Josh M. Cisler

The paper examines how childhood maltreatment affects brain structure in 3,711 individuals with MDD and PTSD, finding age- and sex-specific brain morphometric differences.

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

The paper examines thalamic volume differences in trauma-exposed individuals with PTSD, MDD, and controls, finding specific volume reductions and associations with symptom severity and childhood trauma.

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 study uses real-time fMRI neurofeedback with whole brain classifiers to enhance exposure therapy for PTSD in female IPV survivors, showing improved engagement with trauma memories through brain-state regulation.

The paper introduces a model of latent-state learning that combines Rescorla-Wagner and Bayesian rules to explain various learning phenomena and demonstrates its effectiveness in simulations.