Literature DB >> 29093171

Electroencephalographic connectivity measures predict learning of a motor sequencing task.

Jennifer Wu1,2, Franziska Knapp3,2, Steven C Cramer1,2,4, Ramesh Srinivasan5.   

Abstract

Individuals vary significantly with respect to rate and degree of improvement with motor practice. While the regions that underlie motor learning have been well described, neurophysiological factors underlying differences in response to motor practice are less well understood. The present study examined both resting-state and event-related EEG coherence measures of connectivity as predictors of response to motor practice on a motor sequencing task using the dominant hand. Thirty-two healthy young right-handed participants underwent resting EEG before motor practice. Response to practice was evaluated both across the single session of motor practice and 24 h later at a retention test of short-term motor learning. Behaviorally, the group demonstrated statistically significant gains both in single-session "motor improvement" and across-session "motor learning." A resting-state measure of whole brain coherence with primary motor cortex (M1) at baseline robustly predicted subsequent motor improvement (validated R2 = 0.55) and motor learning (validated R2 = 0.68) in separate partial least-squares regression models. Specifically, greater M1 coherence with left frontal-premotor cortex (PMC) at baseline was characteristic of individuals likely to demonstrate greater gains in both motor improvement and motor learning. Analysis of event-related coherence with respect to movement found the largest changes occurring in areas implicated in planning and preparation of movement, including PMC and frontal cortices. While event-related coherence provided a stronger prediction of practice-induced motor improvement (validated R2 = 0.73), it did not predict the degree of motor learning (validated R2 = 0.16). These results indicate that connectivity in the resting state is a better predictor of consolidated learning of motor skills. NEW & NOTEWORTHY Differences in response to motor training have significant societal implications across a lifetime of motor skill practice. By evaluating both resting-state and event-related measures of brain function, our findings highlight interindividual differences in brain connectivity providing unique insights into differences in response to motor training. These findings have wide-ranging implications in settings ranging from advanced professional motor training to rehabilitation after brain injury.

Entities:  

Keywords:  EEG; event-related coherence; motor learning; partial least-squares regression; prediction; resting-state connectivity

Mesh:

Year:  2017        PMID: 29093171      PMCID: PMC5867382          DOI: 10.1152/jn.00580.2017

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  46 in total

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Review 3.  Towards understanding neural network signatures of motor skill learning in Parkinson's disease and healthy aging.

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

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