (i.e., participant caretakers/spouses) were also analyzed. We examine interrater reliability, test-retest reliability, sensitivity and specificity to the presence of aphasia, sensitivity to therapy gains, and external validity (i.e., correlation with aphasia severity measures) for the SCANT. RESULTS The SCANT has extremely high interrater reliability, and it is sensitive and specific to the presence of aphasia. We demonstrate the superiority of predictions based on the SCANT over those based on the full set of naming items. We estimate a 15% reduction in power when using the SCANT score versus the full test battery's aphasia severity score as an outcome measure; for example, to maintain the same power to detect a significant group average change in aphasia severity, a study with 25 participants using the full test battery to measure treatment effectiveness would require 30 participants if the SCANT were to be used as the testing instrument instead. CONCLUSION We provide a linear model to convert SCANT scores to aphasia severity scores, and we identify a change score cutoff of four SCANT items to obtain a high degree of confidence based on test-retest SCANT data and the modeled relation between SCANT and aphasia severity scores. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.21476871.
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Affiliation(s)
- Grant M. Walker
- Department of Cognitive Sciences, University of California, Irvine
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia
| | - Argye E. Hillis
- Departments of Neurology, Physical Medicine & Rehabilitation, and Cognitive Science, Johns Hopkins Medicine, Baltimore, MA
| | - Dirk B. den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia
| | | | - Gregory Hickok
- Department of Cognitive Sciences, University of California, Irvine
- Department of Language Science, University of California, Irvine
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Röhrig L, Sperber C, Bonilha L, Rorden C, Karnath HO. Right hemispheric white matter hyperintensities improve the prediction of spatial neglect severity in acute stroke. Neuroimage Clin 2022; 36:103265. [PMID: 36451368 PMCID: PMC9723300 DOI: 10.1016/j.nicl.2022.103265] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/12/2022] [Accepted: 11/08/2022] [Indexed: 11/13/2022]
Abstract
White matter hyperintensities (WMH) are frequently observed in brain scans of elderly people. They are associated with an increased risk of stroke, cognitive decline, and dementia. However, it is unknown yet if measures of WMH provide information that improve the understanding of poststroke outcome compared to only state-of-the-art stereotaxic structural lesion data. We implemented high-dimensional machine learning models, based on support vector regression, to predict the severity of spatial neglect in 103 acute right hemispheric stroke patients. We found that (1) the additional information of right hemispheric or bilateral voxel-based topographic WMH extent indeed yielded a significant improvement in predicting acute neglect severity (compared to the voxel-based stroke lesion map alone). (2) Periventricular WMH appeared more relevant for prediction than deep subcortical WMH. (3) Among different measures of WMH, voxel-based maps as measures of topographic extent allowed more accurate predictions compared to the use of traditional ordinally assessed visual rating scales (Fazekas-scale, Cardiovascular Health Study-scale). In summary, topographic WMH appear to be a valuable clinical imaging biomarker for predicting the severity of cognitive deficits and bears great potential for rehabilitation guidance of acute stroke patients.
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Affiliation(s)
- Lisa Röhrig
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Christoph Sperber
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30322, USA
| | - Christopher Rorden
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Hans-Otto Karnath
- Division of Neuropsychology, Center of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany; Department of Psychology, University of South Carolina, Columbia, SC 29208, USA.
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Schwen Blackett D, Varkey J, Wilmskoetter J, Roth R, Andrews K, Busby N, Gleichgerrcht E, Desai RH, Riccardi N, Basilakos A, Johnson LP, Kristinsson S, Johnson L, Rorden C, Spell LA, Fridriksson J, Bonilha L. Neural network bases of thematic semantic processing in language production. Cortex 2022; 156:126-143. [PMID: 36244204 PMCID: PMC10041939 DOI: 10.1016/j.cortex.2022.08.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/10/2022] [Accepted: 08/03/2022] [Indexed: 11/20/2022]
Abstract
Semantic processing is a central component of language and cognition. The anterior temporal lobe is postulated to be a key hub for semantic processing, but the posterior temporoparietal cortex is also involved in thematic associations during language. It is possible that these regions act in concert and depend on an anteroposterior network linking the temporal pole with posterior structures to support thematic semantic processing during language production. We employed connectome-based lesion-symptom mapping to examine the causal relationship between lesioned white matter pathways and thematic processing language deficits among individuals with post-stroke aphasia. Seventy-nine adults with chronic aphasia completed the Philadelphia Naming Test, and semantic errors were coded as either thematic or taxonomic to control for taxonomic errors. Controlling for nonverbal conceptual-semantic knowledge as measured by the Pyramids and Palm Trees Test, lesion size, and the taxonomic error rate, thematic error rate was associated with loss of white matter connections from the temporal pole traversing in peri-Sylvian regions to the posterior cingulate and the insula. These findings support the existence of a distributed network underlying thematic relationship processing in language as opposed to discrete cortical areas.
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Affiliation(s)
- Deena Schwen Blackett
- Department of Otolaryngology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA; Division of Speech-Language Pathology, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA.
| | - Jesse Varkey
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
| | - Janina Wilmskoetter
- Division of Speech-Language Pathology, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA.
| | - Rebecca Roth
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA.
| | - Keeghan Andrews
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Ezequiel Gleichgerrcht
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
| | - Rutvik H Desai
- Department of Psychology, University of South Carolina, Barnwell College, Columbia, SC, USA.
| | - Nicholas Riccardi
- Department of Psychology, University of South Carolina, Barnwell College, Columbia, SC, USA.
| | - Alexandra Basilakos
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Lorelei P Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Sigfus Kristinsson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Barnwell College, Columbia, SC, USA.
| | - Leigh A Spell
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Leonardo Bonilha
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA.
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Srivastava S, Seamon BA, Marebwa BK, Wilmskoetter J, Bowden MG, Gregory CM, Seo NJ, Hanlon CA, Bonilha L, Brown TR, Neptune RR, Kautz SA. The relationship between motor pathway damage and flexion-extension patterns of muscle co-excitation during walking. Front Neurol 2022; 13:968385. [PMID: 36388195 PMCID: PMC9650203 DOI: 10.3389/fneur.2022.968385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 10/12/2022] [Indexed: 01/16/2023] Open
Abstract
Background Mass flexion-extension co-excitation patterns during walking are often seen as a consequence of stroke, but there is limited understanding of the specific contributions of different descending motor pathways toward their control. The corticospinal tract is a major descending motor pathway influencing the production of normal sequential muscle coactivation patterns for skilled movements. However, control of walking is also influenced by non-corticospinal pathways such as the corticoreticulospinal pathway that possibly contribute toward mass flexion-extension co-excitation patterns during walking. The current study sought to investigate the associations between damage to corticospinal (CST) and corticoreticular (CRP) motor pathways following stroke and the presence of mass flexion-extension patterns during walking as evaluated using module analysis. Methods Seventeen healthy controls and 44 stroke survivors were included in the study. We used non-negative matrix factorization for module analysis of paretic leg electromyographic activity. We typically have observed four modules during walking in healthy individuals. Stroke survivors often have less independently timed modules, for example two-modules presented as mass flexion-extension pattern. We used diffusion tensor imaging-based analysis where streamlines connecting regions of interest between the cortex and brainstem were computed to evaluate CST and CRP integrity. We also used a coarse classification tree analysis to evaluate the relative CST and CRP contribution toward module control. Results Interhemispheric CST asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.023), propulsion symmetry (p = 0.016), and fewer modules (p = 0.028). Interhemispheric CRP asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.009), Dynamic gait index (p = 0.035), Six-minute walk test (p = 0.020), Berg balance scale (p = 0.048), self-selected walking speed (p = 0.041), and propulsion symmetry (p = 0.001). The classification tree model reveled that substantial ipsilesional CRP or CST damage leads to a two-module pattern and poor walking ability with a trend toward increased compensatory contralesional CRP based control. Conclusion Both CST and CRP are involved with control of modules during walking and damage to both may lead to greater reliance on the contralesional CRP, which may contribute to a two-module pattern and be associated with worse walking performance.
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Affiliation(s)
- Shraddha Srivastava
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,*Correspondence: Shraddha Srivastava
| | - Bryant A. Seamon
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,Division of Physical Therapy, Department of Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
| | - Barbara K. Marebwa
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, United States
| | - Janina Wilmskoetter
- Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
| | - Mark G. Bowden
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,Division of Physical Therapy, Department of Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
| | - Chris M. Gregory
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,Division of Physical Therapy, Department of Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
| | - Na Jin Seo
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,Division of Occupational Therapy, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
| | - Colleen A. Hanlon
- Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, United States
| | - Leonardo Bonilha
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, United States
| | - Truman R. Brown
- Department of Radiology and Radiological Science, College of Medicine, Medical University of South Carolina, Charleston, SC, United States
| | - Richard R. Neptune
- Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX, United States
| | - Steven A. Kautz
- Ralph H. Johnson VA Medical Center, Charleston, SC, United States,Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States,Division of Physical Therapy, Department of Rehabilitation Sciences, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States
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41
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Kristinsson S, Busby N, Rorden C, Newman-Norlund R, den Ouden DB, Magnusdottir S, Hjaltason H, Thors H, Hillis AE, Kjartansson O, Bonilha L, Fridriksson J. Brain age predicts long-term recovery in post-stroke aphasia. Brain Commun 2022; 4:fcac252. [PMID: 36267328 PMCID: PMC9576153 DOI: 10.1093/braincomms/fcac252] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 07/25/2022] [Accepted: 10/03/2022] [Indexed: 11/30/2022] Open
Abstract
The association between age and language recovery in stroke remains unclear. Here, we used neuroimaging data to estimate brain age, a measure of structural integrity, and examined the extent to which brain age at stroke onset is associated with (i) cross-sectional language performance, and (ii) longitudinal recovery of language function, beyond chronological age alone. A total of 49 participants (age: 65.2 ± 12.2 years, 25 female) underwent routine clinical neuroimaging (T1) and a bedside evaluation of language performance (Bedside Evaluation Screening Test-2) at onset of left hemisphere stroke. Brain age was estimated from enantiomorphically reconstructed brain scans using a machine learning algorithm trained on a large sample of healthy adults. A subsample of 30 participants returned for follow-up language assessments at least 2 years after stroke onset. To account for variability in age at stroke, we calculated proportional brain age difference, i.e. the proportional difference between brain age and chronological age. Multiple regression models were constructed to test the effects of proportional brain age difference on language outcomes. Lesion volume and chronological age were included as covariates in all models. Accelerated brain age compared with age was associated with worse overall aphasia severity (F(1, 48) = 5.65, P = 0.022), naming (F(1, 48) = 5.13, P = 0.028), and speech repetition (F(1, 48) = 8.49, P = 0.006) at stroke onset. Follow-up assessments were carried out ≥2 years after onset; decelerated brain age relative to age was significantly associated with reduced overall aphasia severity (F(1, 26) = 5.45, P = 0.028) and marginally failed to reach statistical significance for auditory comprehension (F(1, 26) = 2.87, P = 0.103). Proportional brain age difference was not found to be associated with changes in naming (F(1, 26) = 0.23, P = 0.880) and speech repetition (F(1, 26) = 0.00, P = 0.978). Chronological age was only associated with naming performance at stroke onset (F(1, 48) = 4.18, P = 0.047). These results indicate that brain age as estimated based on routine clinical brain scans may be a strong biomarker for language function and recovery after stroke.
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Affiliation(s)
- Sigfus Kristinsson
- Correspondence to: Sigfus Kristinsson, PhD Center for the Study of Aphasia Recovery University of South Carolina, 915 Greene Street Columbia, SC 29209, USA E-mail:
| | - Natalie Busby
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA
| | - Christopher Rorden
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Roger Newman-Norlund
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Dirk B den Ouden
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Communication Sciences and Disorders, Columbia, SC 29208, USA
| | | | - Haukur Hjaltason
- Department of Medicine, University of Iceland, Reykjavik 00107, Iceland,Department of Neurology, Landspitali University Hospital, Reykjavik 00101, Iceland
| | - Helga Thors
- Department of Medicine, University of Iceland, Reykjavik 00107, Iceland
| | - Argye E Hillis
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MA 21218, USA
| | - Olafur Kjartansson
- Department of Neurology, Landspitali University Hospital, Reykjavik 00101, Iceland
| | - Leonardo Bonilha
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Julius Fridriksson
- Center for the Study of Aphasia Recovery, University of South Carolina, Columbia, SC 29208, USA,Department of Communication Sciences and Disorders, Columbia, SC 29208, USA
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42
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Sabra Z, Alawieh A, Bonilha L, Naselaris T, AuYong N. Modulation of Spectral Representation and Connectivity Patterns in Response to Visual Narrative in the Human Brain. Front Hum Neurosci 2022; 16:886938. [PMID: 36277048 PMCID: PMC9582122 DOI: 10.3389/fnhum.2022.886938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/22/2022] [Indexed: 11/24/2022] Open
Abstract
The regional brain networks and the underlying neurophysiological mechanisms subserving the cognition of visual narrative in humans have largely been studied with non-invasive brain recording. In this study, we specifically investigated how regional and cross-regional cortical activities support visual narrative interpretation using intracranial stereotactic electroencephalograms recordings from thirteen human subjects (6 females, and 7 males). Widely distributed recording sites across the brain were sampled while subjects were explicitly instructed to observe images from fables presented in “sequential” order, and a set of images drawn from multiple fables presented in “scrambled” order. Broadband activity mainly within the frontal and temporal lobes were found to encode if a presented image is part of a visual narrative (sequential) or random image set (scrambled). Moreover, the temporal lobe exhibits strong activation in response to visual narratives while the frontal lobe is more engaged when contextually novel stimuli are presented. We also investigated the dynamics of interregional interactions between visual narratives and contextually novel series of images. Interestingly, the interregional connectivity is also altered between sequential and scrambled sequences. Together, these results suggest that both changes in regional neuronal activity and cross-regional interactions subserve visual narrative and contextual novelty processing.
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Affiliation(s)
- Zahraa Sabra
- Department of Neurosurgery, Emory University, Atlanta, GA, United States
| | - Ali Alawieh
- Department of Neurosurgery, Emory University, Atlanta, GA, United States
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, United States
| | - Thomas Naselaris
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - Nicholas AuYong
- Department of Neurosurgery, Emory University, Atlanta, GA, United States
- *Correspondence: Nicholas AuYong,
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43
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Johnson L, Nemati S, Bonilha L, Rorden C, Busby N, Basilakos A, Newman-Norlund R, Hillis AE, Hickok G, Fridriksson J. Predictors beyond the lesion: Health and demographic factors associated with aphasia severity. Cortex 2022; 154:375-389. [PMID: 35926368 DOI: 10.1016/j.cortex.2022.06.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 04/20/2022] [Accepted: 06/11/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Lesion-related factors are associated with severity of language impairment in persons with aphasia. The extent to which demographic and health factors predict language impairment beyond traditional cortical measures remains unknown. Identifying and understanding the contributions of factors to predictive models of severity constitutes critical knowledge for clinicians interested in charting the likely course of aphasia in their patients and designing effective treatment approaches in light of those predictions. METHODS Utilizing neuroimaging and language testing from our cohort of 224 individuals in the chronic stage of recovery from a left-hemisphere stroke in a cross-sectional study, we first conducted a lesion symptom mapping (LSM) analysis to identify regions associated with aphasia severity scores. After controlling for lesion volume and damage to pre-identified areas, three models were created to predict severity scores: 1) Demographic Model (N = 147); 2) Health Model (N = 106); and 3) Overall Model (N = 106). Finally, all identified factors were entered into a Final Model to predict raw severity scores. RESULTS Two areas were associated with aphasia severity-left posterior insula and left arcuate fasciculus. The results from the Demographic Model revealed non-linguistic cognitive ability, age at stroke, and time post-stroke as significant predictors of severity (P = .005; P = .02; P = .001, respectively), and results from the Health Model suggested the extent of leukoaraiosis is associated with severity (P = .0004). The Overall Model showed a relationship between aphasia severity and cognitive ability (P = .01), time post-stroke (P = .002), and leukoaraiosis (P = .01). In the Final Model, which aimed to predict raw severity scores, demographic, health, and lesion factors explained 55% of the variance in severity, with health and demographic factors uniquely explaining nearly half of performance variance. CONCLUSIONS Results from this study add to the literature suggesting patient-specific variables can shed light on individual differences in severity beyond lesion factors. Additionally, our results emphasize the importance of non-linguistic cognitive ability and brain health in aphasia recovery.
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Affiliation(s)
- Lisa Johnson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA.
| | - Samaneh Nemati
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Natalie Busby
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Alexandra Basilakos
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | | | - Argye E Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gregory Hickok
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
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44
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Riley EA, Verblaauw M, Masoud H, Bonilha L. Pre-frontal tDCS improves sustained attention and promotes artificial grammar learning in aphasia: An open-label study. Brain Stimul 2022; 15:1026-1028. [PMID: 35868486 PMCID: PMC10021860 DOI: 10.1016/j.brs.2022.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 11/02/2022] Open
Affiliation(s)
- Ellyn A Riley
- SU Aphasia Lab, Dept. of Communication Sciences & Disorders, Syracuse University, Syracuse, NY, USA.
| | - Mikaella Verblaauw
- SU Aphasia Lab, Dept. of Communication Sciences & Disorders, Syracuse University, Syracuse, NY, USA
| | - Hesham Masoud
- Dept. of Neurology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Leonardo Bonilha
- Dept. of Neurology, Medical University of South Carolina, Charleston, SC, USA
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45
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Lopez SM, Aksman LM, Oxtoby NP, Vos SB, Rao J, Kaestner E, Alhusaini S, Alvim M, Bender B, Bernasconi A, Bernasconi N, Bernhardt B, Bonilha L, Caciagli L, Caldairou B, Caligiuri ME, Calvet A, Cendes F, Concha L, Conde‐Blanco E, Davoodi‐Bojd E, de Bézenac C, Delanty N, Desmond PM, Devinsky O, Domin M, Duncan JS, Focke NK, Foley S, Fortunato F, Galovic M, Gambardella A, Gleichgerrcht E, Guerrini R, Hamandi K, Ives‐Deliperi V, Jackson GD, Jahanshad N, Keller SS, Kochunov P, Kotikalapudi R, Kreilkamp BAK, Labate A, Larivière S, Lenge M, Lui E, Malpas C, Martin P, Mascalchi M, Medland SE, Meletti S, Morita‐Sherman ME, Owen TW, Richardson M, Riva A, Rüber T, Sinclair B, Soltanian‐Zadeh H, Stein DJ, Striano P, Taylor P, Thomopoulos SI, Thompson PM, Tondelli M, Vaudano AE, Vivash L, Wang Y, Weber B, Whelan CD, Wiest R, Winston GP, Yasuda CL, McDonald CR, Alexander D, Sisodiya SM, Altmann A. Event-based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross-sectional data. Epilepsia 2022; 63:2081-2095. [PMID: 35656586 PMCID: PMC9540015 DOI: 10.1111/epi.17316] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/01/2022] [Accepted: 06/01/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features. METHODS We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. RESULTS In MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI. SIGNIFICANCE From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.
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Affiliation(s)
- Seymour M. Lopez
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Leon M. Aksman
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Neil P. Oxtoby
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
| | - Sjoerd B. Vos
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Neuroradiological Academic Unit, UCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Jun Rao
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Erik Kaestner
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Saud Alhusaini
- Department of NeurologyAlpert Medical School of Brown UniversityProvidenceRhode IslandUSA
- Department of Molecular and Cellular TherapeuticsRoyal College of Surgeons in IrelandDublinIreland
| | - Marina Alvim
- Department of Neurology and Neuroimaging LaboratoryUniversity of CampinasCampinasBrazil
| | - Benjamin Bender
- Department of Radiology, Diagnostic and Interventional NeuroradiologyUniversity Hospital TübingenTübingenGermany
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuebecCanada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuebecCanada
| | - Boris Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealQuebecCanada
| | | | - Lorenzo Caciagli
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealQuebecCanada
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
| | - Benoit Caldairou
- Neuroimaging of Epilepsy LaboratoryMontreal Neurological Institute, McGill UniversityMontrealQuebecCanada
| | - Maria Eugenia Caligiuri
- Neuroscience Research Center, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
| | - Angels Calvet
- Magnetic Resonance Image Core FacilityAugust Pi i Sunyer Biomedical Research Institute, University of BarcelonaBarcelonaSpain
| | - Fernando Cendes
- Department of Neurology and Neuroimaging LaboratoryUniversity of CampinasCampinasBrazil
| | - Luis Concha
- Institute of NeurobiologyNational Autonomous University of MexicoQuerétaroMexico
| | - Estefania Conde‐Blanco
- Epilepsy Program, Neurology DepartmentHospital Clinic of BarcelonaBarcelonaSpain
- August Pi i Sunyer Biomedical Research InstituteBarcelonaSpain
| | | | - Christophe de Bézenac
- Department of Pharmacology and TherapeuticsInstitute of Systems, Molecular and Integrative Biology, University of LiverpoolLiverpoolUK
| | - Norman Delanty
- Department of Molecular and Cellular TherapeuticsRoyal College of Surgeons in IrelandDublinIreland
- FutureNeuro SFI Research Centre for Rare and Chronic Neurological DiseasesDublinIreland
| | - Patricia M. Desmond
- Department of Radiology, Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
| | - Orrin Devinsky
- New York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Martin Domin
- Functional Imaging Unit, Department of Diagnostic Radiology and NeuroradiologyGreifswald University MedicineGreifswaldGermany
| | - John S. Duncan
- Department of NeurologyEmory UniversityAtlantaUSA
- Chalfont Centre for EpilepsyChalfont St PeterUK
| | - Niels K. Focke
- Department of NeurologyUniversity Medical CenterGöttingenGermany
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUK
| | - Francesco Fortunato
- Institute of Neurology, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
| | - Marian Galovic
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
- Department of NeurologyUniversity Hospital ZurichZurichSwitzerland
| | - Antonio Gambardella
- Neuroscience Research Center, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
- Institute of Neurology, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
| | | | - Renzo Guerrini
- Neuroscience DepartmentUniversity of FlorenceFlorenceItaly
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUK
- Wales Epilepsy Unit, Department of NeurologyUniversity Hospital of WalesCardiffUK
| | | | - Graeme D. Jackson
- Florey Institute of Neuroscience and Mental Health, Austin CampusHeidelbergVictoriaAustralia
- University of MelbourneParkvilleVictoriaAustralia
- Department of NeurologyAustin HealthHeidelbergVictoriaAustralia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Simon S. Keller
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Raviteja Kotikalapudi
- Department of Radiology, Diagnostic and Interventional NeuroradiologyUniversity Hospital TübingenTübingenGermany
- Department of Clinical NeurophysiologyUniversity Hospital GöttingenGöttingenGermany
- Department of Neurology and EpileptologyHertie Institute for Clinical Brain Research, University of TübingenTübingenGermany
| | - Barbara A. K. Kreilkamp
- Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
- Clinical NeurophysiologyUniversity Medical Center GöttingenGöttingenGermany
| | - Angelo Labate
- Neuroscience Research Center, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
- Institute of Neurology, Department of Medical and Surgical SciencesMagna Græcia University of CatanzaroCatanzaroItaly
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealQuebecCanada
| | - Matteo Lenge
- Pediatric Neurology, Neurogenetics and Neurobiology Unit and LaboratoriesA. Meyer Children's Hospital, University of FlorenceFlorenceItaly
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery DepartmentA. Meyer Children's Hospital, University of FlorenceFlorenceItaly
| | - Elaine Lui
- Department of Radiology, Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
| | - Charles Malpas
- Department of NeurologyRoyal Melbourne HospitalMelbourneVictoriaAustralia
- Department of Medicine, Royal Melbourne HospitalUniversity of MelbourneParkvilleVictoriaAustralia
| | - Pascal Martin
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Mario Mascalchi
- Mario Serio Department of Clinical and Experimental Medical SciencesUniversity of FlorenceFlorenceItaly
| | - Sarah E. Medland
- Psychiatric GeneticsQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Stefano Meletti
- Department of Biomedical, Metabolic, and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
- Neurology Unit, OCB HospitalModena University HospitalModenaItaly
| | - Marcia E. Morita‐Sherman
- Department of NeurologyUniversity of CampinasCampinasBrazil
- Cleveland Clinic Neurological InstituteClevelandOhioUSA
| | - Thomas W. Owen
- School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | | | - Antonella Riva
- Giannina Gaslini Institute, Scientific Institute for Research and Health CareGenoaItaly
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child HealthUniversity of GenoaGenoaItaly
| | - Theodor Rüber
- Department of EpileptologyUniversity Hospital BonnBonnGermany
| | - Ben Sinclair
- Department of Neuroscience, Central Clinical School, Alfred HospitalMonash UniversityMelbourneVictoriaAustralia
- Departments of Medicine and Radiology, Royal Melbourne HospitalUniversity of MelbourneParkvilleVictoriaAustralia
| | - Hamid Soltanian‐Zadeh
- Radiology and Research AdministrationHenry Ford Health SystemDetroitMichiganUSA
- School of Electrical and Computer EngineeringCollege of Engineering, University of TehranTehranIran
| | - Dan J. Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | - Pasquale Striano
- Giannina Gaslini Institute, Scientific Institute for Research and Health CareGenoaItaly
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child HealthUniversity of GenoaGenoaItaly
| | - Peter N. Taylor
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
- School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Manuela Tondelli
- Department of Biomedical, Metabolic, and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
- Primary Care DepartmentLocal Health Authority of ModenaModenaItaly
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic, and Neural SciencesUniversity of Modena and Reggio EmiliaModenaItaly
- Neurology Unit, OCB HospitalModena University HospitalModenaItaly
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred HospitalMonash UniversityMelbourneVictoriaAustralia
- Departments of Medicine and Radiology, Royal Melbourne HospitalUniversity of MelbourneParkvilleVictoriaAustralia
| | - Yujiang Wang
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
- School of ComputingNewcastle UniversityNewcastle Upon TyneUK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition ResearchUniversity of BonnBonnGermany
| | - Christopher D. Whelan
- Department of Molecular and Cellular TherapeuticsRoyal College of Surgeons in IrelandDublinIreland
| | - Roland Wiest
- Support Center for Advanced NeuroimagingUniversity Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of BernBernSwitzerland
| | - Gavin P. Winston
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
- Chalfont Centre for EpilepsyChalfont St PeterUK
- Department of Medicine, Division of NeurologyQueen's UniversityKingstonOntarioCanada
| | - Clarissa Lin Yasuda
- Department of Neurology and Neuroimaging LaboratoryUniversity of CampinasCampinasBrazil
| | - Carrie R. McDonald
- Department of PsychiatryUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Daniel C. Alexander
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental EpilepsyUCL Queen Square Institute of Neurology, University College LondonLondonUK
- Chalfont Centre for EpilepsyChalfont St PeterUK
| | - Andre Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
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Larivière S, Royer J, Rodríguez-Cruces R, Paquola C, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Yasuda CL, Bonilha L, Gleichgerrcht E, Focke NK, Domin M, von Podewills F, Langner S, Rummel C, Wiest R, Martin P, Kotikalapudi R, O'Brien TJ, Sinclair B, Vivash L, Desmond PM, Lui E, Vaudano AE, Meletti S, Tondelli M, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Winston GP, Griffin A, Singh A, Tiwari VK, Kreilkamp BAK, Lenge M, Guerrini R, Hamandi K, Foley S, Rüber T, Weber B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Severino M, Striano P, Tortora D, Kaestner E, Hatton SN, Vos SB, Caciagli L, Duncan JS, Whelan CD, Thompson PM, Sisodiya SM, Bernasconi A, Labate A, McDonald CR, Bernasconi N, Bernhardt BC. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression. Nat Commun 2022; 13:4320. [PMID: 35896547 PMCID: PMC9329287 DOI: 10.1038/s41467-022-31730-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 06/30/2022] [Indexed: 12/12/2022] Open
Abstract
Epilepsy is associated with genetic risk factors and cortico-subcortical network alterations, but associations between neurobiological mechanisms and macroscale connectomics remain unclear. This multisite ENIGMA-Epilepsy study examined whole-brain structural covariance networks in patients with epilepsy and related findings to postmortem epilepsy risk gene expression patterns. Brain network analysis included 578 adults with temporal lobe epilepsy (TLE), 288 adults with idiopathic generalized epilepsy (IGE), and 1328 healthy controls from 18 centres worldwide. Graph theoretical analysis of structural covariance networks revealed increased clustering and path length in orbitofrontal and temporal regions in TLE, suggesting a shift towards network regularization. Conversely, people with IGE showed decreased clustering and path length in fronto-temporo-parietal cortices, indicating a random network configuration. Syndrome-specific topological alterations reflected expression patterns of risk genes for hippocampal sclerosis in TLE and for generalized epilepsy in IGE. These imaging-transcriptomic signatures could potentially guide diagnosis or tailor therapeutic approaches to specific epilepsy syndromes.
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Affiliation(s)
- Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Casey Paquola
- Institute for Neuroscience and Medicine (INM-1), Forschungszentrum Jülich, Jülich, Germany
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Fernando Cendes
- Department of Neurology, University of Campinas-UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa L Yasuda
- Department of Neurology, University of Campinas-UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K Focke
- Department of Neurology, University of Medicine Göttingen, Göttingen, Germany
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewills
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Melbourne, VIC, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Melbourne, VIC, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Melbourne, VIC, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Patricia M Desmond
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Elaine Lui
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, VIC, Australia
| | - Anna Elisabetta Vaudano
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, OCB Hospital, Azienda Ospedaliera-Universitaria, Modena, Italy
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Department of Biomedical, Metabolic and Neural Science, University of Modena and Reggio Emilia, Modena, Italy
- Primary Care Department, Azienda Sanitaria Locale di Modena, Modena, Italy
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Colin P Doherty
- Department of Neurology, St James' Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Rhys H Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Contol and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Cognitive Science Department, Xiamen University, Xiamen, China
| | - Gavin P Winston
- Division of Neurology, Department of Medicine, Queen's University, Kingston, ON, Canada
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Aoife Griffin
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry & Biomedical Science, Queens University Belfast, Belfast, UK
| | - Aditi Singh
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry & Biomedical Science, Queens University Belfast, Belfast, UK
| | - Vijay K Tiwari
- Wellcome-Wolfson Institute for Experimental Medicine, School of Medicine, Dentistry & Biomedical Science, Queens University Belfast, Belfast, UK
| | | | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Children's Hospital A. Meyer-University of Florence, Florence, Italy
| | - Khalid Hamandi
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Whales, Cardiff, UK
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
| | - Theodor Rüber
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, Goethe-University Frankfurt, Frankfurt am Main, Germany
- Center for Personalized Translational Epilepsy Research (CePTER), Goethe-University Frankfurt, Frankfurt am Main, Germany
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J A Carr
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eugenio Abela
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mark P Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, US
| | | | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Erik Kaestner
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, US
| | - Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, US
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Christopher D Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, US
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Angelo Labate
- Neurology, BIOMORF Dipartment, University of Messina, Messina, Italy
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, US
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
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Lekoubou A, Ba DM, Nguyen C, Liu G, Leslie DL, Bonilha L, Vernon CM. Poststroke Seizures and the Risk of Dementia Among Young Stroke Survivors. Neurology 2022; 99:e385-e392. [PMID: 35584925 PMCID: PMC9421769 DOI: 10.1212/wnl.0000000000200736] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Accepted: 03/30/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The effect of new-onset seizures in young stroke survivors on the subsequent development of dementia is poorly understood. This study aimed to assess the association between new onset of seizure and dementia in a population-based study of patients with stroke. METHODS The IBM Watson Health MarketScan Commercial Claims and Encounters database for the years 2005-2014 served as the data source for this study. Using the International Classification of Diseases, Ninth Revision (ICD-9), we identified patients aged 18-60 years with ischemic strokes (ISs; 433.x1, 434.x1, and 436) and hemorrhagic strokes (HSs; 430, 431, 432.0, 432.1, and 432.9) between January 1, 2006, and December 31, 2009, which constituted our baseline study cohort. At baseline, all included participants were free of claims for dementia, brain tumors, toxin exposure, traumatic brain injury, and neuroinfectious diseases, identified using ICD-9 codes. They had at least 1-year continuous enrollment before the index stroke diagnosis and 5 years after, with no seizure claims within 1 year after the index date. The exposure of interest was seizures: a time-dependent variable. The study outcome of interest was dementia (ICD-9: 290.0, 290.10-13, 290.20-21, 290.3, 290.40-43, 291.2, 292.82, 294.10-11, 294.20-21, 294.8, 331.0, 331.11, 331.19, and 331.82), which occurred during the follow-up period from January 1, 2010, to December 31, 2014. A Cox proportional hazards regression model was applied to calculate the hazard ratio (HR) and 95% CI for the independent association of seizures with the occurrence of dementia. RESULTS At the end of the baseline period, we identified 23,680 patients with stroke (IS: 20,642 and HS: 3,038). The cumulative incidence of seizure was 6.7%, 6.4%, and 8.3% for all strokes, IS, and HS, respectively. The cumulative incidence of dementia was 1.3%, 1.4%, and 0.9% for all strokes, IS, and HS, respectively. After multivariable adjustment, young patients with stroke who developed seizures had a greater risk of dementia compared with those without seizures (all strokes adjusted HR: 2.53, 95% CI 1.84-3.48; IS: 2.52, 1.79-3.53; HS: 2.80, 1.05-7.43). DISCUSSION These findings suggest that the onset of seizures in young stroke survivors is associated with a 2.53 times increased risk of developing dementia. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that poststroke seizures increase the probability of dementia in young stroke survivors.
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Affiliation(s)
- Alain Lekoubou
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston.
| | - Djibril M Ba
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
| | - Clever Nguyen
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
| | - Guodong Liu
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
| | - Douglas L Leslie
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
| | - Leonardo Bonilha
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
| | - Chinchilli M Vernon
- From the Department of Neurology (A.L., C.N.), Penn State University, Hershey Medical Center; Department of Public Health Sciences (D.M.B., G.L., D.L.L., C.M.V.), Penn State College of Medicine, Hershey; and Department of Neurology (L.B.), Medical University of South Carolina, Charleston
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48
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Matchin W, den Ouden DB, Hickok G, Hillis AE, Bonilha L, Fridriksson J. The Wernicke conundrum revisited: evidence from connectome-based lesion-symptom mapping. Brain 2022; 145:3916-3930. [PMID: 35727949 DOI: 10.1093/brain/awac219] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 05/25/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
Wernicke's area has been assumed since the 1800s to be the primary region supporting word and sentence comprehension. However, in 2015 and 2019, Mesulam and colleagues raised what they termed the 'Wernicke conundrum', noting widespread variability in the anatomical definition of this area and presenting data from primary progressive aphasia that challenged this classical assumption. To resolve the conundrum, they posited a 'double disconnection' hypothesis: that word and sentence comprehension deficits in stroke-based aphasia result from disconnection of anterior temporal and inferior frontal regions from other parts of the brain due to white matter damage, rather than dysfunction of Wernicke's area itself. To test this hypothesis, we performed lesion-deficit correlations, including connectome-based lesion-symptom mapping, in four large, partially overlapping groups of English-speaking chronic left hemisphere stroke survivors. After removing variance due to object recognition and associative semantic processing, the same middle and posterior temporal lobe regions were implicated in both word comprehension deficits and complex noncanonical sentence comprehension deficits. Connectome lesion-symptom mapping revealed similar temporal-occipital white matter disconnections for impaired word and noncanonical sentence comprehension, including the temporal pole. We found an additional significant temporal-parietal disconnection for noncanonical sentence comprehension deficits, which may indicate a role for phonological working memory in processing complex syntax, but no significant frontal disconnections. Moreover, damage to these middle-posterior temporal lobe regions was associated with both word and noncanonical sentence comprehension deficits even when accounting for variance due to the strongest anterior temporal and inferior frontal white matter disconnections, respectively. Our results largely agree with the classical notion that Wernicke's area, defined here as middle superior temporal gyrus and middle-posterior superior temporal sulcus, supports both word and sentence comprehension, suggest a supporting role for temporal pole in both word and sentence comprehension, and speak against the hypothesis that comprehension deficits in Wernicke's aphasia result from double disconnection.
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Affiliation(s)
- William Matchin
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Dirk Bart den Ouden
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
| | - Gregory Hickok
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697, USA.,Department of Language Science, University of California, Irvine, Irvine, CA 92697, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA.,Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA.,Department of Cognitive Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC 29208, USA
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49
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Gross WL, Helfand AI, Swanson SJ, Conant LL, Humphries CJ, Raghavan M, Mueller WM, Busch RM, Allen L, Anderson CT, Carlson CE, Lowe MJ, Langfitt JT, Tivarus ME, Drane DL, Loring DW, Jacobs M, Morgan VL, Allendorfer JB, Szaflarski JP, Bonilha L, Bookheimer S, Grabowski T, Vannest J, Binder JR. Prediction of Naming Outcome With fMRI Language Lateralization in Left Temporal Epilepsy Surgery. Neurology 2022; 98:e2337-e2346. [PMID: 35410903 PMCID: PMC9202528 DOI: 10.1212/wnl.0000000000200552] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 03/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Naming decline after left temporal lobe epilepsy (TLE) surgery is common and difficult to predict. Preoperative language fMRI may predict naming decline, but this application is still lacking evidence. We performed a large multicenter cohort study of the effectiveness of fMRI in predicting naming deficits after left TLE surgery. METHODS At 10 US epilepsy centers, 81 patients with left TLE were prospectively recruited and given the Boston Naming Test (BNT) before and ≈7 months after anterior temporal lobectomy. An fMRI language laterality index (LI) was measured with an auditory semantic decision-tone decision task contrast. Correlations and a multiple regression model were built with a priori chosen predictors. RESULTS Naming decline occurred in 56% of patients and correlated with fMRI LI (r = -0.41, p < 0.001), age at epilepsy onset (r = -0.30, p = 0.006), age at surgery (r = -0.23, p = 0.039), and years of education (r = 0.24, p = 0.032). Preoperative BNT score and duration of epilepsy were not correlated with naming decline. The regression model explained 31% of the variance, with fMRI contributing 14%, with a 96% sensitivity and 44% specificity for predicting meaningful naming decline. Cross-validation resulted in an average prediction error of 6 points. DISCUSSION An fMRI-based regression model predicted naming outcome after left TLE surgery in a large, prospective multicenter sample, with fMRI as the strongest predictor. These results provide evidence supporting the use of preoperative language fMRI to predict language outcome in patients undergoing left TLE surgery. CLASSIFICATION OF EVIDENCE This study provides Class I evidence that fMRI language lateralization can help in predicting naming decline after left TLE surgery.
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Affiliation(s)
- William Louis Gross
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH.
| | - Alexander I Helfand
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Sara J Swanson
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Lisa L Conant
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Colin J Humphries
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Manoj Raghavan
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Wade M Mueller
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Robyn M Busch
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Linda Allen
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Christopher Todd Anderson
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Chad E Carlson
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Mark J Lowe
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - John T Langfitt
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Madalina E Tivarus
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Daniel L Drane
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - David W Loring
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Monica Jacobs
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Victoria L Morgan
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Jane B Allendorfer
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Jerzy P Szaflarski
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Leonardo Bonilha
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Susan Bookheimer
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Thomas Grabowski
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Jennifer Vannest
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
| | - Jeffrey R Binder
- From the Departments of Neurology (W.L.G., A.H., S.J.S., L.L.C., C.H., M.R., L.A., C.T.A., C.E.C., J.R.B.), Anesthesiology (W.L.G.), and Neurosurgery (W.M.M.), Medical College of Wisconsin, Milwaukee; Departments of Neurology (R.M.B.) and Radiology (M.J.L.), Cleveland Clinic Foundation, OH; Departments of Neurology (J.T.L.) and Imaging Sciences (M.E.T.), University of Rochester, NY; Departments of Neurology (D.L.D., D.W.L.) and Pediatrics (D.L.D.), Emory University, Atlanta, GA; Department of Neurology (D.L.D., T.G.), University of Washington, Seattle; Departments of Psychology (M.J.) and Radiology (V.L.M.), Vanderbilt University Medical Center, Nashville, TN; Department of Neurology (J.B.A., J.P.S.), University of Alabama at Birmingham; Department of Neurology (L.B.), Medical University of South Carolina, Charleston; Department of Neurology (S.B.), University of California, Los Angeles; and Department of Neurology (J.V.), University of Cincinnati, OH
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Park BY, Larivière S, Rodríguez-Cruces R, Royer J, Tavakol S, Wang Y, Caciagli L, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Alvim MKM, Yasuda C, Bonilha L, Gleichgerrcht E, Focke NK, Kreilkamp BAK, Domin M, von Podewils F, Langner S, Rummel C, Rebsamen M, Wiest R, Martin P, Kotikalapudi R, Bender B, O’Brien TJ, Law M, Sinclair B, Vivash L, Kwan P, Desmond PM, Malpas CB, Lui E, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Weber B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Severino M, Striano P, Parodi C, Tortora D, Hatton SN, Vos SB, Duncan JS, Galovic M, Whelan CD, Bargalló N, Pariente J, Conde-Blanco E, Vaudano AE, Tondelli M, Meletti S, Kong X, Francks C, Fisher SE, Caldairou B, Ryten M, Labate A, Sisodiya SM, Thompson PM, McDonald CR, Bernasconi A, Bernasconi N, Bernhardt BC. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy. Brain 2022; 145:1285-1298. [PMID: 35333312 PMCID: PMC9128824 DOI: 10.1093/brain/awab417] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 07/15/2021] [Accepted: 08/14/2021] [Indexed: 12/20/2022] Open
Abstract
Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine our notion of the neuropathology of temporal lobe epilepsy and may inform future discovery and validation of complementary MRI biomarkers in temporal lobe epilepsy.
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Affiliation(s)
- Bo-yong Park
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Data Science, Inha University, Incheon, Republic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raul Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Yezhou Wang
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Fernando Cendes
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | - Marina K M Alvim
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas–UNICAMP, Campinas, São Paulo, Brazil
| | | | | | - Niels K Focke
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewils
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Michael Rebsamen
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Benjamin Bender
- Department of Radiology, Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Terence J O’Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Meng Law
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patrick Kwan
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M Desmond
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Charles B Malpas
- Departments of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Elaine Lui
- Department of Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Colin P Doherty
- Department of Neurology, St James’ Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, Member of the European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Rhys H Thomas
- Transitional and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Department of Artificial Intelligence, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Children’s Hospital A. Meyer-University of Florence, Florence, Italy
| | - Emanuele Bartolini
- USL Centro Toscana, Neurology Unit, Nuovo Ospedale Santo Stefano, Prato, Italy
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
- The Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J A Carr
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Eugenio Abela
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Mark P Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariasavina Severino
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Pasquale Striano
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Costanza Parodi
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Domenico Tortora
- IRCCS Istituto Giannina Gaslini, Genova, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genova, Genova, Italy
| | - Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Marian Galovic
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
- Department of Neurology, Clinical Neuroscience Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Christopher D Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Núria Bargalló
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Department of Radiology CDIC, Hospital Clinic Barcelona, Barcelona, Spain
| | - Jose Pariente
- Magnetic Resonance Image Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Manuela Tondelli
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Stefano Meletti
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, Modena, Italy
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Xiang‐Zhen Kong
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China
| | - Clyde Francks
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Simon E Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Benoit Caldairou
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Mina Ryten
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, University College London, London, UK
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Angelo Labate
- Neurology, BIOMORF Department, University of Messina, Messina, Italy
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Epilepsy Society, Chalfont St Peter, Buckinghamshire, UK
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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