Patrick K. A. Neff

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.

The paper investigates residual inhibition (RI) in tinnitus patients using EEG, finding differences in alpha and gamma band activity between responders and non-responders, suggesting trait-like oscillatory signatures in tinnitus subgroups.

This study investigates whether amplitude-modulated noise-like stimuli can increase residual inhibition in patients with noise-like tinnitus, finding no significant difference between modulated and unmodulated stimuli but better effects in a subgroup.