Modeling Causal Interactions Across Brain Functional Subnetworks for Population-specific Disease Analysis

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Hauptverfasser: Moreno, Alissen, Zhang, Yingying, Huang, Qi, Vazquez, Fabian, Nunez, Jose A., Enriquez, Erik, Kim, Dongchul, Zhou, Kaixiong, Gao, Hongchang, Gu, Pengfei, Zhan, Liang, Tang, Haoteng
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Veröffentlicht: 2025
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author Moreno, Alissen
Zhang, Yingying
Huang, Qi
Vazquez, Fabian
Nunez, Jose A.
Enriquez, Erik
Kim, Dongchul
Zhou, Kaixiong
Gao, Hongchang
Gu, Pengfei
Zhan, Liang
Tang, Haoteng
author_facet Moreno, Alissen
Zhang, Yingying
Huang, Qi
Vazquez, Fabian
Nunez, Jose A.
Enriquez, Erik
Kim, Dongchul
Zhou, Kaixiong
Gao, Hongchang
Gu, Pengfei
Zhan, Liang
Tang, Haoteng
contents Current neuroimaging studies on neurodegenerative diseases and psychological risk factors have been developed predominantly in non Hispanic White cohorts, with other populations markedly underrepresented. In this work, we construct directed hyper connectomes among large scale functional brain systems based on causal influences between brain regions, and examine their links to Alzheimer Disease progression and worry levels across racial groups. By using Health and Aging Brain Study Health Disparities (HABS HD) dataset, our experimental results suggest that neglecting racial variation in brain network architecture may reduce predictive performance in both cognitive and affective phenotypes. Important shared and population-specific hyper-connectome patterns related to both AD progression and worry levels were identified. We further observed distinct closed loop directed circuits across groups, suggesting that different populations may rely on distinct feedback based network regulation strategies when supporting cognition or managing emotional states. Together, these results indicate a common backbone of network vulnerability with population-dependent variations in regulatory coordination, underscoring the importance of population-aware neuroimaging models.
format Preprint
id arxiv_https___arxiv_org_abs_2511_05548
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modeling Causal Interactions Across Brain Functional Subnetworks for Population-specific Disease Analysis
Moreno, Alissen
Zhang, Yingying
Huang, Qi
Vazquez, Fabian
Nunez, Jose A.
Enriquez, Erik
Kim, Dongchul
Zhou, Kaixiong
Gao, Hongchang
Gu, Pengfei
Zhan, Liang
Tang, Haoteng
Neurons and Cognition
Applications
Current neuroimaging studies on neurodegenerative diseases and psychological risk factors have been developed predominantly in non Hispanic White cohorts, with other populations markedly underrepresented. In this work, we construct directed hyper connectomes among large scale functional brain systems based on causal influences between brain regions, and examine their links to Alzheimer Disease progression and worry levels across racial groups. By using Health and Aging Brain Study Health Disparities (HABS HD) dataset, our experimental results suggest that neglecting racial variation in brain network architecture may reduce predictive performance in both cognitive and affective phenotypes. Important shared and population-specific hyper-connectome patterns related to both AD progression and worry levels were identified. We further observed distinct closed loop directed circuits across groups, suggesting that different populations may rely on distinct feedback based network regulation strategies when supporting cognition or managing emotional states. Together, these results indicate a common backbone of network vulnerability with population-dependent variations in regulatory coordination, underscoring the importance of population-aware neuroimaging models.
title Modeling Causal Interactions Across Brain Functional Subnetworks for Population-specific Disease Analysis
topic Neurons and Cognition
Applications
url https://arxiv.org/abs/2511.05548