Jiang Qiu

The paper identifies sgACC functional connectivity abnormalities in depression using large-scale brain imaging data and develops an individualized TMS targeting algorithm to improve treatment outcomes.

The paper identifies dissociable neural connectome patterns for reward and punishment sensitivity using multimodal fMRI and transcriptomic data, linking them to specific gene sets and neurotransmitter systems.

The paper evaluates factors affecting brain-age prediction models using structural neuroimaging data from 35,683 individuals, finding optimal model performance with no site harmonization, age-binning, and a sample size of over 1,600.

The paper introduces a longitudinal dataset of school-age children and adolescents in China, detailing its design, sampling, and neuroimaging measurements.

The paper identifies two neurophysiological subtypes of MDD using normative models of functional connectivity in a large multisite fMRI dataset.

The paper benchmarks and optimizes a normative modeling framework for brain morphometry across the lifespan using MFPR, showing excellent accuracy and stability.

The paper shows the default mode network (DMN) actively supports narrative speech comprehension, not just being suppressed, through neural couplings and hierarchical network interactions.

The paper develops a pipeline to generate age-specific MRI brain templates and growth charts for children and adolescents, revealing neurodevelopmental differences between Chinese and US populations.

The paper identifies genes associated with dynamic brain network changes and links them to neuroplasticity processes, showing that temporal variability predicts cognitive outcomes.

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 investigates reproducibility of functional brain alterations in MDD using a large multisite R-fMRI dataset and finds consistent patterns across centers but notes influences from clinical factors.

This study examines age-related changes in dynamic functional network connectivity across the adult lifespan, finding reduced variability and specific topological features associated with cognitive aging.

The paper presents a dataset of structural and functional MRI scans from 494 adults to study brain development and aging.