Martin Schecklmann

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.