Jacek Rogala

This study shows that personalized EEG neurofeedback using deep neural networks improves cognitive performance in adults, with significant gains in reasoning tasks and neural connectivity.

The paper uses persistent homology to analyze visual structures in abstract paintings and maps topological features to viewer eye tracking and EEG data.

The paper applies RID-Rihaczek phase synchrony to resting-state EEG to predict multiple cognitive and performance measures with an average R2 of .60.

The paper investigates gender differences in working memory performance using brain temperature and BOLD responses, finding no gender disparity in performance but significant temperature variation and compensatory mechanisms in females.