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Saha R, Saha DK, Fu Z, Duda M, Silva RF, Calhoun VD. Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588473. [PMID: 38645216 PMCID: PMC11030394 DOI: 10.1101/2024.04.07.588473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
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. 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 introduce two approaches and applied them to data from the Adolescent Brain and Cognitive Development (ABCD) dataset. First, we evaluate voxelwise sMRI-FCP 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. FCP 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 identify structured FCPs 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 (SCPs) including alterations in the bilateral sensorimotor cortex. Interestingly, females exhibit stronger coupling between brain functional and structural changes than males, highlighting sex-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate sex-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the dynamic nature of brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.
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Affiliation(s)
- Rekha Saha
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Debbrata K. Saha
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Marlena Duda
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Rogers F. Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University 55 Park Pl NE, Atlanta, GA 30303, USA
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Mitchell JW, Gillette MU. Development of circadian neurovascular function and its implications. Front Neurosci 2023; 17:1196606. [PMID: 37732312 PMCID: PMC10507717 DOI: 10.3389/fnins.2023.1196606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 08/14/2023] [Indexed: 09/22/2023] Open
Abstract
The neurovascular system forms the interface between the tissue of the central nervous system (CNS) and circulating blood. It plays a critical role in regulating movement of ions, small molecules, and cellular regulators into and out of brain tissue and in sustaining brain health. The neurovascular unit (NVU), the cells that form the structural and functional link between cells of the brain and the vasculature, maintains the blood-brain interface (BBI), controls cerebral blood flow, and surveils for injury. The neurovascular system is dynamic; it undergoes tight regulation of biochemical and cellular interactions to balance and support brain function. Development of an intrinsic circadian clock enables the NVU to anticipate rhythmic changes in brain activity and body physiology that occur over the day-night cycle. The development of circadian neurovascular function involves multiple cell types. We address the functional aspects of the circadian clock in the components of the NVU and their effects in regulating neurovascular physiology, including BBI permeability, cerebral blood flow, and inflammation. Disrupting the circadian clock impairs a number of physiological processes associated with the NVU, many of which are correlated with an increased risk of dysfunction and disease. Consequently, understanding the cell biology and physiology of the NVU is critical to diminishing consequences of impaired neurovascular function, including cerebral bleeding and neurodegeneration.
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Affiliation(s)
- Jennifer W. Mitchell
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
| | - Martha U. Gillette
- Department of Cell and Developmental Biology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Department of Molecular and Integrative Physiology, University of Illinois Urbana-Champaign, Urbana, IL, United States
- Carle-Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States
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Liu X, Tyler LK, Rowe JB, Tsvetanov KA. Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects. Hum Brain Mapp 2022; 43:5490-5508. [PMID: 35855641 PMCID: PMC9704789 DOI: 10.1002/hbm.26025] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/24/2022] [Accepted: 07/07/2022] [Indexed: 01/15/2023] Open
Abstract
Brain aging is a complex process that requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization, and vascular dynamics. However, most neuroimaging studies of aging have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in aging. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging (MRI) of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18-88 years (main dataset n = 215 and secondary dataset n = 433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns. Split-sample (n = 108/107) and out-of-sample (n = 433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with age-related and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy aging.
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Affiliation(s)
- Xulin Liu
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Lorraine K. Tyler
- The Centre for Speech, Language and the Brain, Department of PsychologyUniversity of CambridgeCambridgeUK
| | - Cam‐CAN
- Cambridge Centre for Ageing and Neuroscience (Cam‐CAN), MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Kamen A. Tsvetanov
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- The Centre for Speech, Language and the Brain, Department of PsychologyUniversity of CambridgeCambridgeUK
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