The paper uses IS-RSA to link brain morphometry, connectivity, and mentalising ability, finding significant correlations and region-specific associations in 24 participants.

Human Brain Mapping · Apr 13, 2023Peer-reviewedNeuroscience

Genetic influences on the shape of brain ventricular and subcortical structures

Bingxin Zhao, Tengfei Li, Xiaochen Yang, Juan Shu, Xifeng Wang, Tianyou Luo, Yue Yang, Zhenyi Wu, Zirui Fan, Zhiwen Jiang, Jie Chen, Yue Shan, Jiarui Tang, Di Xiong, Ziliang Zhu, , Hongtu Zhu B

The paper identifies 60 genetic loci associated with brain ventricular and subcortical shape features using shape measures from over 45,000 UK Biobank and ABCD study subjects.

medRxiv · Sep 26, 2022 · PreprintGenetic & Genomic Medicine

FEDERATED MORPHOMETRY FEATURE SELECTION FOR HIPPOCAMPAL MORPHOMETRY ASSOCIATED BETA-AMYLOID AND TAU PATHOLOGY

Jianfeng Wu, Qunxi Dong, Jie Zhang, Yi Su, Teresa Wu, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Natasha Leporé, Kewei Chen, Paul M. Thompson, Yalin Wang, Alzheimer’s Disease Neuroimaging Initiative

This paper introduces FMFS, a framework for selecting hippocampal morphometry features linked to Aβ/tau pathology, showing it outperforms existing methods and identifies key subregions for biomarker development.

Frontiers in Neuroscience · Nov 25, 2021Peer-reviewedNeuroscience

Predicting Brain Amyloid using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals from the ADNI and OASIS Databases

Jianfeng Wu, Qunxi Dong, Jie Gui, Jie Zhang, Yi Su, Kewei Chen, Paul M. Thompson, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Yalin Wang

This paper develops a method to predict brain amyloid burden using MRI-based morphometry statistics and sparse coding, achieving high accuracy in ADNI and OASIS cohorts.

Frontiers in Neuroscience · Aug 6, 2021Peer-reviewedNeuroscience