Nicholas D. Theis

The paper examines dynamic brain network changes in early psychoses using maximum entropy models, finding temporally unstable network configurations linked to cognitive deficits.

This study uses energy landscape analysis on fMRI data to show that adolescent-onset schizophrenia exhibits altered brain state dynamics during task engagement compared to healthy controls.

The paper uses causal discovery analysis to show that statistically non-significant fMRI regions causally influence psychopathology severity and working memory performance.

The paper uses maximum entropy models to analyze brain activity patterns in adolescent-onset schizophrenia and healthy controls, finding higher energy states correlate with worse cognitive performance and psychopathology.

This study uses maximum entropy modeling to analyze resting state fMRI data and identifies diagnostically distinct energy distributions across psychiatric disorders.

This paper introduces an objective function thresholding method for brain connectomes, showing it outperforms existing methods in preserving network structure and clustering features.