Ilya Kuzovkin

The paper uses EEG data from TMS-treated patients to show that changes in anterior default mode brain state dynamics predict depressive symptom improvement during treatment.

This study uses machine learning to identify spectral signatures in human brain activity that correlate with perceptual categorization of visual stimuli.

The paper introduces a method for visualizing mental state spaces to help users find effective BCI control strategies through interactive exploration.

The paper investigates the alignment between gamma band activity in the human visual cortex and feature transformations in deep convolutional neural networks (DCNNs) along the ventral visual pathway.