Rekha Saha, Debbrata K. Saha, Zening Fu, Marlena Duda, Rogers F. Silva, Tony W. Wilson, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun
{"title":"Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion","authors":"Rekha Saha, Debbrata K. Saha, Zening Fu, Marlena Duda, Rogers F. Silva, Tony W. Wilson, Yu-Ping Wang, Julia M. Stephen, Vince D. Calhoun","doi":"10.1002/hbm.70241","DOIUrl":null,"url":null,"abstract":"<p>Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. However each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduced two approaches and applied them to data from the adolescent brain and cognitive development (ABCD) dataset. First, we evaluate voxel-wise sMRI-<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>FCP</mi>\n <mtext>asym</mtext>\n </msub>\n </mrow>\n <annotation>$$ {FCP}_{asym} $$</annotation>\n </semantics></math> coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject-level variation. <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mi>FCP</mi>\n <mtext>asym</mtext>\n </msub>\n </mrow>\n <annotation>$$ {FCP}_{asym} $$</annotation>\n </semantics></math> components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identified structured <span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mtext>FCPs</mtext>\n <mi>sym</mi>\n </msub>\n </mrow>\n <annotation>$$ {FCPs}_{sym} $$</annotation>\n </semantics></math> such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns (<span></span><math>\n <semantics>\n <mrow>\n <msub>\n <mtext>SCPs</mtext>\n <mi>sym</mi>\n </msub>\n </mrow>\n <annotation>$$ {SCPs}_{sym} $$</annotation>\n </semantics></math>) including alterations in the bilateral sensorimotor cortex. Interestingly, females show stronger connection between brain functional and structural changes than males, highlighting gender-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate gender-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the evolving nature of whole brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70241","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Brain Mapping","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hbm.70241","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROIMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. However each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduced two approaches and applied them to data from the adolescent brain and cognitive development (ABCD) dataset. First, we evaluate voxel-wise sMRI- coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject-level variation. components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identified structured such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns () including alterations in the bilateral sensorimotor cortex. Interestingly, females show stronger connection between brain functional and structural changes than males, highlighting gender-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate gender-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the evolving nature of whole brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.
期刊介绍:
Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged.
Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.