Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and function.

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Bibliographic Details
Title: Multimodal subspace independent vector analysis effectively captures latent relationships between brain structure and function.
Authors: Li X; Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States., Kochunov P; Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, United States., Adali T; Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, United States., Silva RF; Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States., Calhoun VD; Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
Source: Imaging neuroscience (Cambridge, Mass.) [Imaging Neurosci (Camb)] 2026 Jun 18; Vol. 4. Date of Electronic Publication: 2026 Jun 18 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: The MIT Press Country of Publication: United States NLM ID: 9918663686606676 Publication Model: eCollection Cited Medium: Internet ISSN: 2837-6056 (Electronic) Linking ISSN: 28376056 NLM ISO Abbreviation: Imaging Neurosci (Camb) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2837-6056
DOI:10.1162/IMAG.a.1266