David Hofmann

IBMMA improves neuroimaging analysis by handling missing data and large datasets, revealing new brain region findings overlooked by traditional methods.

This paper classifies PTSD vs. controls using MRI data from multiple sites, finding better performance when distinguishing PTSD from trauma-unexposed controls than trauma-exposed controls, and showing DVAE improves generalizability.

This study finds smaller total and subregional cerebellar volumes in PTSD compared to controls using a large dataset and advanced parcellation methods.

This paper compares four methods for harmonizing cortical thickness data across multiple sites and finds that ComBat-GAM is most effective in detecting case-control differences and age-related cortical thinning.

The paper examines how prediction error and adaptation differ across auditory cortical regions during deviance processing using fMRI and an auditory oddball paradigm.

This study examines structural covariance networks in PTSD using a large multisite dataset, finding differences in centrality measures between PTSD and control groups, and highlighting sex-based and comorbid differences.

This study examines how prediction error signaling during reinforcement learning in social anxiety disorder (SAD) is altered by social observation, finding increased DMPFC coupling to prediction errors and reduced ventral pallidum connectivity in SAD.

This study identifies hippocampal subfield volume differences in PTSD and depression across 31 cohorts, finding depression has a stronger effect than PTSD, especially in CA1, with comorbid cases showing more pronounced changes.

This study identifies reduced fractional anisotropy in the tapetum region of the corpus callosum in PTSD patients using a large multi-cohort analysis of diffusion MRI data.