Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses

Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses

Abstract Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether “classical” ERPs are truly the best reflection or even causal to observable var...

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Bibliographic Details
Main Authors: Amirali Vahid, Moritz Mückschel, Andres Neuhaus, Ann-Kathrin Stock, Christian Beste
Format: Article
Language:English
Published: Nature Publishing Group 2018-11-01
Series:Scientific Reports
Subjects:
Neurophysiological Features
Event-related Potentials (ERP)
Behavioral Performance
Sequential Floating Forward Selection (SFFS)
NoGo Trials
Online Access:https://doi.org/10.1038/s41598-018-34727-7

Internet

https://doi.org/10.1038/s41598-018-34727-7

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