Juan Helen Zhou

Improving DASH adherence after midlife promotes better late-life cognition and brain health: the SG70 Study

This study shows that better adherence to the DASH diet in midlife and early elderhood improves late-life verbal memory and brain health through structural and neurovascular mechanisms.

From Geometry to Hierarchy: Charting the Dominant Modes of Human Cortical Function Through Development

This study shows that the development of long-range cortical connections leads to the emergence of hierarchical functional modes in the human cortex, shifting from geometrically driven patterns to sensory-association organization.

Spurious model comparisons are widespread in biomedical artificial intelligence

97% of 184 high-impact biomedical AI studies compare cross-validated models with tests assuming fold independence; in 69% of re-analyzable studies a significant comparison does not survive correction.

Developing a multi-modal neuroimaging-based BrainAge model across childhood

This paper develops and benchmarks BrainAge models using multi-modal neuroimaging data from childhood cohorts to distinguish healthy from symptomatic developmental trajectories.

Test Retest Reliability of Meta Analytic Networks During Naturalistic Viewing

This study compares the test-retest reliability of functional brain networks from resting-state and naturalistic viewing paradigms across two sessions, showing increased reliability with naturalistic viewing but varying by stimuli and networks.

Mind the Gap: Does Brain Age Improve Alzheimer's Disease Prediction?

This study compares brain age models and direct models for predicting Alzheimer's Disease outcomes, finding that direct models perform better despite brain age models having larger training data.

Longer scans boost prediction and cut costs in brain-wide association studies

The paper shows longer scans improve prediction accuracy in brain-wide association studies while reducing costs, with 30-minute scans being the most cost-effective.

Rate of brain aging associates with future executive function in Asian children and older adults

This study tests a brain age model on Singaporean children and elderly, finding that brain age gap change relates to future executive function in both groups.

WMH-DualTasker: A weakly-supervised deep learning model for automated white matter hyperintensities segmentation and visual rating prediction

WMH-DualTasker is a weakly-supervised deep learning model that segments white matter hyperintensities and predicts visual ratings, outperforming supervised methods on benchmark datasets.

Optimizing Biophysical Large-Scale Brain Circuit Models With Deep Neural Networks

This paper introduces DELSSOME, a deep learning framework that accelerates biophysical brain circuit model optimization, enabling faster parameter estimation and lifespan trajectory analysis of cortical E/I ratios.

Additive effects of cerebrovascular disease functional connectome phenotype and plasma p-tau181 on longitudinal neurodegeneration and cognitive outcomes

The paper examines how cerebrovascular disease markers and plasma p-tau181 interact to affect brain connectivity, grey matter volume, and cognitive decline over time.

DeepResBat: deep residual batch harmonization accounting for covariate distribution differences

DeepResBat improves MRI data harmonization by addressing covariate distribution differences, outperforming existing methods while avoiding false associations.

In-vivo whole-cortex estimation of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

The paper estimates the whole-cortex excitation-inhibition ratio using fMRI and shows it declines during youth, with lower ratios linked to better cognitive performance in children.

Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity

The paper develops homotopic local-global parcellations of the human cerebral cortex using resting-state and task-fMRI, showing improved homogeneity and lateralization compared to existing parcellations.

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

This study examines brain morphometric deviations in individuals at clinical high-risk for psychosis and finds they largely overlap with healthy variation and are not strongly associated with symptom severity or conversion to psychosis.

Comparison of individualized behavioral predictions across anatomical, diffusion and functional connectivity MRI

This study compares the ability of anatomical, diffusion, and functional MRI to predict individual behavioral measures, finding that functional connectivity provides the best predictions, especially for cognition.

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

The paper examines how structural and metabolic network integrity influences memory across Alzheimer's disease stages, finding pathology-dependent changes in these relationships.

Goal-specific brain MRI harmonization

This paper introduces a goal-specific MRI harmonization framework that improves downstream prediction performance by integrating application-specific constraints during harmonization.

Individual-Specific fMRI-Subspaces Improve Functional Connectivity Prediction of Behavior

The paper improves behavioral prediction by removing common resting-state fMRI signals from individual-specific subspaces, resulting in an 11.7% average improvement across 58 behavioral measures.

Cognitive vulnerability to sleep deprivation is robustly associated with two dynamic connectivity states

The paper links two dynamic connectivity states to cognitive vulnerability to sleep deprivation using fMRI data and behavioral measures.

Interpreting Temporal Fluctuations In Resting-State Functional Connectivity MRI

This paper examines statistical issues in dynamic functional connectivity analysis using resting-state fMRI data and suggests AR models may better capture temporal fluctuations than static FC or HMM approaches.