Shitong Xiang

The paper develops a digital twin brain model that simulates and manipulates functional brain networks to predict mental illness symptoms and responses to interventions.

The paper introduces Brain-DiT, a deep generative model for analyzing task-fMRI data, identifying cognitive regions and subgroups linked to psychiatric conditions like depression and alcohol abuse.

The paper identifies a genetic-dependent brain signature of resilience linked to childhood abuse and depression risk in girls, showing its predictive value for emotional disorders in adolescence and early adulthood.

The paper develops a neural signature that predicts anxious arousal during uncertain threat anticipation using fMRI and multivariate modeling.

This paper introduces DeCoP, a novel decoding method that separates reward processing into evaluation and salience components, showing improved performance over traditional methods.