Review paper

Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control

Volume: 3, Issue: 1
Published: Mar 9, 2020
Abstract
Efficient action control is indispensable for goal-directed behaviour. Different theories have stressed the importance of either attention or response selection sub-processes for action control. Yet, it is unclear to what extent these processes can be identified in the dynamics of neurophysiological (EEG) processes at the single-trial level and be used to predict the presence of conflicts in a given moment. Applying deep learning, which was...
Paper Details
Title
Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control
Published Date
Mar 9, 2020
Volume
3
Issue
1
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