Carles Soriano‐Mas

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.

The paper identifies convergent and selective functional zones in the insula using fMRI data, revealing a hierarchical convergence architecture across pain, appetitive, aversive, and cognitive control domains.

This study analyzes fMRI data from OCD patients and controls to identify neural activation patterns during executive control tasks, finding reduced activation in frontoparietal regions and increased default mode network activity in OCD.

The paper examines white matter volume deviations in psychiatric disorders using normative modeling, finding heterogeneous patterns with some aggregation in autism and schizophrenia.

The paper uses reinforcement learning models and fMRI to analyze cognitive flexibility differences in Gambling Disorder and Cocaine Use Disorder, finding distinct neural and behavioral patterns.

The paper examines hippocampal and amygdala subfield volumes in OCD patients and healthy controls, finding differences based on medication status.

The paper investigates neurophysiological signatures during the retrieval of real-life episodic memories using EEG and a convolutional network-based algorithm to select stimuli.

The paper identifies a common neural network underlying state, trait, and pathological anxiety using fMRI data across multiple datasets.