Predicting Gains With Visuospatial Training After Stroke Using an EEG Measure of Frontoparietal Circuit Function

Authors

Robert J. Zhou, University of California, Irvine
Hossein M. Hondori, University of California, Irvine
Maryam Khademi, University of California, Irvine
Jessica M. Cassidy, University of California, Irvine
Katherine M. Wu, University of California, Irvine
Derek Z. Yang, University of California, Irvine
Nikhita Kathuria, University of California, Irvine
Fareshte R. Erani, University of California, Irvine
Lucy Dodakian, University of California, Irvine
Alison McKenzie, Chapman UniversityFollow
Cristina V. Lopes, University of California - Irvine
Walt Scacchi, University of California, Irvine
Ramesh Srinivasan, University of California, Irvine
Steven C. Cramer, University of California, Irvine

Document Type

Article

Publication Date

7-24-2018

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 (20–30Hz) 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.

Comments

This article was originally published in Frontiers in Neurology, volume 9, in 2018. DOI: 10.3389/fneur.2018.00597

Recommended Citation

Zhou RJ, Hondori HM, Khademi M et al. Predicting gains with visuospatial training after stroke using an EEG measure of frontoparietal circuit function. Front. Neurol. 2018;9:597. doi: 10.3389/fneur.2018.00597

Peer Reviewed

1

Copyright

The authors

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This work is licensed under a Creative Commons Attribution 4.0 License.