Xiao Chen

This study examines intracranial EEG during rumination, finding increased slow frequency power in the precuneus and decreased high gamma power in the hippocampus, linked to reflection tendency.

This study evaluates harmonization strategies for multisite resting-state fMRI data, finding that SMA outperforms other methods in reducing site effects and improving identifiability and replicability.

This study investigates brain activation during think-aloud fMRI, finding that self-generated thoughts engage widespread brain regions and are represented across multiple neural scales.

This paper develops a deep learning classifier for Alzheimer's disease using brain MRI data from 85,721 scans, achieving high accuracy across multiple independent datasets.

This study compares the predictive power of brain structural and functional metrics for age, sex, and schizophrenia treatment outcomes using variance partitioning and permutation tests.

This study investigates the subsystem mechanism of the default mode network (DMN) underlying rumination using neuroimaging data from healthy participants.

The paper analyzes resting-state fMRI data from 1,300 MDD patients and 1,128 controls to find reduced default mode network functional connectivity in recurrent MDD, not first-episode MDD.

This study evaluates whether R-fMRI indices can differentiate brain tumors from normal tissue and finds that ALFF and VMHC, with Z-standardization, are effective in this task.

The paper examines age-related changes in brain network connectivity in ASD and identifies distinct maturation patterns in three core networks.

This study evaluates how multiple comparison correction strategies and sample sizes affect reproducibility of R-fMRI metrics, finding that permutation tests with TFCE balance error rates and reliability, while larger samples improve replicability.