Christian Beste

Distilling Trial-Level EEG Variability into Participant Representations: Neurophysiologically Constrained Graph Learning in ADHD

The paper develops a neurophysiologically constrained graph learning method to extract stable participant representations from EEG data in ADHD and finds group-related structure in embeddings that capture trial-level variability.

Reward processing in children with Affective Dysregulation

The paper examines reward processing in children with affective dysregulation using ERP components, finding attenuated anticipatory reward processing and associations with AD symptoms.

Neurophysiological Dynamics of Metacontrol States: EEG Insights into Conflict Regulation

This study uses EEG and artificial neural networks to analyze how metacontrol states affect conflict regulation, finding theta band activity reflects mismatch between expected bias and task demands, while alpha and beta bands are involved in neural reset.

Neurophysiological coding of statistical and deterministic rule information

The paper investigates how statistical and rule-based learning mechanisms are represented in EEG data and identifies distinct neural correlates for each.

How non-veridical perception drives actions in healthy humans - Evidence from Synaesthesia

The paper shows that non-veridical perceptions influence actions in healthy humans, with high-order brain processes mediating this effect, challenging assumptions about perception-action interactions.