Joaquim Raduà

This study analyzes structural brain network changes in bipolar disorder, finding widespread connectivity disruptions linked to illness severity and medication use.

The paper introduces a scalable toolkit for 3D surface-based brain analysis, demonstrating its utility in mapping subcortical shape variations across 21 international samples.

This study investigates how structural brain alterations in schizophrenia relate to network architecture, finding hub susceptibility and shared epicenters across disease stages and disorders.

This study analyzes lifespan changes in brain activation related to cognitive control using a meta-analysis of neuroimaging studies, finding an inverted U-shaped trajectory and heterogeneous patterns across brain networks.

This paper uses neuroimaging meta-regression to examine THC's acute effects on brain activation and its relationship with CB1R gene expression.

The paper examines age-related variations in cortical thickness across different life stages using gene expression data from a large neuroimaging dataset.

This study uses resting-state functional imaging meta-analysis to find shared and distinct brain activation patterns between borderline personality disorder and post-traumatic stress disorder.

This paper introduces a method to adjust for variable brain coverage in fMRI meta-analysis, showing increased effect sizes in regions with low coverage.

The paper develops deep learning models to assess the quality of subcortical brain shape models from MRI, reducing human rater time by 46-70%.

This work uses machine learning to automate quality control of 3D brain shape models, reducing human workload by 30-70% across multiple datasets and diseases.