Frontiers in Neurology (Jul 2018)

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

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

DOI
https://doi.org/10.3389/fneur.2018.00597
Journal volume & issue
Vol. 9

Abstract

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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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