Sebastian Gluth

This study uses EEG and eye-tracking with a computational model to identify neural signatures of value-integration during decision-making under naturalistic conditions.

The paper shows humans use decision-process cues like response times and gaze to infer others' preferences during social interactions.

This study examines how episodic memory retrieval impacts the timing and dynamics of value-based decisions using EEG and drift-diffusion modeling.

This study uses 7T fMRI to examine dopaminergic nuclei in humans, finding correlations with reward prediction error and risk in SN and VTA, and a surprise signal in SN.

The paper introduces LOTO, a method to estimate trial-wise cognitive model parameters from neural data, showing it is efficient, general, and better at distinguishing true parameter variability from noise.