Silvia Brem

This study analyzes fMRI data from OCD patients and controls to identify age-specific differences in brain activation during inhibitory control and error processing.

This paper introduces a Hodge-Laplacian framework to analyze higher-order topology in OCD brain networks, identifying loop-level abnormalities not detectable by conventional functional connectivity analysis.

This study predicts children's literacy from task-based fMRI by comparing task types and contrasts, finding active tasks and multisensory learning tasks yield better predictive performance.

The paper identifies distinct neurocomputational mechanisms for multisensory learning using a novel task and fMRI, showing dissociable networks for statistical learning, reinforcement learning, and outcome surprise.

This study examines age-related changes in multisensory learning using behavioral, neuroimaging, and computational methods in children, finding faster processing and stronger neural engagement in older children.

This paper analyzes fMRI neurofeedback data to identify brain regions and networks involved in feedback processing and regulation recalibration during training.

This study investigates brain dynamics during audiovisual learning of symbol-speech sound associations using fMRI and a reinforcement learning model, showing how learning and prediction errors modulate specific brain regions.

This study shows that individuals can voluntarily regulate their Visual Word Form Area (VWFA) activity using real-time fMRI neurofeedback, with lasting effects even without feedback.

The paper examines the development of visual N1 sensitivity to digits across elementary school years and finds it remains stable, contrasting with sensitivity to words or letters.

This study analyzes structural brain asymmetries in ADHD using 39 datasets, finding small effects that do not meet study-wide significance thresholds.

This study identifies white matter microstructural alterations in adult OCD patients and links them to clinical features, while finding no such abnormalities in pediatric patients.

This study uses machine learning to show that structural brain anomalies in ADHD are similar in children and adults, supporting continuity of the disorder's pathophysiology.

This study compares structural brain differences across ADHD, ASD, and OCD using MRI data from multiple cohorts, finding disorder-specific alterations in brain volume and cortical thickness.

The paper analyzes cerebral cortical asymmetry in 17,141 healthy individuals, finding widespread hemispheric and regional asymmetries, associations with sex, age, brain size, and heritability.