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Tesfaye E, Getnet M, Anmut Bitew D, Adugna DG, Maru L. Brain functional connectivity in hyperthyroid patients: systematic review. Front Neurosci 2024; 18:1383355. [PMID: 38726033 PMCID: PMC11080614 DOI: 10.3389/fnins.2024.1383355] [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: 02/07/2024] [Accepted: 04/05/2024] [Indexed: 05/12/2024] Open
Abstract
Introduction Functional connectivity (FC) is the correlation between brain regions' activities, studied through neuroimaging techniques like fMRI. It helps researchers understand brain function, organization, and dysfunction. Hyperthyroidism, characterized by high serum levels of free thyroxin and suppressed thyroid stimulating hormone, can lead to mood disturbance, cognitive impairment, and psychiatric symptoms. Excessive thyroid hormone exposure can enhance neuronal death and decrease brain volume, affecting memory, attention, emotion, vision, and motor planning. Methods We conducted thorough searches across Google Scholar, PubMed, Hinari, and Science Direct to locate pertinent articles containing original data investigating FC measures in individuals diagnosed with hyperthyroidism. Results The systematic review identified 762 articles, excluding duplicates and non-matching titles and abstracts. Four full-text articles were included in this review. In conclusion, a strong bilateral hippocampal connection in hyperthyroid individuals suggests a possible neurobiological influence on brain networks that may affect cognitive and emotional processing. Systematic Review Registration PROSPERO, CRD42024516216.
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Affiliation(s)
- Ephrem Tesfaye
- Department of Biomedical Sciences, Madda Walabu University Goba Referral Hospital, Bale-Robe, Ethiopia
| | - Mihret Getnet
- Department of Human Physiology, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
- Department of Epidemiology and Biostatistics, Institute of Public Health, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
| | - Desalegn Anmut Bitew
- Department of Reproductive Health, Institute of Public Health, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
| | - Dagnew Getnet Adugna
- Department of Anatomy, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
| | - Lemlemu Maru
- Department of Human Physiology, School of Medicine, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
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Caeyenberghs K, Imms P, Irimia A, Monti MM, Esopenko C, de Souza NL, Dominguez D JF, Newsome MR, Dobryakova E, Cwiek A, Mullin HAC, Kim NJ, Mayer AR, Adamson MM, Bickart K, Breedlove KM, Dennis EL, Disner SG, Haswell C, Hodges CB, Hoskinson KR, Johnson PK, Königs M, Li LM, Liebel SW, Livny A, Morey RA, Muir AM, Olsen A, Razi A, Su M, Tate DF, Velez C, Wilde EA, Zielinski BA, Thompson PM, Hillary FG. ENIGMA's simple seven: Recommendations to enhance the reproducibility of resting-state fMRI in traumatic brain injury. Neuroimage Clin 2024; 42:103585. [PMID: 38531165 PMCID: PMC10982609 DOI: 10.1016/j.nicl.2024.103585] [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: 09/21/2023] [Revised: 02/22/2024] [Accepted: 02/25/2024] [Indexed: 03/28/2024]
Abstract
Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.
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Affiliation(s)
- Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Phoebe Imms
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Alfred E. Mann Department of Biomedical Engineering, Andrew & Erna Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Quantitative & Computational Biology, Dana and David Dornsife College of Arts & Sciences, University of Southern California, Los Angeles, CA, USA.
| | - Martin M Monti
- Department of Psychology, UCLA, USA; Brain Injury Research Center (BIRC), Department of Neurosurgery, UCLA, USA.
| | - Carrie Esopenko
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, NY, USA.
| | - Nicola L de Souza
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, NY, USA.
| | - Juan F Dominguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Geelong, Australia.
| | - Mary R Newsome
- Michael E. DeBakey VA Medical Center, Houston, TX, USA; H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA; TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA.
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ, USA; Rutgers New Jersey Medical School, Newark, NJ, USA.
| | - Andrew Cwiek
- Department of Psychology, Penn State University, State College, PA, USA.
| | - Hollie A C Mullin
- Department of Psychology, Penn State University, State College, PA, USA.
| | - Nicholas J Kim
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA; Alfred E. Mann Department of Biomedical Engineering, Andrew & Erna Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
| | - Andrew R Mayer
- Mind Research Network, Albuquerque, NM, USA; Departments of Neurology and Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA.
| | - Maheen M Adamson
- Women's Operational Military Exposure Network (WOMEN) & Rehabilitation Department, VA Palo Alto, Palo Alto, CA, USA; Rehabilitation Service, VA Palo Alto, Palo Alto, CA, USA; Neurosurgery, Stanford School of Medicine, Stanford, CA, USA.
| | - Kevin Bickart
- UCLA Steve Tisch BrainSPORT Program, USA; Department of Neurology, David Geffen School of Medicine at UCLA, USA.
| | - Katherine M Breedlove
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Emily L Dennis
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA; Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN, USA.
| | - Courtney Haswell
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA.
| | - Cooper B Hodges
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA; Department of Psychology, Brigham Young University, Provo, UT, USA.
| | - Kristen R Hoskinson
- Center for Biobehavioral Health, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA; Department of Pediatrics, The Ohio State University College of Medicine, OH, USA.
| | - Paula K Johnson
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; Neuroscience Center, Brigham Young University, Provo, UT, USA.
| | - Marsh Königs
- Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Emma Neuroscience Group, The Netherlands; Amsterdam Reproduction and Development, Amsterdam, The Netherlands.
| | - Lucia M Li
- C3NL, Imperial College London, United Kingdom; UK DRI Centre for Health Care and Technology, Imperial College London, United Kingdom.
| | - Spencer W Liebel
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Abigail Livny
- Division of Diagnostic Imaging, Sheba Medical Center, Tel-Hashomer, Israel; Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
| | - Rajendra A Morey
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA; VA Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham, NC, USA.
| | - Alexandra M Muir
- Department of Psychology, Brigham Young University, Provo, UT, USA.
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway; Clinic of Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway; NorHEAD - Norwegian Centre for Headache Research, Norwegian University of Science and Technology, Trondheim, Norway.
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC 3800, Australia; Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR London, United Kingdom; CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, ON, Canada.
| | - Matthew Su
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA.
| | - David F Tate
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Carmen Velez
- TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Elisabeth A Wilde
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA; TBI and Concussion Center, Department of Neurology, University of Utah, Salt Lake City, UT, USA; George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA.
| | - Brandon A Zielinski
- Departments of Pediatrics, Neurology, and Neuroscience, University of Florida, Gainesville, FL, USA; Departments of Pediatrics, Neurology, and Radiology, University of Utah, Salt Lake City, UT, USA.
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, University of Southern California, Marina del Rey, CA, USA.
| | - Frank G Hillary
- Department of Psychology, Penn State University, State College, PA, USA; Department of Neurology, Hershey Medical Center, PA, USA.
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Bouchard HC, Higgins KL, Amadon GK, Laing-Young JM, Maerlender A, Al-Momani S, Neta M, Savage CR, Schultz DH. Concussion-Related Disruptions to Hub Connectivity in the Default Mode Network Are Related to Symptoms and Cognition. J Neurotrauma 2024; 41:571-586. [PMID: 37974423 DOI: 10.1089/neu.2023.0089] [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] [Indexed: 11/19/2023] Open
Abstract
Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three time points: baseline (before beginning their athletic season), acute post-injury (approximately 48h after a diagnosed concussion), and recovery (after starting return-to-play progression, but before returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar time points to link these functional connectivity changes to clinical outcomes. Concussion resulted in increased connectivity between regions within the DMN compared with baseline and recovery, and this post-injury connectivity was more positively related to symptoms and more negatively related to visual memory performance compared with baseline and recovery. Further, concussion led to decreased connectivity between DMN hubs and visual network non-hubs relative to baseline and recovery, and this post-injury connectivity was more negatively related to somatic symptoms and more positively related to visual memory performance compared with baseline and recovery. Relationships between functional connectivity, symptoms, and cognition were not significantly different at baseline versus recovery. These results highlight a unique relationship between self-reported symptoms, visual memory performance, and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.
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Affiliation(s)
- Heather C Bouchard
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Kate L Higgins
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Athletics, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Grace K Amadon
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Julia M Laing-Young
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Arthur Maerlender
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Seima Al-Momani
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Maital Neta
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Cary R Savage
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Douglas H Schultz
- Center for Brain, Biology and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
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4
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Everson CA, Szabo A, Plyer C, Hammeke TA, Stemper BD, Budde MD. Sleep loss, caffeine, sleep aids and sedation modify brain abnormalities of mild traumatic brain injury. Exp Neurol 2024; 372:114620. [PMID: 38029810 DOI: 10.1016/j.expneurol.2023.114620] [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: 08/23/2023] [Revised: 11/06/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023]
Abstract
Little evidence exists about how mild traumatic brain injury (mTBI) is affected by commonly encountered exposures of sleep loss, sleep aids, and caffeine that might be potential therapeutic opportunities. In addition, while propofol sedation is administered in severe TBI, its potential utility in mild TBI is unclear. Each of these exposures is known to have pronounced effects on cerebral metabolism and blood flow and neurochemistry. We hypothesized that they each interact with cerebral metabolic dynamics post-injury and change the subclinical characteristics of mTBI. MTBI in rats was produced by head rotational acceleration injury that mimics the biomechanics of human mTBI. Three mTBIs spaced 48 h apart were used to increase the likelihood that vulnerabilities induced by repeated mTBI would be manifested without clinically relevant structural damage. After the third mTBI, rats were immediately sleep deprived or administered caffeine or suvorexant (an orexin antagonist and sleep aid) for the next 24 h or administered propofol for 5 h. Resting state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were performed 24 h after the third mTBI and again after 30 days to determine changes to the brain mTBI phenotype. Multi-modal analyses on brain regions of interest included measures of functional connectivity and regional homogeneity from rs-fMRI, and mean diffusivity (MD) and fractional anisotropy (FA) from DTI. Each intervention changed the mTBI profile of subclinical effects that presumably underlie healing, compensation, damage, and plasticity. Sleep loss during the acute post-injury period resulted in dramatic changes to functional connectivity. Caffeine, propofol sedation and suvorexant were especially noteworthy for differential effects on microstructure in gray and white matter regions after mTBI. The present results indicate that commonplace exposures and short-term sedation alter the subclinical manifestations of repeated mTBI and therefore likely play roles in symptomatology and vulnerability to damage by repeated mTBI.
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Affiliation(s)
- Carol A Everson
- Department of Medicine (Endocrinology and Molecular Medicine) and Cell Biology, Neurobiology & Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Aniko Szabo
- Division of Biostatistics, Institute for Health & Equity, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Cade Plyer
- Neurology Residency Program, Department of Neurology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
| | - Thomas A Hammeke
- Department of Psychiatry and Behavioral Medicine, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian D Stemper
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Biomedical Engineering, Medical College of Wisconsin, Milwaukee, WI, USA; Neuroscience Research, Zablocki Veterans Affairs Medical Center, Milwaukee, WI, USA.
| | - Mathew D Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA.
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Parsons N, Irimia A, Amgalan A, Ugon J, Morgan K, Shelyag S, Hocking A, Poudel G, Caeyenberghs K. Structural-functional connectivity bandwidth predicts processing speed in mild traumatic brain Injury: A multiplex network analysis. Neuroimage Clin 2023; 38:103428. [PMID: 37167841 PMCID: PMC10196722 DOI: 10.1016/j.nicl.2023.103428] [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: 01/10/2023] [Revised: 04/17/2023] [Accepted: 05/01/2023] [Indexed: 05/13/2023]
Abstract
An emerging body of work has revealed alterations in structural (SC) and functional (FC) brain connectivity following mild TBI (mTBI), with mixed findings. However, these studies seldom integrate complimentary neuroimaging modalities within a unified framework. Multilayer network analysis is an emerging technique to uncover how white matter organization enables functional communication. Using our novel graph metric (SC-FC Bandwidth), we quantified the information capacity of synchronous brain regions in 53 mild TBI patients (46 females; age mean = 40.2 years (y), σ = 16.7 (y), range: 18-79 (y). Diffusion MRI and resting state fMRI were administered at the acute and chronic post-injury intervals. Moreover, participants completed a cognitive task to measure processing speed (30 Seconds and Counting Task; 30-SACT). Processing speed was significantly increased at the chronic, relative to the acute post-injury intervals (p = <0.001). Nonlinear principal components of direct (t = -1.84, p = 0.06) and indirect SC-FC Bandwidth (t = 3.86, p = <0.001) predicted processing speed with a moderate effect size (R2 = 0.43, p < 0.001), while controlling for age. A subnetwork of interhemispheric edges with increased SC-FC Bandwidth was identified at the chronic, relative to the acute mTBI post-injury interval (pFDR = 0.05). Increased interhemispheric SC-FC Bandwidth of this network corresponded with improved processing speed at the chronic post-injury interval (partial r = 0.32, p = 0.02). Our findings revealed that mild TBI results in complex reorganization of brain connectivity optimized for maximum information flow, supporting improved cognitive performance as a compensatory mechanism. Moving forward, this measurement may complement clinical assessment as an objective marker of mTBI recovery.
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Affiliation(s)
- Nicholas Parsons
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia; BrainCast Neurotechnologies, Australia; School of Psychological Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia.
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Anar Amgalan
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Julien Ugon
- School of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Kerri Morgan
- School of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Sergiy Shelyag
- School of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Alex Hocking
- School of Information Technology, Faculty of Science Engineering Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Govinda Poudel
- BrainCast Neurotechnologies, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia
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Kim E, Seo HG, Seong MY, Kang MG, Kim H, Lee MY, Yoo RE, Hwang I, Choi SH, Oh BM. An exploratory study on functional connectivity after mild traumatic brain injury: Preserved global but altered local organization. Brain Behav 2022; 12:e2735. [PMID: 35993893 PMCID: PMC9480924 DOI: 10.1002/brb3.2735] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 06/26/2022] [Accepted: 07/20/2022] [Indexed: 12/18/2022] Open
Abstract
INTRODUCTION This study aimed to investigate alterations in whole-brain functional connectivity after a concussion using graph-theory analysis from global and local perspectives and explore the association between changes in the functional network properties and cognitive performance. METHODS Individuals with mild traumatic brain injury (mTBI, n = 29) within a month after injury, and age- and sex-matched healthy controls (n = 29) were included. Graph-theory measures on functional connectivity assessed using resting state functional magnetic resonance imaging data were acquired from each participant. These included betweenness centrality, strength, clustering coefficient, local efficiency, and global efficiency. Multi-domain cognitive functions were correlated with the graph-theory measures. RESULTS In comparison to the controls, the mTBI group showed preserved network characteristics at a global level. However, in the local network, we observed decreased betweenness centrality, clustering coefficient, and local efficiency in several brain areas, including the fronto-parietal attention network. Network strength at the local level showed mixed-results in different areas. The betweenness centrality of the right parahippocampus showed a significant positive correlation with the cognitive scores of the verbal learning test only in the mTBI group. CONCLUSION The intrinsic functional connectivity after mTBI is preserved globally, but is suboptimally organized locally in several areas. This possibly reflects the neurophysiological sequelae of a concussion. The present results may imply that the network property could be used as a potential indicator for clinical outcomes after mTBI.
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Affiliation(s)
- Eunkyung Kim
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea.,Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Han Gil Seo
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea.,Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Min Yong Seong
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea
| | - Min-Gu Kang
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea
| | - Heejae Kim
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea
| | - Min Yong Lee
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine and Seoul National University Hospital, Seoul, Korea
| | - Byung-Mo Oh
- Department of Rehabilitation Medicine, Seoul National University Hospital, Seoul, Korea.,Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul, Korea.,National Traffic Injury Rehabilitation Hospital, Yangpyeong, Korea
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Ly MT, Scarneo-Miller SE, Lepley AS, Coleman K, Hirschhorn R, Yeargin S, Casa DJ, Chen CM. Combining MRI and cognitive evaluation to classify concussion in university athletes. Brain Imaging Behav 2022; 16:2175-2187. [PMID: 35639240 DOI: 10.1007/s11682-022-00687-w] [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] [Accepted: 05/09/2022] [Indexed: 11/26/2022]
Abstract
Current methods of concussion assessment lack the objectivity and reliability to detect neurological injury. This multi-site study uses combinations of neuroimaging (diffusion tensor imaging and resting state functional MRI) and cognitive measures to train algorithms to detect the presence of concussion in university athletes. Athletes (29 concussed, 48 controls) completed symptom reports, brief cognitive evaluation, and MRI within 72 h of injury. Hierarchical linear regression compared groups on cognitive and neuroimaging measures while controlling for sex and data collection site. Logistic regression and support vector machine models were trained using cognitive and neuroimaging measures and evaluated for overall accuracy, sensitivity, and specificity. Concussed athletes reported greater symptoms than controls (∆R2 = 0.32, p < .001), and performed worse on tests of concentration (∆R2 = 0.07, p < .05) and delayed memory (∆R2 = 0.17, p < .001). Concussed athletes showed lower functional connectivity within the frontoparietal and primary visual networks (p < .05), but did not differ on mean diffusivity and fractional anisotropy. Of the cognitive measures, classifiers trained using delayed memory yielded the best performance with overall accuracy of 71%, though sensitivity was poor at 46%. Of the neuroimaging measures, classifiers trained using mean diffusivity yielded similar accuracy. Combining cognitive measures with mean diffusivity increased overall accuracy to 74% and sensitivity to 64%, comparable to the sensitivity of symptom report. Trained algorithms incorporating both MRI and cognitive performance variables can reliably detect common neurobiological sequelae of acute concussion. The integration of multi-modal data can serve as an objective, reliable tool in the assessment and diagnosis of concussion.
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Affiliation(s)
- Monica T Ly
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA.
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
- Department of Psychiatry, University of California San Diego, School of Medicine, San Diego, CA, USA.
| | - Samantha E Scarneo-Miller
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- Division of Athletic Training, School of Medicine, West Virginia University, Morgantown, WV, USA
| | - Adam S Lepley
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- School of Kinesiology, Exercise and Sport Science Initiative, University of Michigan, Ann Arbor, MI, USA
| | - Kelly Coleman
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
- Department of Health & Movement Sciences, Southern Connecticut State University, New Haven, CT, USA
| | - Rebecca Hirschhorn
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
- School of Kinesiology, Louisiana State University, Baton Rouge, LA, USA
| | - Susan Yeargin
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Douglas J Casa
- Department of Kinesiology, Korey Stringer Institute, University of Connecticut, Storrs, CT, USA
| | - Chi-Ming Chen
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
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Effects of Mild Traumatic Brain Injury on Resting State Brain Network Connectivity in Older Adults. Brain Imaging Behav 2022; 16:1863-1872. [PMID: 35394617 PMCID: PMC9279274 DOI: 10.1007/s11682-022-00662-5] [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] [Accepted: 03/10/2022] [Indexed: 11/02/2022]
Abstract
Older age is associated with worsened outcome after mild traumatic brain injury (mTBI) and a higher risk of developing persistent post-traumatic complaints. However, the effects of mTBI sequelae on brain connectivity at older age and their association with post-traumatic complaints remain understudied.We analyzed multi-echo resting-state functional magnetic resonance imaging data from 25 older adults with mTBI (mean age: 68 years, SD: 5 years) in the subacute phase (mean injury to scan interval: 38 days, SD: 9 days) and 20 age-matched controls. Severity of complaints (e.g. fatigue, dizziness) was assessed using self-reported questionnaires. Group independent component analysis was used to identify intrinsic connectivity networks (ICNs). The effects of group and severity of complaints on ICNs were assessed using spatial maps intensity (SMI) as a measure of within-network connectivity, and (static) functional network connectivity (FNC) as a measure of between-network connectivity.Patients indicated a higher total severity of complaints than controls. Regarding SMI measures, we observed hyperconnectivity in left-mid temporal gyrus (cognitive-language network) and hypoconnectivity in the right-fusiform gyrus (visual-cerebellar network) that were associated with group. Additionally, we found interaction effects for SMI between severity of complaints and group in the visual(-cerebellar) domain. Regarding FNC measures, no significant effects were found.In older adults, changes in cognitive-language and visual(-cerebellar) networks are related to mTBI. Additionally, group-dependent associations between connectivity within visual(-cerebellar) networks and severity of complaints might indicate post-injury (mal)adaptive mechanisms, which could partly explain post-traumatic complaints (such as dizziness and balance disorders) that are common in older adults during the subacute phase.
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Bostami B, Hillary FG, van der Horn HJ, van der Naalt J, Calhoun VD, Vergara VM. A Decentralized ComBat Algorithm and Applications to Functional Network Connectivity. Front Neurol 2022; 13:826734. [PMID: 35370895 PMCID: PMC8965063 DOI: 10.3389/fneur.2022.826734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/09/2022] [Indexed: 11/13/2022] Open
Abstract
Recent studies showed that working with neuroimage data collected from different research facilities or locations may incur additional source dependency, affecting the overall statistical power. This problem can be mitigated with data harmonization approaches. Recently, the ComBat method has become commonly adopted for various neuroimage modalities. While open neuroimaging datasets are becoming more common, a substantial amount of data is still unable to be shared for various reasons. In addition, current approaches require moving all the data to a central location, which requires additional resources and creates redundant copies of the same datasets. To address these issues, we propose a decentralized harmonization approach that does not create redundant copies of the original datasets and performs remote operations on the datasets separately without sharing any individual subject data, ensuring a certain level of privacy and reducing regulatory hurdles. We proposed a novel approach called "Decentralized ComBat" which can harmonize datasets separately without combining the datasets. We tested our model by harmonizing functional network connectivity datasets from two traumatic brain injury studies in a decentralized way. Also, we used simulations to analyze the performance and scalability of our model when the number of data collection sites increases. We compare the output with centralized ComBat and show that the proposed approach produces similar results, increasing the sensitivity of the functional network connectivity analysis and validating our approach. Simulations show that our model can be easily scaled to many more datasets based on the requirement. In sum, we believe this provides a powerful tool, further complementing open data and allowing for integrating public and private datasets.
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Affiliation(s)
- Biozid Bostami
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Frank G. Hillary
- Department of Psychology, Penn State University, State College, PA, United States
| | - Harm Jan van der Horn
- Department of Developmental Neurology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Joukje van der Naalt
- Department of Medical Sciences, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Vince D. Calhoun
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Victor M. Vergara
- Department of Computer Science, Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia Institute of Technology, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
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