Sungkean Kim

This study investigates the neural mechanisms of willed attention control using fMRI and EEG data, finding distinct activation patterns and decoding capabilities in the frontoparietal decision network.

The paper uses EEG-fMRI data to decode the temporal dynamics of affective scene processing, finding distinct neural activity patterns for pleasant and unpleasant images.

This study uses EEG and fMRI with machine learning to show that affective pictures evoke valence-specific neural representations in retinotopic visual cortex, influenced by limbic and frontal connectivity.