A Flexible Constrained ICA Approach for Multisubject fMRI Analysis.
Large‐scale analysis of functional connectivity within intrinsic brain networks using functional magnetic resonance imaging (fMRI) data has been widely used for identifying biomarkers in various psychiatric disorders. While the emerging access to large neuroimaging datasets provides unprecedented op...
| Publicado en: | International Journal of Biomedical Imaging Vol. 2025; pp. 1 - 20 |
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| Autores principales: | , , , , , |
| Formato: | algorithm computer program diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
3/26/2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=184106600&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 184106600 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16874188 1WZI jtl: International Journal of Biomedical Imaging issn: 16874188 maglogo: N pubinfo: dt: 3/26/2025 vid: 2025 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 184106600 184106600 184106600 10.1155/ijbi/2064944 184106600 ppf: 1 ppct: 19 formats: tig: atl: A Flexible Constrained ICA Approach for Multisubject fMRI Analysis. aug: au: Yang, Hanlu Vu, Trung Dhrubo, Ehsan Ahmed Calhoun, Vince D. Adali, Tülay Gallegos Funes, Francisco Javier affil: Department of Computer Science and Electrical Engineering,, University of Maryland,, Baltimore County, Maryland,, USA, umaryland.edu sug: subj: Magnetic Resonance Imaging Methods Brain Mapping Methods Schizophrenia Diagnosis Human Funding Source Neural Networks (Computer) Bioinformatics Data Analysis, Statistical Mental Disorders Diagnosis Algorithms Descriptive Statistics Prospective Studies Biological Markers ab: Large‐scale analysis of functional connectivity within intrinsic brain networks using functional magnetic resonance imaging (fMRI) data has been widely used for identifying biomarkers in various psychiatric disorders. While the emerging access to large neuroimaging datasets provides unprecedented opportunities for exploring brain functions, they also pose significant computational complexity challenges due to the large amount of inherent variability across individuals and the complexity of brain activity patterns. To address these challenges, this paper introduces two novel constrained ICA methods, arc‐EBM and minc‐EBM, designed to overcome the computational complexity issue by incorporating prior information into the analysis framework. The proposed methods preserve the subject variability by adaptively selecting the constrained parameters for different functional networks and individuals, while also allowing estimation flexibility for activities not covered by the prior information through the concept of free components. Our methods are shown to enhance the precision of functional network estimation and improve the capture of subject variability across different cohorts. We evaluate the proposed methods using both synthetic and real fMRI data. By applying the proposed methods to a resting‐state fMRI dataset including 179 subjects, both algorithms successfully reveal significant group differences in functional network connectivity between healthy controls and schizophrenia patients. The observed group differences, particularly the abnormal connectivity alterations in networks involving the thalamus, subthalamus/hypothalamus, and superior temporal gyrus, align with findings from previous clinical studies. Furthermore, our results demonstrate that the constraint parameters adaptively selected by arc‐EBM reveal more diverse resting‐state network structures in individuals with schizophrenia compared with healthy controls. This finding is consistent with prior studies and suggests that the selected constraint parameters could serve as potential biomarkers for mental disorder diagnosis. pubtype: Academic Journal doctype: algorithm computer program diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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