Adrian Naas

This study examines how aesthetic design principles affect neurofeedback (NFB) stimulus evaluation using ERP responses, finding rapid and implicit hedonic reactions to stimuli.

This study uses graph learning to analyze resting-state MEG data and identifies frequency-specific functional connectome differences in tinnitus patients compared to controls.

This paper uses explainable AI to predict acoustic tinnitus suppression from resting state EEG data, identifying key neural features associated with the ability to suppress tinnitus.

This study investigates if alpha neurofeedback training with a low-cost EEG device improves alpha amplitudes and short-term memory, using a sham-controlled design.