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Luckett PH, Olufawo MO, Park KY, Lamichhane B, Dierker D, Verastegui GT, Lee JJ, Yang P, Kim A, Butt OH, Chheda MG, Snyder AZ, Shimony JS, Leuthardt EC. Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning. J Neurooncol 2024; 169:175-185. [PMID: 38789843 DOI: 10.1007/s11060-024-04715-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
PURPOSE High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.
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Affiliation(s)
- Patrick H Luckett
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA.
| | - Michael O Olufawo
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Ki Yun Park
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Bidhan Lamichhane
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Center for Health Sciences, Oklahoma State University, Tulsa, OK, USA
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - John J Lee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Peter Yang
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Albert Kim
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
| | - Omar H Butt
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Milan G Chheda
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Abraham Z Snyder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric C Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
- Department of Mechanical Engineering and Materials Science, Washington University in Saint Louis, St. Louis, MO, USA
- Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, USA
- Brain Laser Center, Washington University School of Medicine, St. Louis, MO, USA
- National Center for Adaptive Neurotechnologies, Albany, NY, USA
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2
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Salvalaggio A, Pini L, Bertoldo A, Corbetta M. Glioblastoma and brain connectivity: the need for a paradigm shift. Lancet Neurol 2024; 23:740-748. [PMID: 38876751 DOI: 10.1016/s1474-4422(24)00160-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/29/2024] [Accepted: 04/03/2024] [Indexed: 06/16/2024]
Abstract
Despite substantial advances in cancer treatment, for patients with glioblastoma prognosis remains bleak. The emerging field of cancer neuroscience reveals intricate functional interplays between glioblastoma and the cellular architecture of the brain, encompassing neurons, glia, and vessels. New findings underscore the role of structural and functional connections within hierarchical networks, known as the connectome. These connections contribute to the location, spread, and recurrence of a glioblastoma, and a patient's overall survival, revealing a complex interplay between the tumour and the CNS. This mounting evidence prompts a paradigm shift, challenging the perception of glioblastomas as mere foreign bodies within the brain. Instead, these tumours are intricately woven into the structural and functional fabric of the brain. This radical change in thinking holds profound implications for the understanding and treatment of glioblastomas, which could unveil new prognostic factors and surgical strategies and optimise radiotherapy. Additionally, a connectivity approach suggests that non-invasive brain stimulation could disrupt pathological neuron-glioma interactions within specific networks.
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Affiliation(s)
- Alessandro Salvalaggio
- Clinica Neurologica, Azienda Ospedale Università Padova, Padova, Italy; Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Lorenzo Pini
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Information Engineering, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Azienda Ospedale Università Padova, Padova, Italy; Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy; Veneto Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy.
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3
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Tanaka M, Vécsei L. A Decade of Dedication: Pioneering Perspectives on Neurological Diseases and Mental Illnesses. Biomedicines 2024; 12:1083. [PMID: 38791045 PMCID: PMC11117868 DOI: 10.3390/biomedicines12051083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024] Open
Abstract
Welcome to Biomedicines' 10th Anniversary Special Issue, a journey through the human mind's labyrinth and complex neurological pathways [...].
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Affiliation(s)
- Masaru Tanaka
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged, Danube Neuroscience Research Laboratory, Tisza Lajos krt. 113, H-6725 Szeged, Hungary;
| | - László Vécsei
- HUN-REN-SZTE Neuroscience Research Group, Hungarian Research Network, University of Szeged, Danube Neuroscience Research Laboratory, Tisza Lajos krt. 113, H-6725 Szeged, Hungary;
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Semmelweis u. 6, H-6725 Szeged, Hungary
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4
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Latifi S, Carmichael ST. The emergence of multiscale connectomics-based approaches in stroke recovery. Trends Neurosci 2024; 47:303-318. [PMID: 38402008 DOI: 10.1016/j.tins.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/31/2023] [Accepted: 01/21/2024] [Indexed: 02/26/2024]
Abstract
Stroke is a leading cause of adult disability. Understanding stroke damage and recovery requires deciphering changes in complex brain networks across different spatiotemporal scales. While recent developments in brain readout technologies and progress in complex network modeling have revolutionized current understanding of the effects of stroke on brain networks at a macroscale, reorganization of smaller scale brain networks remains incompletely understood. In this review, we use a conceptual framework of graph theory to define brain networks from nano- to macroscales. Highlighting stroke-related brain connectivity studies at multiple scales, we argue that multiscale connectomics-based approaches may provide new routes to better evaluate brain structural and functional remapping after stroke and during recovery.
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Affiliation(s)
- Shahrzad Latifi
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA; Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA
| | - S Thomas Carmichael
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.
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5
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Dai Z, Song L, Luo C, Liu D, Li M, Han Z. Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups. Cereb Cortex 2024; 34:bhad437. [PMID: 38031356 DOI: 10.1093/cercor/bhad437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 10/27/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
The hemispheric laterality of language processing has become a hot topic in modern neuroscience. Although most previous studies have reported left-lateralized language processing, other studies found it to be bilateral. A previous neurocomputational model has proposed a unified framework to explain that the above discrepancy might be from healthy and patient individuals. This model posits an initial symmetry but imbalanced capacity in language processing for healthy individuals, with this imbalance contributing to language recovery disparities following different hemispheric injuries. The present study investigated this model by analyzing the lateralization patterns of language subnetworks across multiple attributes with a group of 99 patients (compared to nonlanguage processing) and examining the lateralization patterns of language subnetworks in subgroups with damage to different hemispheres. Subnetworks were identified using a whole-brain network-based lesion-symptom mapping method, and the lateralization index was quantitatively measured. We found that all the subnetworks in language processing were left-lateralized, while subnetworks in nonlanguage processing had different lateralization patterns. Moreover, diverse hemisphere-injury subgroups exhibited distinct language recovery effects. These findings provide robust support for the proposed neurocomputational model of language processing.
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Affiliation(s)
- Zhiyun Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Luping Song
- Shenzhen Sixth People's Hospital (Nanshan Hospital), Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen 518052, China
| | - Chongjing Luo
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Di Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou 310027, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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6
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Yoon KJ, Park CH, Rho MH, Kim M. Disconnection-Based Prediction of Poststroke Dysphagia. AJNR Am J Neuroradiol 2023; 45:57-65. [PMID: 38164540 PMCID: PMC10756566 DOI: 10.3174/ajnr.a8074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 10/24/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND PURPOSE Dysphagia is a common deficit after a stroke and is associated with serious complications. It is not yet fully clear which brain regions are directly related to swallowing. Previous lesion symptom mapping studies may have overlooked structural disconnections that could be responsible for poststroke dysphagia. Here, we aimed to predict and explain the relationship between poststroke dysphagia and the topologic distribution of structural disconnection via a multivariate predictive framework. MATERIALS AND METHODS We enrolled first-ever ischemic stroke patients classified as full per-oral nutrition (71 patients) and nonoral nutrition necessary (43 patients). After propensity score matching, 43 patients for each group were enrolled (full per-oral nutrition group with 17 women, 68 ± 15 years; nonoral nutrition necessary group with 13 women, 75 ± 11 years). The structural disconnectome was estimated by using the lesion segmented from acute phase diffusion-weighted images. The prediction of poststroke dysphagia by using the structural disconnectome and demographics was performed in a leave-one-out manner. RESULTS Using both direct and indirect disconnection matrices of the motor network, the disconnectome-based prediction model could predict poststroke dysphagia above the level of chance (accuracy = 68.6%, permutation P = .001). When combined with demographic data, the classification accuracy reached 72.1%. The edges connecting the right insula and left motor strip were the most informative in prediction. CONCLUSIONS Poststroke dysphagia could be predicted by using the structural disconnectome derived from acute phase diffusion-weighted images. Specifically, the direct and indirect disconnection within the motor network was the most informative in predicting poststroke dysphagia.
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Affiliation(s)
- Kyung Jae Yoon
- From the Department of Physical and Rehabilitation Medicine (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
- Medical Research Institute (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
| | - Chul-Hyun Park
- From the Department of Physical and Rehabilitation Medicine (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
- Medical Research Institute (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
| | - Myung-Ho Rho
- Department of Radiology (M.-H.R., M.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Minchul Kim
- Department of Radiology (M.-H.R., M.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
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Kim M, Choi KS, Hyun RC, Hwang I, Kwon YN, Sung JJ, Kim SM, Kim JH. Structural disconnection is associated with disability in the neuromyelitis optica spectrum disorder. Brain Imaging Behav 2023; 17:664-673. [PMID: 37676409 DOI: 10.1007/s11682-023-00792-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/28/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVES Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune inflammatory disease of the central nervous system. Accumulating evidence suggests there is a distinct pattern of brain lesions characteristic of NMOSD, and brain MRI has potential prognostic implications. However, the question of how the brain lesions in NMOSD are associated with its distinct clinical course remains incompletely understood. Here, we aimed to investigate the association between neurological impairment and brain lesions via brain structural disconnection. METHODS Twenty patients were diagnosed with NMOSD according to the 2015 International Panel for NMO Diagnosis criteria. The white matter lesions were manually drawn section by section. Whole-brain structural disconnection was estimated, and connectome-based predictive modeling (CPM) was used to estimate the patient's Expanded Disability Status Scale score (EDSS) from their disconnection severity matrix. Furthermore, correlational tractography was performed to assess the fractional anisotropy (FA) and axial diffusivity (AD) of white matter fibers, which negatively correlated with the EDSS score. RESULTS CPM successfully predicted the EDSS using the disconnection severity matrix (r = 0.506, p = 0.028; q2 = 0.274). Among the important edges in the prediction process, the majority of edges connected the motor to the frontoparietal network. Correlational tractography identified a decreased FA and AD value according to EDSS scores in periependymal white matter tracts. DISCUSSION Structural disconnection-based predictive modeling and local connectome analysis showed that frontoparietal and periependymal white matter disconnection is predictive and associated with the EDSS score of NMOSD patients.
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Affiliation(s)
- Minchul Kim
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Ryoo Chang Hyun
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Young Nam Kwon
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Jung-Joon Sung
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Sung Min Kim
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea.
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea.
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8
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Nozais V, Forkel SJ, Petit L, Talozzi L, Corbetta M, Thiebaut de Schotten M, Joliot M. Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain. Commun Biol 2023; 6:726. [PMID: 37452124 PMCID: PMC10349117 DOI: 10.1038/s42003-023-05107-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 07/06/2023] [Indexed: 07/18/2023] Open
Abstract
Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.
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Affiliation(s)
- Victor Nozais
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Donders Institute for Brain Cognition Behaviour, Radboud University, Nijmegen, the Netherlands
- Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Departments of Neurosurgery, Technical University of Munich School of Medicine, Munich, Germany
| | - Laurent Petit
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
| | - Lia Talozzi
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Department of Neurology, Stanford University, Stanford, CA, USA
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine and Padova Neuroscience Center, University of Padua, Padova, PD, 32122, Italy
| | - Michel Thiebaut de Schotten
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
| | - Marc Joliot
- Univ. Bordeaux, CNRS, CEA, IMN, UMR 5293, GIN, F-33000, Bordeaux, France.
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Zou J, Yin Y, Lin Z, Gong Y. The analysis of brain functional connectivity of post-stroke cognitive impairment patients: an fNIRS study. Front Neurosci 2023; 17:1168773. [PMID: 37214384 PMCID: PMC10196111 DOI: 10.3389/fnins.2023.1168773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 04/18/2023] [Indexed: 05/24/2023] Open
Abstract
Background Post-stroke cognitive impairment (PSCI) is a considerable risk factor for developing dementia and reoccurrence of stroke. Understanding the neural mechanisms of cognitive impairment after stroke can facilitate early identification and intervention. Objectives Using functional near-infrared spectroscopy (fNRIS), the present study aimed to examine whether resting-state functional connectivity (FC) of brain networks differs in patients with PSCI, patients with Non-PSCI (NPSCI), and healthy controls (HCs), and whether these features could be used for clinical diagnosis of PSCI. Methods The present study recruited 16 HCs and 32 post-stroke patients. Based on the diagnostic criteria of PSCI, post-stroke patients were divided to the PSCI or NPSCI group. All participants underwent a 6-min resting-state fNRIS test to measure the hemodynamic responses from regions of interests (ROIs) that were primarily distributed in the prefrontal, somatosensory, and motor cortices. Results The results showed that, when compared to the HC group, the PSCI group exhibited significantly decreased interhemispheric FC and intra-right hemispheric FC. ROI analyses showed significantly decreased FC among the regions of somatosensory cortex, dorsolateral prefrontal cortex, and medial prefrontal cortex for the PSCI group than for the HC group. However, no significant difference was found in the FC between the PSCI and the NPSCI groups. Conclusion Our findings provide evidence for compromised interhemispheric and intra-right hemispheric functional connectivity in patients with PSCI, suggesting that fNIRS is a promising approach to investigate the effects of stroke on functional connectivity of brain networks.
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Affiliation(s)
- Jiahuan Zou
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu,Sichuan, China
| | - Yongyan Yin
- School of Medical and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu,Sichuan, China
| | - Zhenfang Lin
- Department of Neurology, Sichuan Bayi Rehabilitation Center (Sichuan Provincial Rehabilitation Hospital), Chengdu, Sichuan, China
| | - Yulai Gong
- Department of Neurology, Sichuan Bayi Rehabilitation Center (Sichuan Provincial Rehabilitation Hospital), Chengdu, Sichuan, China
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Schaechter JD, Kim M, Hightower BG, Ragas T, Loggia ML. Disruptions in Structural and Functional Connectivity Relate to Poststroke Fatigue. Brain Connect 2023; 13:15-27. [PMID: 35570655 PMCID: PMC9942175 DOI: 10.1089/brain.2022.0021] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction: Poststroke fatigue (PSF) is a disabling condition with unclear etiology. The brain lesion is thought to be an important causal factor in PSF, although focal lesion characteristics such as size and location have not proven to be predictive. Given that the stroke lesion results not only in focal tissue death but also in widespread changes in brain networks that are structurally and functionally connected to damaged tissue, we hypothesized that PSF relates to disruptions in structural and functional connectivity. Materials and Methods: Twelve patients who incurred an ischemic stroke in the middle cerebral artery (MCA) territory 1-3 years prior, and currently experiencing a range of fatigue severity, were enrolled. The patients underwent structural and resting-state functional magnetic resonance imaging (MRI). The structural MRI data were used to measure structural disconnection of gray matter resulting from lesion to white matter pathways. The functional MRI data were used to measure network functional connectivity. Results: The patients showed structural disconnection in varying cortical and subcortical regions. Fatigue severity correlated significantly with structural disconnection of several frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres. Fatigue-related structural disconnection was most severe in the IL rostral middle frontal cortex. Greater structural disconnection of a subset of fatigue-related frontal cortex regions, including the IL rostral middle frontal cortex, trended toward correlating significantly with greater loss in functional connectivity. Among identified fatigue-related frontal cortex regions, only the IL rostral middle frontal cortex showed loss in functional connectivity correlating significantly with fatigue severity. Conclusion: Our results provide evidence that loss in structural and functional connectivity of bihemispheric frontal cortex regions plays a role in PSF after MCA stroke, with connectivity disruptions of the IL rostral middle frontal cortex having a central role. Impact statement Poststroke fatigue (PSF) is a common disabling condition with unclear etiology. We hypothesized that PSF relates to disruptions in structural and functional connectivity secondary to the focal lesion. Using structural and resting-state functional connectivity magnetic resonance imaging (MRI) in patients with chronic middle cerebral artery (MCA) stroke, we found frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres with greater structural disconnection correlating with greater fatigue. Among these fatigue-related cortices, the IL rostral middle frontal cortex showed loss in functional connectivity correlating with fatigue. These findings suggest that disruptions in structural and functional connectivity play a role in PSF after MCA stroke.
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Affiliation(s)
- Judith D. Schaechter
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Minhae Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Baileigh G. Hightower
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Trevor Ragas
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Marco L. Loggia
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
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Rivier C, Preti MG, Nicolo P, Van De Ville D, Guggisberg AG, Pirondini E. Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages. Brain Commun 2023; 5:fcad055. [PMID: 36938525 PMCID: PMC10016810 DOI: 10.1093/braincomms/fcad055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 11/04/2022] [Accepted: 02/28/2023] [Indexed: 03/05/2023] Open
Abstract
Following a stroke in regions of the brain responsible for motor activity, patients can lose their ability to control parts of their body. Over time, some patients recover almost completely, while others barely recover at all. It is known that lesion volume, initial motor impairment and cortico-spinal tract asymmetry significantly impact motor changes over time. Recent work suggested that disabilities arise not only from focal structural changes but also from widespread alterations in inter-regional connectivity. Models that consider damage to the entire network instead of only local structural alterations lead to a more accurate prediction of patients' recovery. However, assessing white matter connections in stroke patients is challenging and time-consuming. Here, we evaluated in a data set of 37 patients whether we could predict upper extremity motor recovery from brain connectivity measures obtained by using the patient's lesion mask to introduce virtual lesions in 60 healthy streamline tractography connectomes. This indirect estimation of the stroke impact on the whole brain connectome is more readily available than direct measures of structural connectivity obtained with magnetic resonance imaging. We added these measures to benchmark structural features, and we used a ridge regression regularization to predict motor recovery at 3 months post-injury. As hypothesized, accuracy in prediction significantly increased (R 2 = 0.68) as compared to benchmark features (R 2 = 0.38). This improved prediction of recovery could be beneficial to clinical care and might allow for a better choice of intervention.
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Affiliation(s)
- Cyprien Rivier
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva 1202, Switzerland
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Maria Giulia Preti
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva 1202, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne 1015, Switzerland
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
| | - Pierre Nicolo
- University of Applied Sciences and Arts Western Switzerland, Delémont 2800, Switzerland
| | - Dimitri Van De Ville
- Medical Image Processing Laboratory, Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne 1015, Switzerland
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva 1202, Switzerland
| | - Adrian G Guggisberg
- Universitäre Neurorehabilitation, University Hospital of Berne, Inselspital, Berne 3010, Switzerland
- Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospital of Geneva, Geneva 1205, Switzerland
| | - Elvira Pirondini
- Correspondence to: Elvira Pirondini Rehabilitation and Neural Engineering Laboratories University of Pittsburgh 3520, Fifth Av., Suite 311, Pittsburgh 15213, PA, USA E-mail:
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12
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Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients. Sci Rep 2022; 12:22400. [PMID: 36575263 PMCID: PMC9794717 DOI: 10.1038/s41598-022-26945-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.
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13
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Zevgolatakou E, Thye M, Mirman D. Behavioural and neural structure of fluent speech production deficits in aphasia. Brain Commun 2022; 5:fcac327. [PMID: 36601623 PMCID: PMC9798301 DOI: 10.1093/braincomms/fcac327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/03/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
Deficits in fluent speech production following left hemisphere stroke are a central concern because of their impact on patients' lives and the insight they provide about the neural organization of language processing. Fluent speech production requires the rapid coordination of phonological, semantic, and syntactic processing, so this study examined how deficits in connected speech relate to these language sub-systems. Behavioural data (N = 69 participants with aphasia following left hemisphere stroke) consisted of a diverse and comprehensive set of narrative speech production measures and measures of overall severity, semantic deficits, and phonological deficits. These measures were entered into a principal component analysis with bifactor rotation-a latent structure model where each item loads on a general factor that reflects what is common among the items, and orthogonal factors that explain variance not accounted for by the general factor. Lesion data were available for 58 of the participants, and each factor score was analysed with multivariate lesion-symptom mapping. Effects of connectivity disruption were evaluated using robust regression with tract disconnection or graph theoretic measures of connectivity as predictors. The principal component analysis produced a four-factor solution that accounted for 70.6% of the variance in the data, with a general factor corresponding to the overall severity and length and complexity of speech output (complexity factor), a lexical syntax factor, and independent factors for Semantics and Phonology. Deficits in the complexity of speech output were associated with a large temporo-parietal region, similar to overall aphasia severity. The lexical syntax factor was associated with damage in a relatively small set of fronto-parietal regions which may reflect the recruitment of control systems to support retrieval and correct usage of lexical items that primarily serve a syntactic rather than semantic function. Tract-based measures of connectivity disruption were not statistically associated with the deficit scores after controlling for overall lesion volume. Language network efficiency and average clustering coefficient within the language network were significantly associated with deficit scores after controlling for overall lesion volume. These results highlight overall severity as the critical contributor to fluent speech in post-stroke aphasia, with a dissociable factor corresponding to lexical syntax.
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Affiliation(s)
- Eleni Zevgolatakou
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Melissa Thye
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Daniel Mirman
- Correspondence to: Daniel Mirman Department of Psychology, 7 George Square Edinburgh EH8 9JZ, UK E-mail:
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14
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Idesis S, Favaretto C, Metcalf NV, Griffis JC, Shulman GL, Corbetta M, Deco G. Inferring the dynamical effects of stroke lesions through whole-brain modeling. Neuroimage Clin 2022; 36:103233. [PMID: 36272340 PMCID: PMC9668672 DOI: 10.1016/j.nicl.2022.103233] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022]
Abstract
Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered. The presented model classifies behavioral impairment severity with higher accuracy than other types of information (e.g.: functional connectivity). We assessed topological measures that characterize the functional effects of damage. With the obtained results, we were able to understand how network dynamics change emerge, in a nontrivial way, after a stroke injury of the underlying complex brain system. This type of modeling, including structural disconnection information, helps to deepen our understanding of the underlying mechanisms of stroke lesions.
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Affiliation(s)
- Sebastian Idesis
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, Barcelona, Catalonia 08005, Spain,Corresponding author.
| | - Chiara Favaretto
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, Padova 35129, Italy,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, Padova 35128, Italy
| | - Nicholas V. Metcalf
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Joseph C. Griffis
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Gordon L. Shulman
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, Padova 35129, Italy,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, Padova 35128, Italy,Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,VIMM, Venetian Institute of Molecular Medicine (VIMM), Biomedical Foundation, via Orus 2, Padova 35129, Italy
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, Barcelona, Catalonia 08005, Spain,Institució Catalana de Recerca I Estudis Avançats (ICREA), Passeig Lluis Companys 23, Barcelona, Catalonia 08010, Spain
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15
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Li Y, Yu Z, Zhou X, Wu P, Chen J. Aberrant interhemispheric functional reciprocities of the default mode network and motor network in subcortical ischemic stroke patients with motor impairment: A longitudinal study. Front Neurol 2022; 13:996621. [PMID: 36267883 PMCID: PMC9577250 DOI: 10.3389/fneur.2022.996621] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/15/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose The purpose of the present study was to explore the longitudinal changes in functional homotopy in the default mode network (DMN) and motor network and its relationships with clinical characteristics in patients with stroke. Methods Resting-state functional magnetic resonance imaging was performed in stroke patients with subcortical ischemic lesions and healthy controls. The voxel-mirrored homotopic connectivity (VMHC) method was used to examine the differences in functional homotopy in patients with stroke between the two time points. Support vector machine (SVM) and correlation analyses were also applied to investigate whether the detected significant changes in VMHC were the specific feature in patients with stroke. Results The patients with stroke had significantly lower VMHC in the DMN and motor-related regions than the controls, including in the precuneus, parahippocampus, precentral gyrus, supplementary motor area, and middle frontal gyrus. Longitudinal analysis revealed that the impaired VMHC of the superior precuneus showed a significant increase at the second time point, which was no longer significantly different from the controls. Between the two time points, the changes in VMHC in the superior precuneus were significantly correlated with the changes in clinical scores. SVM analysis revealed that the VMHC of the superior precuneus could be used to correctly identify the patients with stroke from the controls with a statistically significant accuracy of 81.25% (P ≤ 0.003). Conclusions Our findings indicated that the increased VMHC in the superior precuneus could be regarded as the neuroimaging manifestation of functional recovery. The significant correlation and the discriminative power in classification results might provide novel evidence to understand the neural mechanisms responsible for brain reorganization after stroke.
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Affiliation(s)
- Yongxin Li
- School of Traditional Chinese Medicine, Formula-Pattern Research Center, Jinan University, Guangzhou, China
- *Correspondence: Yongxin Li
| | - Zeyun Yu
- Acupuncture and Tuina School/Tird Teaching Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xuan Zhou
- School of Traditional Chinese Medicine, Formula-Pattern Research Center, Jinan University, Guangzhou, China
| | - Ping Wu
- Acupuncture and Tuina School/Tird Teaching Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Ping Wu
| | - Jiaxu Chen
- School of Traditional Chinese Medicine, Formula-Pattern Research Center, Jinan University, Guangzhou, China
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16
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Zangrossi A, Silvestri E, Bisio M, Bertoldo A, De Pellegrin S, Vallesi A, Della Puppa A, D'Avella D, Denaro L, Scienza R, Mondini S, Semenza C, Corbetta M. Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients. Neuroimage Clin 2022; 36:103219. [PMID: 36209618 PMCID: PMC9668620 DOI: 10.1016/j.nicl.2022.103219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/27/2022] [Accepted: 10/01/2022] [Indexed: 11/07/2022]
Abstract
Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information.
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Affiliation(s)
- Andrea Zangrossi
- Department of Neuroscience, University of Padova, Italy,Padova Neuroscience Center (PNC), University of Padova, Italy,Corresponding author at: Padova Neuroscience Center (PNC), University of Padova, Italy.
| | - Erica Silvestri
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Information Engineering, University of Padova, Italy
| | - Marta Bisio
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Biomedical Sciences, University of Padova, Italy
| | - Alessandra Bertoldo
- Padova Neuroscience Center (PNC), University of Padova, Italy,Department of Information Engineering, University of Padova, Italy
| | | | | | - Alessandro Della Puppa
- Neurosurgery Clinical Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital and University of Florence, Florence, Italy
| | - Domenico D'Avella
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Luca Denaro
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Renato Scienza
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Italy
| | - Sara Mondini
- Department of Philosophy, Sociology, Pedagogy and Applied Psychology, University of Padova, Padova, Italy
| | - Carlo Semenza
- Padova Neuroscience Center (PNC), University of Padova, Italy
| | - Maurizio Corbetta
- Department of Neuroscience, University of Padova, Italy,Padova Neuroscience Center (PNC), University of Padova, Italy,Neurology Clinical Unit, University Hospital of Padova, Padova, Italy,Venetian Institute of Molecular Medicine, VIMM, Foundation for Advanced Biomedical Research, Padova, Italy
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17
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Schlemm E, Jensen M, Kuceyeski A, Jamison K, Ingwersen T, Mayer C, Königsberg A, Boutitie F, Ebinger M, Endres M, Fiebach JB, Fiehler J, Galinovic I, Lemmens R, Muir KW, Nighoghossian N, Pedraza S, Puig J, Simonsen CZ, Thijs V, Wouters A, Gerloff C, Thomalla G, Cheng B. Early effect of thrombolysis on structural brain network organisation after anterior‐circulation stroke in the randomized
WAKE‐UP
trial. Hum Brain Mapp 2022; 43:5053-5065. [PMID: 36102287 PMCID: PMC9582379 DOI: 10.1002/hbm.26073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Revised: 07/11/2022] [Accepted: 08/22/2022] [Indexed: 11/08/2022] Open
Abstract
The symptoms of acute ischemic stroke can be attributed to disruption of the brain network architecture. Systemic thrombolysis is an effective treatment that preserves structural connectivity in the first days after the event. Its effect on the evolution of global network organisation is, however, not well understood. We present a secondary analysis of 269 patients from the randomized WAKE‐UP trial, comparing 127 imaging‐selected patients treated with alteplase with 142 controls who received placebo. We used indirect network mapping to quantify the impact of ischemic lesions on structural brain network organisation in terms of both global parameters of segregation and integration, and local disruption of individual connections. Network damage was estimated before randomization and again 22 to 36 h after administration of either alteplase or placebo. Evolution of structural network organisation was characterised by a loss in integration and gain in segregation, and this trajectory was attenuated by the administration of alteplase. Preserved brain network organization was associated with excellent functional outcome. Furthermore, the protective effect of alteplase was spatio‐topologically nonuniform, concentrating on a subnetwork of high centrality supported in the salvageable white matter surrounding the ischemic cores. This interplay between the location of the lesion, the pathophysiology of the ischemic penumbra, and the spatial embedding of the brain network explains the observed potential of thrombolysis to attenuate topological network damage early after stroke. Our findings might, in the future, lead to new brain network‐informed imaging biomarkers and improved prognostication in ischemic stroke.
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Affiliation(s)
- Eckhard Schlemm
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Märit Jensen
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Amy Kuceyeski
- Department of Radiology Weill Cornell Medicine New York New York USA
| | - Keith Jamison
- Department of Radiology Weill Cornell Medicine New York New York USA
| | - Thies Ingwersen
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Carola Mayer
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Alina Königsberg
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Florent Boutitie
- Department of Radiology Weill Cornell Medicine New York New York USA
- Hospices Civils de Lyon, Service de Biostatistique Lyon France
- Université Lyon 1 Villeurbanne France
- CNRS, UMR 5558 Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique‐Santé Villeurbanne France
| | - Martin Ebinger
- Centrum für Schlaganfallforschung Berlin (CSB) Charité ‐ Universitätsmedizin Berlin Berlin Germany
- Klinik für Neurologie Medical Park Berlin Humboldtmühle Berlin Germany
| | - Matthias Endres
- Centrum für Schlaganfallforschung Berlin (CSB) Charité ‐ Universitätsmedizin Berlin Berlin Germany
- Klinik und Hochschulambulanz für Neurologie Charité‐Universitätsmedizin Berlin Berlin Germany
- German Centre for Neurodegenerative Diseases (DZNE) Berlin Germany
- German Centre for Cardiovascular Research (DZHK) Berlin Germany
- ExcellenceCluster NeuroCure Berlin Germany
| | - Jochen B. Fiebach
- Centrum für Schlaganfallforschung Berlin (CSB) Charité ‐ Universitätsmedizin Berlin Berlin Germany
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Ivana Galinovic
- Centrum für Schlaganfallforschung Berlin (CSB) Charité ‐ Universitätsmedizin Berlin Berlin Germany
| | - Robin Lemmens
- Department of Neurology University Hospitals Leuven Leuven Belgium
- Department of Neurosciences Division of Experimental Neurology KU Leuven—University of Leuven Leuven Belgium
- VIB, Centre for Brain & Disease Research Laboratory of Neurobiology Leuven Belgium
| | - Keith W. Muir
- Institute of Neuroscience & Psychology University of Glasgow Glasgow UK
| | - Norbert Nighoghossian
- Department of Stroke Medicine, Université Claude Bernard Lyon 1 CREATIS CNRS UMR 5220‐INSERM U1206, INSA‐Lyon Lyon France
| | - Salvador Pedraza
- Department of Radiology, Institut de Diagnostic per la Image (IDI) Hospital Dr Josep Trueta, Institut d'Investigació Biomèdica de Girona (IDIBGI) Girona Spain
| | - Josep Puig
- Department of Radiology, Institut de Diagnostic per la Image (IDI) Hospital Dr Josep Trueta, Institut d'Investigació Biomèdica de Girona (IDIBGI) Girona Spain
| | | | - Vincent Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health University of Melbourne Heidelberg Victoria Australia
- Department of Neurology Austin Health Heidelberg Victoria Australia
| | - Anke Wouters
- Department of Neurology University Hospitals Leuven Leuven Belgium
- Department of Neurosciences Division of Experimental Neurology KU Leuven—University of Leuven Leuven Belgium
- VIB, Centre for Brain & Disease Research Laboratory of Neurobiology Leuven Belgium
- Department of Neurology Amsterdam UMC University of Amsterdam Amsterdam Netherlands
| | - Christian Gerloff
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Götz Thomalla
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
| | - Bastian Cheng
- Klinik und Poliklinik für Neurologie, Kopf‐ und Neurozentrum University Medical Centre Hamburg‐Eppendorf Hamburg Germany
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18
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Sperber C, Griffis J, Kasties V. Indirect structural disconnection-symptom mapping. Brain Struct Funct 2022; 227:3129-3144. [PMID: 36048282 DOI: 10.1007/s00429-022-02559-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/24/2022] [Indexed: 01/01/2023]
Abstract
In vivo tracking of white matter fibres catalysed a modern perspective on the pivotal role of brain connectome disruption in neuropsychological deficits. However, the examination of white matter integrity in neurological patients by diffusion-weighted magnetic resonance imaging bears conceptual limitations and is not widely applicable, as it requires imaging-compatible patients and resources beyond the capabilities of many researchers. The indirect estimation of structural disconnection offers an elegant and economical alternative. For this approach, a patient's structural lesion information and normative connectome data are combined to estimate different measures of lesion-induced structural disconnection. Using one of several toolboxes, this method is relatively easy to implement and is even available to scientists without expertise in fibre tracking analyses. Nevertheless, the anatomo-behavioural statistical mapping of structural brain disconnection requires analysis steps that are not covered by these toolboxes. In this paper, we first review the current state of indirect lesion disconnection estimation, the different existing measures, and the available software. Second, we aim to fill the remaining methodological gap in statistical disconnection-symptom mapping by providing an overview and guide to disconnection data and the statistical mapping of their relationship to behavioural measurements using either univariate or multivariate statistical modelling. To assist in the practical implementation of statistical analyses, we have included software tutorials and analysis scripts.
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Affiliation(s)
- Christoph Sperber
- University of Tubingen: Eberhard Karls Universitat Tubingen, Tubingen, Germany.
| | - Joseph Griffis
- University of Tubingen: Eberhard Karls Universitat Tubingen, Tubingen, Germany
| | - Vanessa Kasties
- Centre of Neurology, Hertie-Institute for Clinical Brain Research, University of Tubingen, Tubingen, Germany
- Child Development Center, University Childrens Hospital Zurich, University of Zurich, Zurich, Switzerland
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19
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Favaretto C, Allegra M, Deco G, Metcalf NV, Griffis JC, Shulman GL, Brovelli A, Corbetta M. Subcortical-cortical dynamical states of the human brain and their breakdown in stroke. Nat Commun 2022; 13:5069. [PMID: 36038566 PMCID: PMC9424299 DOI: 10.1038/s41467-022-32304-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 07/25/2022] [Indexed: 11/17/2022] Open
Abstract
The mechanisms controlling dynamical patterns in spontaneous brain activity are poorly understood. Here, we provide evidence that cortical dynamics in the ultra-slow frequency range (<0.01–0.1 Hz) requires intact cortical-subcortical communication. Using functional magnetic resonance imaging (fMRI) at rest, we identify Dynamic Functional States (DFSs), transient but recurrent clusters of cortical and subcortical regions synchronizing at ultra-slow frequencies. We observe that shifts in cortical clusters are temporally coincident with shifts in subcortical clusters, with cortical regions flexibly synchronizing with either limbic regions (hippocampus/amygdala), or subcortical nuclei (thalamus/basal ganglia). Focal lesions induced by stroke, especially those damaging white matter connections between basal ganglia/thalamus and cortex, provoke anomalies in the fraction times, dwell times, and transitions between DFSs, causing a bias toward abnormal network integration. Dynamical anomalies observed 2 weeks after stroke recover in time and contribute to explaining neurological impairment and long-term outcome. Favaretto et al. show that the brain rapidly alternates between transient connectivity patterns, with cortical regions flexibly synchronizing with two groups of subcortical regions, and that this dynamic is abnormal in stroke patients.
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Affiliation(s)
- Chiara Favaretto
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy.
| | - Michele Allegra
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy.,Department of Physics and Astronomy "Galileo Galilei", University of Padova, via Marzolo 8, 35131, Padova, Italy.,Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain.,Institució Catalana de Recerca I Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010, Barcelona, Catalonia, Spain
| | - Nicholas V Metcalf
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA.,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, 13005, Marseille, France
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padova, Italy. .,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, 35128, Padova, Italy. .,Department of Neurology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,Department of Radiology, Washington University School of Medicine, 660S. Euclid Ave, St. Louis, MO, 63110, USA. .,VIMM, Venetian Institute of Molecular Medicine (VIMM), Biomedical Foundation, via Orus 2, 35129, Padova, Italy.
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20
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Kolskår KK, Ulrichsen KM, Richard G, Dørum ES, de Schotten MT, Rokicki J, Monereo-Sánchez J, Engvig A, Hansen HI, Nordvik JE, Westlye LT, Alnaes D. Structural disconnectome mapping of cognitive function in poststroke patients. Brain Behav 2022; 12:e2707. [PMID: 35861657 PMCID: PMC9392540 DOI: 10.1002/brb3.2707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/19/2022] [Accepted: 06/25/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND AND PURPOSE Sequalae following stroke represents a significant challenge in current rehabilitation. The location and size of focal lesions are only moderately predictive of the diverse cognitive outcome after stroke. One explanation building on recent work on brain networks proposes that the cognitive consequences of focal lesions are caused by damages to anatomically distributed brain networks supporting cognition rather than specific lesion locations. METHODS To investigate the association between poststroke structural disconnectivity and cognitive performance, we estimated individual level whole-brain disconnectivity probability maps based on lesion maps from 102 stroke patients using normative data from healthy controls. Cognitive performance was assessed in the whole sample using Montreal Cognitive Assessment, and a more comprehensive computerized test protocol was performed on a subset (n = 82). RESULTS Multivariate analysis using Partial Least Squares on the disconnectome maps revealed that higher disconnectivity in right insular and frontal operculum, superior temporal gyrus and putamen was associated with poorer MoCA performance, indicating that lesions in regions connected with these brain regions are more likely to cause cognitive impairment. Furthermore, our results indicated that disconnectivity within these clusters was associated with poorer performance across multiple cognitive domains. CONCLUSIONS These findings demonstrate that the extent and distribution of structural disconnectivity following stroke are sensitive to cognitive deficits and may provide important clinical information predicting poststroke cognitive sequalae.
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Affiliation(s)
- Knut K Kolskår
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway.,Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Kristine M Ulrichsen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway.,Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Genevieve Richard
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Erlend S Dørum
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway.,Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Jaroslav Rokicki
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway.,Centre of Research and Education in Forensic Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Jennifer Monereo-Sánchez
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, the Netherlands
| | - Andreas Engvig
- Department of Nephrology, Oslo University Hospital, Ullevål, Norway.,Department of Medicine, Diakonhjemmet Hospital, Oslo, Norway
| | | | - Jan Egil Nordvik
- CatoSenteret Rehabilitation Center, Son, Norway.,Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway.,KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Dag Alnaes
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Bjørknes College, Oslo, Norway
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21
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Mapping correlated neurological deficits after stroke to distributed brain networks. Brain Struct Funct 2022; 227:3173-3187. [PMID: 35881254 DOI: 10.1007/s00429-022-02525-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 06/12/2022] [Indexed: 11/02/2022]
Abstract
Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases.
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22
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Rocha RP, Koçillari L, Suweis S, De Filippo De Grazia M, de Schotten MT, Zorzi M, Corbetta M. Recovery of neural dynamics criticality in personalized whole-brain models of stroke. Nat Commun 2022; 13:3683. [PMID: 35760787 PMCID: PMC9237050 DOI: 10.1038/s41467-022-30892-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/16/2022] [Indexed: 01/13/2023] Open
Abstract
The critical brain hypothesis states that biological neuronal networks, because of their structural and functional architecture, work near phase transitions for optimal response to internal and external inputs. Criticality thus provides optimal function and behavioral capabilities. We test this hypothesis by examining the influence of brain injury (strokes) on the criticality of neural dynamics estimated at the level of single participants using directly measured individual structural connectomes and whole-brain models. Lesions engender a sub-critical state that recovers over time in parallel with behavior. The improvement of criticality is associated with the re-modeling of specific white-matter connections. We show that personalized whole-brain dynamical models poised at criticality track neural dynamics, alteration post-stroke, and behavior at the level of single participants. The authors investigate the influence of brain injury (strokes) on the criticality of neural dynamics using directly measured connectomes and whole-brain models. They show that lesions engender a sub-critical state that recovers over time in parallel with behavior.
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Affiliation(s)
- Rodrigo P Rocha
- Departamento de Física, Centro de Ciências Físicas e Matemáticas, Universidade Federal de Santa Catarina, 88040-900, Florianópolis, SC, Brazil. .,Department of Physics, School of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil. .,Padova Neuroscience Center, Università di Padova, Padova, Italy.
| | - Loren Koçillari
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Laboratory of Neural Computation, Istituto Italiano di Tecnologia, 38068, Rovereto, Italy.,Dipartimento di Fisica e Astronomia, Università di Padova and INFN, via Marzolo 8, I-35131, Padova, Italy
| | - Samir Suweis
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Dipartimento di Fisica e Astronomia, Università di Padova and INFN, via Marzolo 8, I-35131, Padova, Italy
| | | | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, BCBlab, Sorbonne Universities, Paris, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Marco Zorzi
- IRCCS San Camillo Hospital, Venice, Italy.,Dipartimento di Psicologia Generale, Università di Padova, Padova, Italy
| | - Maurizio Corbetta
- Padova Neuroscience Center, Università di Padova, Padova, Italy.,Dipartimento di Neuroscienze, Università di Padova, Padova, Italy.,Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Padova, Italy
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23
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Medaglia JD, Erickson BA, Pustina D, Kelkar AS, DeMarco AT, Dickens JV, Turkeltaub PE. Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia. J Neurosci 2022; 42:4913-4926. [PMID: 35545436 PMCID: PMC9188386 DOI: 10.1523/jneurosci.1163-21.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 02/17/2022] [Accepted: 02/18/2022] [Indexed: 11/21/2022] Open
Abstract
Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.
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Affiliation(s)
- John D Medaglia
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
- Department of Neurology, Drexel University, Philadelphia, Pennsylvania 19104
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Brian A Erickson
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Dorian Pustina
- Cure Huntingdon's Disease Initiative (CHDI) Foundation, Princeton, New Jersey 08540
| | - Apoorva S Kelkar
- Department of Psychology, Drexel University, Philadelphia, Pennsylvania 19104
| | - Andrew T DeMarco
- Department of Neurology, Georgetown University, Washington, DC 20007
| | - J Vivian Dickens
- Department of Neurology, Georgetown University, Washington, DC 20007
| | - Peter E Turkeltaub
- Department of Neurology, Georgetown University, Washington, DC 20007
- MedStar National Rehabilitation Hospital, Washington, DC 20007
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24
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Averna A, Barban F, Care M, Murphy MD, Iandolo R, De Michieli L, Nudo RJ, Guggenmos DJ, Chiappalone M. LFP Analysis of Brain Injured Anesthetized Animals Undergoing Closed-Loop Intracortical Stimulation. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1441-1451. [PMID: 35604961 PMCID: PMC9216176 DOI: 10.1109/tnsre.2022.3177254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Activity dependent stimulation (ADS) is a closed loop stimulation technique whose neurophysiological effects have not been deeply investigated. Here we explored how Local field Potentials (LFP) are impacted by a focal ischemic lesion and, subsequently, by ADS treatment. Intracortical microelectrode arrays were implanted in the rostral forelimb area (RFA) and in the primary somatosensory area (S1) of anaesthetized rats. An ischemic injury was induced in the caudal forelimb area through microinjections of Endothelin-1. The lesion induced an acute depressive trend in LFP power in RFA (evaluated in 6 bands of interest: Delta (1–4Hz), Theta (4–8Hz), Alpha (8–11Hz), Beta (11–30Hz), LowGamma (30–55Hz) and HighGamma (55–80)) followed by a noticeable significant rebound in both areas. Applying ADS induced an overall decrease of power. The lesion impacted the connectivity in a frequency specific manner, resulting in widespread increase in connectivity in Delta both between and within areas. Two hours after the lesion, without stimulation, correlated activity between areas increased in Beta and Gamma. After stimulation, inter-area connectivity increased in Delta, Theta and Alpha, while considerably dropping within RFA in highGamma. By computing phase-amplitude coupling, we found that the lesion produced an incremental increase in the coupling between (Theta) Alpha phase and (lowGamma) highGamma amplitude within RFA, while S1 had a more generalized increase. Likewise, coupling between Theta phase and lowGamma/highGamma amplitudes increased between areas after lesion. ADS induced a similar increase, but greater in magnitude both within and between RFA and S1. These results have important implications on the emerging field of closed-loop adaptive stimulation promoting ADS as an innovative tool for the treatment of neurological disorders.
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25
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Pirondini E, Kinany N, Sueur CL, Griffis JC, Shulman GL, Corbetta M, Ville DVD. Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions. Neuroimage 2022; 255:119201. [PMID: 35405342 DOI: 10.1016/j.neuroimage.2022.119201] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 03/24/2022] [Accepted: 04/07/2022] [Indexed: 02/06/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis.
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Affiliation(s)
- Elvira Pirondini
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland; Department of Physical Medicine and Rehabilitation, University of Pittsburgh; Pittsburgh, PA, USA; Rehabilitation Neural Engineering Laboratories, University of Pittsburgh; Pittsburgh, PA, USA; Department of BioEngineering, University of Pittsburgh; Pittsburgh, PA, USA.
| | - Nawal Kinany
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland; Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, Institute of Bioengineerin, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland
| | - Cécile Le Sueur
- Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland
| | - Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA
| | - Maurizio Corbetta
- Department of Neurology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Bioengineering, Washington University School of Medicine, St. Louis; MO, 63110, USA; Department of Neuroscience and Padua Neuroscience Center, University of Padua; Padua, Italy; Venetian Institute of Molecular Medicine (VIMM); Padua, Italy
| | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, University of Geneva; 1211 Geneva, Switzerland; Medical Image Processing Laboratory, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL); 1202 Geneva, Switzerland.
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26
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Pan C, Li G, Sun W, Miao J, Qiu X, Lan Y, Wang Y, Wang H, Zhu Z, Zhu S. Neural Substrates of Poststroke Depression: Current Opinions and Methodology Trends. Front Neurosci 2022; 16:812410. [PMID: 35464322 PMCID: PMC9019549 DOI: 10.3389/fnins.2022.812410] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/04/2022] [Indexed: 12/21/2022] Open
Abstract
Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients’ functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.
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27
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Lin BF, Yeh SC, Kao YCJ, Lu CF, Tsai PY. Functional Remodeling Associated With Language Recovery After Repetitive Transcranial Magnetic Stimulation in Chronic Aphasic Stroke. Front Neurol 2022; 13:809843. [PMID: 35330805 PMCID: PMC8940300 DOI: 10.3389/fneur.2022.809843] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 01/24/2022] [Indexed: 11/22/2022] Open
Abstract
Background Repetitive transcranial magnetic stimulation (rTMS) has shown promising efficacy in improving the language functions in poststroke aphasia. However, randomized controlled trials were lacking to investigate the rTMS-related neuroimaging changes underlying the therapeutic effects on language improvement in chronic aphasia. Objective In this study, we aimed to evaluate the effects of low-frequency rTMS (LF-rTMS) on chronic poststroke aphasia. We hypothesized that the deactivation of the right pars triangularis could restore the balance of interhemispheric inhibition and, hence, facilitated the functional remodeling of language networks in both the hemispheres. Furthermore, the rTMS-induced functional reorganization should underpin the language recovery after rTMS. Methods A total of 33 patients (22 males; age: 58.70 ± 13.77 years) with chronic stroke in the left hemisphere and nonfluent aphasia were recruited in this randomized double-blinded study. The ratio of randomization between the rTMS and sham groups is 17:16. All the patients received real 1-Hz rTMS or sham stimulation (placebo coil delivered < 5% of magnetic output with similar audible click-on discharge) at the right posterior pars triangularis for 10 consecutive weekdays (stroke onset to the first stimulation: 10.97 ± 10.35 months). Functional connectivity of language networks measured by resting-state fMRI was calculated and correlated to the scores of the Concise Chinese Aphasia Test by using the stepwise regression analysis. Results After LF-rTMS intervention, significant improvement in language functions in terms of comprehension and expression abilities was observed compared with the sham group. The rTMS group showed a significant decrease of coupling strength between right pars triangularis and pars opercularis with a strengthened connection between right pars orbitalis and angular gyrus. Furthermore, the LF-rTMS significantly enhanced the coupling strength associated with left Wernicke area. Results of regression analysis showed that the identified functional remodeling involving both the hemispheres could support and predict the language recovery after LF-rTMS treatment. Conclusion We reported the therapeutic effects of LF-rTMS and corresponding functional remodeling in chronic poststroke aphasia. Our results provided neuroimage evidence reflecting the rebalance of interhemispheric inhibition induced by LF-rTMS, which could facilitate future research in the refinement of rTMS protocol to optimize the neuromodulation efficacy and benefit the clinical management of patients with stroke.
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Affiliation(s)
- Bing-Fong Lin
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Ching Yeh
- Department of Computer Science and Information Engineering, National Central University, Taoyuan, Taiwan
| | - Yu-Chieh Jill Kao
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Feng Lu
- Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Biophotonics, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Po-Yi Tsai
- Department of Physical Medicine and Rehabilitation, Taipei Veterans General Hospital, Taipei, Taiwan.,School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
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28
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Adezati E, Thye M, Edmondson-Stait AJ, Szaflarski JP, Mirman D. Lesion correlates of auditory sentence comprehension deficits in post-stroke aphasia. NEUROIMAGE. REPORTS 2022; 2:None. [PMID: 35243477 PMCID: PMC8843825 DOI: 10.1016/j.ynirp.2021.100076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 12/27/2021] [Accepted: 12/28/2021] [Indexed: 11/19/2022]
Abstract
Auditory sentence comprehension requires coordination of multiple levels of processing: auditory-phonological perception, lexical-semantic comprehension, syntactic parsing and discourse construction, as well as executive functions such as verbal working memory (WM) and cognitive control. This study examined the lesion correlates of sentence comprehension deficits in post-stroke aphasia, building on prior work on this topic by using a different and clinically-relevant measure of sentence comprehension (the Token Test) and multivariate (SCCAN) and connectome-based lesion-symptom mapping methods. The key findings were that lesions in the posterior superior temporal lobe and inferior frontal gyrus (pars triangularis) were associated with sentence comprehension deficits, which was observed in both mass univariate and multivariate lesion-symptom mapping. Graph theoretic measures of connectome disruption were not statistically significantly associated with sentence comprehension deficits after accounting for overall lesion size.
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Affiliation(s)
- Erica Adezati
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Melissa Thye
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | | | - Jerzy P. Szaflarski
- Department of Neurology and the University of Alabama at Birmingham Epilepsy Center, University of Alabama at Birmingham Heersink School of Medicine, Birmingham, AL, USA
| | - Daniel Mirman
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Corresponding author.
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29
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Keator LM, Yourganov G, Basilakos A, Hillis AE, Hickok G, Bonilha L, Rorden C, Fridriksson J. Independent contributions of structural and functional connectivity: Evidence from a stroke model. Netw Neurosci 2022; 5:911-928. [PMID: 35024536 PMCID: PMC8746188 DOI: 10.1162/netn_a_00207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 08/12/2021] [Indexed: 11/08/2022] Open
Abstract
Altered functional connectivity is related to severity of language impairment in poststroke aphasia. However, it is not clear whether this finding specifically reflects loss of functional coherence, or more generally, is related to decreased structural connectivity due to cortical necrosis. The aim of the current study was to investigate this issue by factoring out structural connectivity from functional connectivity measures and then relating the residual data to language performance poststroke. Ninety-seven participants with a history of stroke were assessed using language impairment measures (Auditory Verbal Comprehension and Spontaneous Speech scores from the Western Aphasia Battery–Revised) and MRI (structural, diffusion tensor imaging, and resting-state functional connectivity). We analyzed the association between functional connectivity and language and controlled for multiple potential neuroanatomical confounders, namely structural connectivity. We identified functional connections within the left hemisphere ventral stream where decreased functional connectivity, independent of structural connectivity, was associated with speech comprehension impairment. These connections exist in frontotemporal and temporoparietal regions. Our results suggest poor speech comprehension in aphasia is at least partially caused by loss of cortical synchrony in a left hemisphere ventral stream network and is not only reflective of localized necrosis or structural connectivity.
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Affiliation(s)
- Lynsey M Keator
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC, USA
| | - Grigori Yourganov
- Department of Psychology, 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, Department of Language Science, University of California, Irvine, CA, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Christopher 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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30
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Meier EL. The role of disrupted functional connectivity in aphasia. HANDBOOK OF CLINICAL NEUROLOGY 2022; 185:99-119. [PMID: 35078613 DOI: 10.1016/b978-0-12-823384-9.00005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Language is one of the most complex and specialized higher cognitive processes. Brain damage to the distributed, primarily left-lateralized language network can result in aphasia, a neurologic disorder characterized by receptive and/or expressive deficits in spoken and/or written language. Most often, aphasia is the consequence of stroke-termed poststroke aphasia (PSA)-yet, aphasia can also manifest due to neurodegenerative disease, specifically, a disorder called primary progressive aphasia (PPA). In recent years, functional connectivity neuroimaging studies have provided emerging evidence supporting theories regarding the relationships between language impairments, structural brain damage, and functional network properties in these two disorders. This chapter reviews the current evidence for the "network phenotype of stroke injury" hypothesis (Siegel et al., 2016) as it pertains to PSA and the "network degeneration hypothesis" (Seeley et al., 2009) as it pertains to PPA. Methodologic considerations for functional connectivity studies, limitations of the current functional connectivity literature in aphasia, and future directions are also discussed.
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Affiliation(s)
- Erin L Meier
- Department of Communication Sciences and Disorders, Northeastern University, Boston, MA, United States.
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Cassidy JM, Mark JI, Cramer SC. Functional connectivity drives stroke recovery: shifting the paradigm from correlation to causation. Brain 2021; 145:1211-1228. [PMID: 34932786 DOI: 10.1093/brain/awab469] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/20/2021] [Accepted: 11/26/2021] [Indexed: 11/14/2022] Open
Abstract
Stroke is a leading cause of disability, with deficits encompassing multiple functional domains. The heterogeneity underlying stroke poses significant challenges in the prediction of post-stroke recovery, prompting the development of neuroimaging-based biomarkers. Structural neuroimaging measurements, particularly those reflecting corticospinal tract injury, are well-documented in the literature as potential biomarker candidates of post-stroke motor recovery. Consistent with the view of stroke as a 'circuitopathy', functional neuroimaging measures probing functional connectivity may also prove informative in post-stroke recovery. An important step in the development of biomarkers based on functional neural network connectivity is the establishment of causality between connectivity and post-stroke recovery. Current evidence predominantly involves statistical correlations between connectivity measures and post-stroke behavioral status, either cross-sectionally or serially over time. However, the advancement of functional connectivity application in stroke depends on devising experiments that infer causality. In 1965, Sir Austin Bradford Hill introduced nine viewpoints to consider when determining the causality of an association: [1] Strength, [2] Consistency [3] Specificity, [4] Temporality, [5] Biological gradient, [6] Plausibility, [7] Coherence, [8] Experiment, and [9] Analogy. Collectively referred to as the Bradford Hill Criteria, these points have been widely adopted in epidemiology. In this review, we assert the value of implementing Bradford Hill's framework to stroke rehabilitation and neuroimaging. We focus on the role of neural network connectivity measurements acquired from task-oriented and resting-state functional magnetic resonance imaging, electroencephalography, magnetoencephalography, and functional near-infrared spectroscopy in describing and predicting post-stroke behavioral status and recovery. We also identify research opportunities within each Bradford Hill tenet to shift the experimental paradigm from correlation to causation.
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Affiliation(s)
- Jessica M Cassidy
- Department of Allied Health Sciences, Division of Physical Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Jasper I Mark
- Department of Allied Health Sciences, Division of Physical Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Steven C Cramer
- Department of Neurology, University of California, Los Angeles; and California Rehabilitation Institute, Los Angeles, CA USA
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Adhikari MH, Griffis J, Siegel JS, Thiebaut de Schotten M, Deco G, Instabato A, Gilson M, Corbetta M. Effective connectivity extracts clinically relevant prognostic information from resting state activity in stroke. Brain Commun 2021; 3:fcab233. [PMID: 34729479 PMCID: PMC8557690 DOI: 10.1093/braincomms/fcab233] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 06/11/2021] [Accepted: 06/25/2021] [Indexed: 11/16/2022] Open
Abstract
Recent resting-state functional MRI studies in stroke patients have identified two robust biomarkers of acute brain dysfunction: a reduction of inter-hemispheric functional connectivity between homotopic regions of the same network, and an abnormal increase of ipsi-lesional functional connectivity between task-negative and task-positive resting-state networks. Whole-brain computational modelling studies, at the individual subject level, using undirected effective connectivity derived from empirically measured functional connectivity, have shown a reduction of measures of integration and segregation in stroke as compared to healthy brains. Here we employ a novel method, first, to infer whole-brain directional effective connectivity from zero-lagged and lagged covariance matrices, then, to compare it to empirically measured functional connectivity for predicting stroke versus healthy status, and patient performance (zero, one, multiple deficits) across neuropsychological tests. We also investigated the accuracy of functional connectivity versus model effective connectivity in predicting the long-term outcome from acute measures. Both functional and effective connectivity predicted healthy from stroke individuals significantly better than the chance-level; however, accuracy for the effective connectivity was significantly higher than for functional connectivity at 1- to 2-week, 3-month and 1-year post-stroke. Predictive functional connections mainly included those reported in previous studies (within-network inter-hemispheric and between task-positive and -negative networks intra-hemispherically). Predictive effective connections included additional between-network links. Effective connectivity was a better predictor than functional connectivity of the number of behavioural domains in which patients suffered deficits, both at 2-week and 1-year post-onset of stroke. Interestingly, patient deficits at 1-year time-point were better predicted by effective connectivity values at 2 weeks rather than at 1-year time-point. Our results thus demonstrate that the second-order statistics of functional MRI resting-state activity at an early stage of stroke, derived from a whole-brain effective connectivity, estimated in a model fitted to reproduce the propagation of neuronal activity, has pertinent information for clinical prognosis.
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Affiliation(s)
- Mohit H Adhikari
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, University of Pompeu Fabra, Barcelona 08018, Spain.,Bio-imaging Lab, Department of Biomedical Sciences, University of Antwerp, Anwerp 2610, Belgium
| | - Joseph Griffis
- Department of Neurology, Radiology and Neuroscience, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63108, USA
| | - Joshua S Siegel
- Department of Neurology, Radiology and Neuroscience, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63108, USA
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Quai Saint Bernard 75005, Paris, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, 146 Rue Léo Saignat, 33000, Bordeaux, France
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, University of Pompeu Fabra, Barcelona 08018, Spain.,Institucio Catalana de la Recerca I Estudis Avancats (ICREA), University of Pompeu Fabra, Barcelona 08010, Spain
| | - Andrea Instabato
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, University of Pompeu Fabra, Barcelona 08018, Spain
| | - Matthieu Gilson
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, University of Pompeu Fabra, Barcelona 08018, Spain.,Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, 52425, Jülich, Germany
| | - Maurizio Corbetta
- Department of Neurology, Radiology and Neuroscience, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63108, USA.,Department of Neuroscience, Padova Neuroscience Center (PNC), University of Padova, Via Giuseppe Orus, 2, 35131 Padova PD, Italy.,Venetian Institute of Molecular Medicine (VIMM), Fondazione Biomedica, Via Orus 2, 35129, Padova, Italy
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33
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Hall SA, Bell RP, Davis SW, Towe SL, Ikner TP, Meade CS. Human immunodeficiency virus-related decreases in corpus callosal integrity and corresponding increases in functional connectivity. Hum Brain Mapp 2021; 42:4958-4972. [PMID: 34382273 PMCID: PMC8449114 DOI: 10.1002/hbm.25592] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/25/2021] [Accepted: 07/06/2021] [Indexed: 12/15/2022] Open
Abstract
People living with human immunodeficiency virus (PLWH) often have neurocognitive impairment. However, findings on HIV-related differences in brain network function underlying these impairments are inconsistent. One principle frequently absent from these reports is that brain function is largely emergent from brain structure. PLWH commonly have degraded white matter; we hypothesized that functional communities connected by degraded white matter tracts would show abnormal functional connectivity. We measured white matter integrity in 69 PLWH and 67 controls using fractional anisotropy (FA) in 24 intracerebral white matter tracts. Then, among tracts with degraded FA, we identified gray matter regions connected to these tracts and measured their functional connectivity during rest. Finally, we identified cognitive impairment related to these structural and functional connectivity systems. We found HIV-related decreased FA in the corpus callosum body (CCb), which coordinates activity between the left and right hemispheres, and corresponding increases in functional connectivity. Finally, we found that individuals with impaired cognitive functioning have lower CCb FA and higher CCb functional connectivity. This result clarifies the functional relevance of the corpus callosum in HIV and provides a framework in which abnormal brain function can be understood in the context of abnormal brain structure, which may both contribute to cognitive impairment.
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Affiliation(s)
- Shana A. Hall
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Ryan P. Bell
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Simon W. Davis
- Department of NeurologyDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Sheri L. Towe
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Taylor P. Ikner
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
| | - Christina S. Meade
- Department of Psychiatry and Behavioral SciencesDuke University School of MedicineDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
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34
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Olafson ER, Jamison KW, Sweeney EM, Liu H, Wang D, Bruss JE, Boes AD, Kuceyeski A. Functional connectome reorganization relates to post-stroke motor recovery and structural and functional disconnection. Neuroimage 2021; 245:118642. [PMID: 34637901 PMCID: PMC8805675 DOI: 10.1016/j.neuroimage.2021.118642] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/15/2021] [Accepted: 10/08/2021] [Indexed: 11/28/2022] Open
Abstract
Motor recovery following ischemic stroke is contingent on the ability of surviving brain networks to compensate for damaged tissue. In rodent models, sensory and motor cortical representations have been shown to remap onto intact tissue around the lesion site, but remapping to more distal sites (e.g. in the contralesional hemisphere) has also been observed. Resting state functional connectivity (FC) analysis has been employed to study compensatory network adaptations in humans, but mechanisms and time course of motor recovery are not well understood. Here, we examine longitudinal FC in 23 first-episode ischemic pontine stroke patients and utilize a graph matching approach to identify patterns of functional connectivity reorganization during recovery. We quantified functional reorganization between several intervals ranging from 1 week to 6 months following stroke, and demonstrated that the areas that undergo functional reorganization most frequently are in cerebellar/subcortical networks. Brain regions with more structural and functional connectome disruption due to the stroke also had more remapping over time. Finally, we show that functional reorganization is correlated with the extent of motor recovery in the early to late subacute phases, and furthermore, individuals with greater baseline motor impairment demonstrate more extensive early subacute functional reorganization (from one to two weeks post-stroke) and this reorganization correlates with better motor recovery at 6 months. Taken together, these results suggest that our graph matching approach can quantify recovery-relevant, whole-brain functional connectivity network reorganization after stroke.
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Affiliation(s)
- Emily R Olafson
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA.
| | - Keith W Jamison
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Elizabeth M Sweeney
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Hesheng Liu
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Danhong Wang
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Joel E Bruss
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Aaron D Boes
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medical College, New York, NY 10021, USA; Department of Population Health Sciences, Weill Cornell Medical College, New York, NY 10021, USA; Department of Radiology, Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, University of Iowa, Iowa, IA 52242, USA
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35
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Allegra M, Favaretto C, Metcalf N, Corbetta M, Brovelli A. Stroke-related alterations in inter-areal communication. NEUROIMAGE-CLINICAL 2021; 32:102812. [PMID: 34544032 PMCID: PMC8453222 DOI: 10.1016/j.nicl.2021.102812] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 08/02/2021] [Accepted: 08/29/2021] [Indexed: 01/03/2023]
Abstract
We used covariance-based Granger Causality on resting-state fMRI of stroke patients. Stroke determines an overall decrease of homotopic Granger causality (GC) Stroke determines a decrease of GC from and within the lesioned hemisphere. Stroke causes imbalances in GC between the lesioned and the healthy hemisphere. GC anomalies correlate with impaired performance in several behavioral domains.
Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned.
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Affiliation(s)
- Michele Allegra
- Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, Marseille 13005, France.
| | - Chiara Favaretto
- Department of Neuroscience, Neurological Clinic, University of Padua, Padua, Italy; Padova Neuroscience Center, University of Padua, Padua, Italy
| | - Nicholas Metcalf
- Department of Neurology, Radiology, and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
| | - Maurizio Corbetta
- Department of Neuroscience, Neurological Clinic, University of Padua, Padua, Italy; Padova Neuroscience Center, University of Padua, Padua, Italy; Department of Neurology, Radiology, and Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone UMR 7289, Aix Marseille Université, CNRS, Marseille 13005, France.
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36
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Li M, Song L, Zhang Y, Han Z. White matter network of oral word reading identified by network-based lesion-symptom mapping. iScience 2021; 24:102862. [PMID: 34386727 PMCID: PMC8346667 DOI: 10.1016/j.isci.2021.102862] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 04/29/2021] [Accepted: 07/13/2021] [Indexed: 11/19/2022] Open
Abstract
Oral word reading is supported by a neural subnetwork that includes gray matter regions and white matter tracts connected by the regions. Traditional methods typically determine the reading-relevant focal gray matter regions or white matter tracts rather than the reading-relevant global subnetwork. The present study developed a network-based lesion-symptom mapping (NLSM) method to identify the reading-relevant global white matter subnetwork in 84 brain-damaged patients. The global subnetwork was selected among all possible subnetworks because its global efficiency exhibited the best explanatory power for patients' reading scores. This reading subnetwork was left lateralized and included 7 gray matter regions and 15 white matter tracts. Moreover, the reading subnetwork had additional explanatory power for the patients' reading performance after eliminating the effects of reading-related local regions and tracts. These findings refine the reading neuroanatomical architecture and indicate that the NLSM can be a better method for revealing behavior-specific subnetworks.
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Affiliation(s)
- Mingyang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Luping Song
- Shenzhen University General Hospital, Department of Rehabilitation Medicine, Shenzhen 518055, China
| | - Yumei Zhang
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zaizhu Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Corresponding author
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37
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Cognitive impairment after focal brain lesions is better predicted by damage to structural than functional network hubs. Proc Natl Acad Sci U S A 2021; 118:2018784118. [PMID: 33941692 DOI: 10.1073/pnas.2018784118] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Hubs are highly connected brain regions important for coordinating processing in brain networks. It is unclear, however, which measures of network "hubness" are most useful in identifying brain regions critical to human cognition. We tested how closely two measures of hubness-edge density and participation coefficient, derived from white and gray matter, respectively-were associated with general cognitive impairment after brain damage in two large cohorts of patients with focal brain lesions (N = 402 and 102, respectively) using cognitive tests spanning multiple cognitive domains. Lesions disrupting white matter regions with high edge density were associated with cognitive impairment, whereas lesions damaging gray matter regions with high participation coefficient had a weaker, less consistent association with cognitive outcomes. Similar results were observed with six other gray matter hubness measures. This suggests that damage to densely connected white matter regions is more cognitively impairing than similar damage to gray matter hubs, helping to explain interindividual differences in cognitive outcomes after brain damage.
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38
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Griffis JC, Metcalf NV, Corbetta M, Shulman GL. Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions. Neuroimage Clin 2021; 30:102639. [PMID: 33813262 PMCID: PMC8053805 DOI: 10.1016/j.nicl.2021.102639] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 12/19/2022]
Abstract
Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions.
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Affiliation(s)
- Joseph C Griffis
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nicholas V Metcalf
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Maurizio Corbetta
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Bioengineering, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neuroscience, University of Padua, Padua, Italy; Padua Neuroscience Center, Padua, Italy
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
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Zorzi G, Thiebaut de Schotten M, Manara R, Bussè C, Corbetta M, Cagnin A. White matter abnormalities of right hemisphere attention networks contribute to visual hallucinations in dementia with Lewy bodies. Cortex 2021; 139:86-98. [PMID: 33848693 DOI: 10.1016/j.cortex.2021.03.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 01/16/2021] [Accepted: 03/04/2021] [Indexed: 12/28/2022]
Abstract
OBJECTIVE Functional alterations of the visual attention networks in a setting of impaired visual information processing have a role in the genesis of visual hallucinations (VH) in dementia with Lewy bodies (DLB). This multimodal MRI study aims at exploring structural and functional basis of VH. METHODS 23 DLB patients (10 with and 13 without VH) and 13 healthy controls were studied. They underwent MRI with T1-w sequences to measure cortical thickness, DTI for whole-brain and single tract microstructural properties and rs-fMRI of the default mode, dorsal and ventral attention, and visual networks. RESULTS In DLB with VH, whole-brain DTI revealed a lower fractional anisotropy and a greater mean diffusivity in the right frontal and temporo-parietal white matter tracts. Tracts dissection showed lower fractional anisotropy in the right inferior and superior (ventral part) longitudinal fasciculi (ILF and SLF) (p < .05, corrected), and greater mean diffusivity (p < .05). The extent of white matter microstructural alterations involving the right ILF and SLF correlated with the severity of VH (r = .55, p < .01; r = .42, p < .05, respectively), and with performance in the visual attention task (r = -.56 and r = -.61; p < .01, respectively). Cortical thickness in the projection areas of the right SLF was significantly reduced (p < .05). Patients with VH also showed an altered functional connectivity in the ventral attention network, connected by the ventral portion of the SLF (p < .05). CONCLUSIONS Our findings suggest that a combination of microstructural and functional alterations involving the attention networks in the right hemisphere may be important in the genesis of VH.
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Affiliation(s)
- Giovanni Zorzi
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy.
| | - Michel Thiebaut de Schotten
- Padova Neuroscience Center, University of Padova, Padova, Italy; Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Renzo Manara
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Cinzia Bussè
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Neurology, Radiology, Neuroscience, Washington University School of Medicine, St.Louis, MO, USA
| | - Annachiara Cagnin
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
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Wodeyar A, Cassidy JM, Cramer SC, Srinivasan R. Damage to the structural connectome reflected in resting-state fMRI functional connectivity. Netw Neurosci 2021; 4:1197-1218. [PMID: 33409436 PMCID: PMC7781612 DOI: 10.1162/netn_a_00160] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 07/21/2020] [Indexed: 11/04/2022] Open
Abstract
The relationship between structural and functional connectivity has been mostly examined in intact brains. Fewer studies have examined how differences in structure as a result of injury alters function. In this study we analyzed the relationship of structure to function across patients with stroke among whom infarcts caused heterogenous structural damage. We estimated relationships between distinct brain regions of interest (ROIs) from functional MRI in two pipelines. In one analysis pipeline, we measured functional connectivity by using correlation and partial correlation between 114 cortical ROIs. We found fMRI-BOLD partial correlation was altered at more edges as a function of the structural connectome (SC) damage, relative to the correlation. In a second analysis pipeline, we limited our analysis to fMRI correlations between pairs of voxels for which we possess SC information. We found that voxel-level functional connectivity showed the effect of structural damage that we could not see when examining correlations between ROIs. Further, the effects of structural damage on functional connectivity are consistent with a model of functional connectivity, diffusion, which expects functional connectivity to result from activity spreading over multiple edge anatomical paths.
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Affiliation(s)
- Anirudh Wodeyar
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Jessica M Cassidy
- Department of Allied Health Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Steven C Cramer
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
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Birle C, Slavoaca D, Balea M, Livint Popa L, Muresanu I, Stefanescu E, Vacaras V, Dina C, Strilciuc S, Popescu BO, Muresanu DF. Cognitive function: holarchy or holacracy? Neurol Sci 2020; 42:89-99. [PMID: 33070201 DOI: 10.1007/s10072-020-04737-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 09/17/2020] [Indexed: 12/24/2022]
Abstract
Cognition is the most complex function of the brain. When exploring the inner workings of cognitive processes, it is crucial to understand the complexity of the brain's dynamics. This paper aims to describe the integrated framework of the cognitive function, seen as the result of organization and interactions between several systems and subsystems. We briefly describe several organizational concepts, spanning from the reductionist hierarchical approach, up to the more dynamic theory of open complex systems. The homeostatic regulation of the mechanisms responsible for cognitive processes is showcased as a dynamic interplay between several anticorrelated mechanisms, which can be found at every level of the brain's organization, from molecular and cellular level to large-scale networks (e.g., excitation-inhibition, long-term plasticity-long-term depression, synchronization-desynchronization, segregation-integration, order-chaos). We support the hypothesis that cognitive function is the consequence of multiple network interactions, integrating intricate relationships between several systems, in addition to neural circuits.
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Affiliation(s)
- Codruta Birle
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Dana Slavoaca
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania. .,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania.
| | - Maria Balea
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Livia Livint Popa
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Ioana Muresanu
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Emanuel Stefanescu
- "RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Vitalie Vacaras
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Constantin Dina
- Department of Clinical Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Stefan Strilciuc
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
| | - Bogdan Ovidiu Popescu
- Department of Radiology, Faculty of Medicine, "Ovidius" University, Constanta, Romania
| | - Dafin F Muresanu
- Department of Neurosciences, "Iuliu Hatieganu" University of Medicine and Pharmacy, No. 37 Mircea Eliade Street, 400486, Cluj-Napoca, Romania.,"RoNeuro" Institute for Neurological Research and Diagnostic, Cluj-Napoca, Romania
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42
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Kim D, Livne T, Metcalf NV, Corbetta M, Shulman GL. Spontaneously emerging patterns in human visual cortex and their functional connectivity are linked to the patterns evoked by visual stimuli. J Neurophysiol 2020; 124:1343-1363. [PMID: 32965156 DOI: 10.1152/jn.00630.2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli. We compared in human visual cortex multivertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g., phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g., extrastriate body area for bodies), measured multivertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multivertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, positive and negative, was significantly greater for the preferred stimulus category of an ROI. The relationship between spontaneous and stimulus-evoked multivertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting multivertex patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and fluctuations of the pattern for a category (e.g., body) within its preferred ROIs were largely uncorrelated with fluctuations of the pattern for a disparate category (e.g., scene) within its preferred ROIs. These results support the proposal that spontaneous multivertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity.NEW & NOTEWORTHY Spontaneous brain activity was once thought to reflect only noise, but evidence of strong spatiotemporal regularities has motivated a search for functional explanations. Here we show that the spatial pattern of spontaneous activity in human high-level and early visual cortex is related to the spatial patterns evoked by stimuli. Moreover, these patterns partly govern spontaneous spatiotemporal interactions between regions, so-called functional connectivity. These results support the hypothesis that spontaneous activity serves a representational function.
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Affiliation(s)
- DoHyun Kim
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri
| | - Tomer Livne
- Department of Neurobiology, Weizmann Institution of Science, Rehovot, Israel.,Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
| | - Nicholas V Metcalf
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri
| | - Maurizio Corbetta
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.,Department of Radiology Washington University School of Medicine, St. Louis, Missouri.,Department of Anatomy & Neurobiology, Washington University School of Medicine, St. Louis, Missouri.,Department of Neuroscience, University of Padova, Padova, Italy.,Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.,Venetian Institute of Molecular Medicine (VIMM), Padova, Italy
| | - Gordon L Shulman
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri.,Department of Radiology Washington University School of Medicine, St. Louis, Missouri
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