Ricarda Ines Schubotz

The paper introduces a naturalistic audio stimuli database with unsupervised labeling, resulting in 10 semantic categories for diverse experimental use.

The paper presents a computational model based on a modified Hopfield network to explain how prediction errors drive competition between memory updating and differentiation in recognition tasks.

The paper analyzes gaze and hand movement patterns in leader-follower interactions during a cooperative manipulation task, finding distinct decision-making strategies between roles.

This study uses graph theory to analyze task-based fMRI data from schizophrenia patients and healthy controls, finding altered network topology associated with cognitive flexibility and stability.

The paper investigates how different types of episodic prediction errors affect brain activity and memory performance using modified episodic cues and fMRI.

The paper investigates how global and local information interact in predictive processing using EEG, finding that global models better explain the data than local models.