Different slopes for different folks: alpha and delta EEG power predict subsequent video game learning rate and improvements in cognitive control tasks. Academic Article uri icon

Overview

abstract

  • We hypothesized that control processes, as measured using electrophysiological (EEG) variables, influence the rate of learning of complex tasks. Specifically, we measured alpha power, event-related spectral perturbations (ERSPs), and event-related brain potentials during early training of the Space Fortress task, and correlated these measures with subsequent learning rate and performance in transfer tasks. Once initial score was partialled out, the best predictors were frontal alpha power and alpha and delta ERSPs, but not P300. By combining these predictors, we could explain about 50% of the learning rate variance and 10%-20% of the variance in transfer to other tasks using only pretraining EEG measures. Thus, control processes, as indexed by alpha and delta EEG oscillations, can predict learning and skill improvements. The results are of potential use to optimize training regimes.

publication date

  • October 23, 2012

Research

keywords

  • Alpha Rhythm
  • Brain
  • Delta Rhythm
  • Evoked Potentials
  • Learning

Identity

Scopus Document Identifier

  • 84868211651

Digital Object Identifier (DOI)

  • 10.1111/j.1469-8986.2012.01474.x

PubMed ID

  • 23095124

Additional Document Info

volume

  • 49

issue

  • 12