Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion
Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion
Abstract Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies comparing individuals with SZ to healthy controls (HC) have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively). The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands. The initial implementation used a set of filters spanning the full connectivity spectral range, providing a unified approach to examine both sFNC and dFNC in a single analysis. Initial FBC results found that individuals with SZ spend more time in a less structured, more disconnected low-frequency (i.e., static) FNC state than HC, as well as preferential SZ occupancy in high-frequency connectivity states, suggesting a frequency-specific component underpinning the functional dysconnectivity observed in SZ. Building on these findings, we sought to link such frequency-specific patterns of FNC to covarying data-driven structural brain networks in the context of SZ. Specifically, we employ a multi-set canonical correlation analysis + joint independent components analysis (mCCA + jICA) data fusion framework to study the connection between grey matter volume (GMV) maps and FBC states across the full connectivity frequency spectrum. Our multimodal analysis identified two joint sources that captured co-varying patterns of frequency-specific functional connectivity and alterations in GMV with significant group differences in loading parameters between the SZ group and HC. The first joint source linked frequency-modulated connections between the subcortical and sensorimotor networks and GMV alterations in the frontal and temporal lobes, while the second joint source identified a relationship between low-frequency cerebellar-sensorimotor connectivity and structural changes in both the cerebellum and motor cortex. Together, these results show a strong connection between cortico-subcortical functional connectivity at both high and low frequencies and alterations in cortical GMV that may be relevant to the pathogenesis and pathophysiology of SZ.
Mathalon Daniel H.、Mueller Bryon A.、Potkin Steven G.、Preda Adrian、Sui Jing、Bustillo Juan R.、Calhoun Vince D.、Duda Marlena、Belger Aysenil、Ford Judith M.、Pearlson Godfrey D.、Van Erp Theo G.M.、Faghiri Ashkan
Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco||Department of Psychiatry and Weill Institute for Neurosciences, University of California San FranciscoDepartment of Psychiatry and Behavioral Sciences, University of MinnesotaDepartment of Psychiatry and Human Behavior, University of California IrvineDepartment of Psychiatry and Human Behavior, University of California IrvineTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University||IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal UniversityDepartment of Psychiatry and Behavioral Sciences, University of New MexicoTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory UniversityTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory UniversityDepartment of Psychiatry, University of North CarolinaMental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco||Department of Psychiatry and Weill Institute for Neurosciences, University of California San FranciscoDepartments of Psychiatry and Neuroscience, Yale University School of MedicineClinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine||Center for the Neurobiology of Learning and Memory, University of California IrvineTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University
神经病学、精神病学基础医学医学研究方法
Mathalon Daniel H.,Mueller Bryon A.,Potkin Steven G.,Preda Adrian,Sui Jing,Bustillo Juan R.,Calhoun Vince D.,Duda Marlena,Belger Aysenil,Ford Judith M.,Pearlson Godfrey D.,Van Erp Theo G.M.,Faghiri Ashkan.Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion[EB/OL].(2025-03-28)[2025-04-27].https://www.biorxiv.org/content/10.1101/2023.07.05.547840.点此复制
评论