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Journal article
Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function
Frontiers in neurology, v 9, 597
24 Jul 2018
PMID: 30087653
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The heterogeneity of stroke prompts the need for predictors of individual treatment response to rehabilitation therapies. We previously studied healthy subjects with EEG and identified a frontoparietal circuit in which activity predicted training-related gains in visuomotor tracking. Here we asked whether activity in this same frontoparietal circuit also predicts training-related gains in visuomotor tracking in patients with chronic hemiparetic stroke. Subjects (n = 12) underwent dense-array EEG recording at rest, then received 8 sessions of visuomotor tracking training delivered via home-based telehealth methods. Subjects showed significant training-related gains in the primary behavioral endpoint, Success Rate score on a standardized test of visuomotor tracking, increasing an average of 24.2 ± 21.9% (p = 0.003). Activity in the circuit of interest, measured as coherence (20–30 Hz) between leads overlying ipsilesional frontal (motor cortex) and parietal lobe, significantly predicted training-related gains in visuomotor tracking change, measured as change in Success Rate score (r = 0.61, p = 0.037), supporting the main study hypothesis. Results were specific to the hypothesized ipsilesional motor-parietal circuit, as coherence within other circuits did not predict training-related gains. Analyses were repeated after removing the four subjects with injury to motor or parietal areas; this increased the strength of the association between activity in the circuit of interest and training-related gains. The current study found that (1) Eight sessions of training can significantly improve performance on a visuomotor task in patients with chronic stroke, (2) this improvement can be realized using home-based telehealth methods, (3) an EEG-based measure of frontoparietal circuit function predicts training-related behavioral gains arising from that circuit, as hypothesized and with specificity, and (4) incorporating measures of both neural function and neural injury improves prediction of stroke rehabilitation therapy effects.
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Details
- Title
- Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function
- Creators
- Robert J. Zhou - University of California, IrvineHossein M. Hondori - University of California, IrvineMaryam Khademi - University of California, IrvineJessica M. Cassidy - University of California, IrvineKatherine M. Wu - University of California, IrvineDerek Z. Yang - University of California, IrvineNikhita Kathuria - University of California, IrvineFareshte R. Erani - University of California, IrvineLucy Dodakian - University of California, IrvineAlison McKenzie - University of California, IrvineCristina V. Lopes - University of California, IrvineWalt Scacchi - University of California, IrvineRamesh Srinivasan - University of California, IrvineSteven C. Cramer - University of California, Irvine
- Publication Details
- Frontiers in neurology, v 9, 597
- Publisher
- Frontiers Media S.A.
- Grant note
- 13GRNT16990060 / American Heart Association K24 HD074722; UL1 TR001414; T32 AR047752-11A1 / National Institutes of Health
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychological and Brain Sciences (Psychology)
- Web of Science ID
- WOS:000439599300001
- Scopus ID
- 2-s2.0-85050641732
- Other Identifier
- 991020099629604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Clinical Neurology
- Neurosciences