Jasmin Riegel

This study uses MEG and machine learning to decode auditory and visual mental imagery, showing deep learning models can capture cross-modal neural representations even from non-task-relevant regions.

This study compares cortical speech tracking and attentional modulation between hearing aid users, cochlear implant users, and typical hearing individuals in noisy environments.

The study investigates whether visual information modulates the cortical contribution to the speech-FFR and finds no significant modulation despite improved speech-in-noise comprehension with visual input.

This study investigates how the brain processes audiovisual speech from natural videos, avatars, and degraded videos, revealing distinct neural tracking patterns in different frequency bands.

This study investigates whether musical training affects the cortical contribution to the speech-FFR and its modulation by selective attention, finding no significant differences between musicians and non-musicians.

This study examines how selective attention affects cortical speech envelope tracking in delta and theta bands and finds that musical training does not influence this process.