| Autor: |
Vahid, Amirali, Stock, Ann-Kathrin, Mückschel, Moritz, Beste, Christian |
| Zdroj: |
Neuroimage: Reports; September 2022, Vol. 2 Issue: 3 |
| Abstrakt: |
Goal-directed behavior often requires concatenating different actions to achieve a goal. The neural correlates of such multi-component behavior have extensively been investigated. However, it is still enigmatic whether it is possible to predict, using single-trial EEG data and on a single-subject level, that an individual is confronted with a situation imposing high or low demands on multi-component behavior. This study gathered data from N = 239 individuals and applied EEG-based deep learning combined with explainable artificial intelligence, temporal EEG signal decomposition, and source localization. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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