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Symptom-Dependent Changes in MEG-Derived Neuroelectric Brain Activity in Traumatic Brain Injury Patients with Chronic Symptoms

Authors :
Don Krieger
Paul Shepard
Ryan Soose
Ava M. Puccio
Sue Beers
Walter Schneider
Anthony P. Kontos
Michael W. Collins
David O. Okonkwo
Source :
Medical Sciences, Vol 9, Iss 2, p 20 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Neuroelectric measures derived from human magnetoencephalographic (MEG) recordings hold promise as aides to diagnosis and treatment monitoring and targeting for chronic sequelae of traumatic brain injury (TBI). This study tests novel MEG-derived regional brain measures of tonic neuroelectric activation for long-term test-retest reliability and sensitivity to symptoms. Resting state MEG recordings were obtained from a normative cohort, Cambridge Centre for Ageing and Neuroscience (CamCAN), baseline: n = 619; mean 16-month follow-up: n = 253) and a chronic symptomatic TBI cohort, Targeted Evaluation, Action and Monitoring of Traumatic Brain Injury (TEAM-TBI), baseline: n = 64; mean 6-month follow-up: n = 39). For the CamCAN cohort, MEG-derived neuroelectric measures showed good long-term test-retest reliability for most of the 103 automatically identified stereotypic regions. The TEAM-TBI cohort was screened for depression, somatization, and anxiety with the Brief Symptom Inventory and for insomnia with the Insomnia Severity Index. Linear classifiers constructed from the 103 regional measures from each TEAM-TBI cohort member distinguished those with and without each symptom, with p < 0.01 for each—i.e., the tonic regional neuroelectric measures of activation are sensitive to the presence/absence of these symptoms. The novel regional MEG-derived neuroelectric measures obtained and tested in this study demonstrate the necessary and sufficient properties to be clinically useful—i.e., good test-retest reliability, sensitivity to symptoms in each individual, and obtainable using automatic processing without human judgement or intervention.

Details

Language :
English
ISSN :
20763271
Volume :
9
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Medical Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.10cbf62481b947e08a470b9da2afb16a
Document Type :
article
Full Text :
https://doi.org/10.3390/medsci9020020