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Stanford W, Mucha PJ, Dayan E. Age-related differences in network controllability are mitigated by redundancy in large-scale brain networks. Commun Biol 2024; 7:701. [PMID: 38849512 PMCID: PMC11161655 DOI: 10.1038/s42003-024-06392-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/28/2024] [Indexed: 06/09/2024] Open
Abstract
The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we use diffusion MRI data from cognitively intact participants (n = 480, ages 40-90) to study age-associated differences in the average controllability of structural brain networks, topological features that could mitigate these differences, and the overall effect on cognitive function. We find age-associated declines in average controllability in control hubs and large-scale networks, particularly within the frontoparietal control and default mode networks. Further, we find that redundancy, a hypothesized mechanism of reserve, quantified via the assessment of multi-step paths within networks, mitigates the effects of topological differences on average network controllability. Lastly, we discover that average network controllability, redundancy, and grey matter volume, each uniquely contribute to predictive models of cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging.
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Affiliation(s)
- William Stanford
- Biological and Biomedical Sciences Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Peter J Mucha
- Department of Mathematics, Dartmouth College, Hanover, NH, USA
| | - Eran Dayan
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Koten JW, Koschutnig K, Wood G. An attempt to model the causal structure behind white matter aging and cognitive decline. Sci Rep 2023; 13:10883. [PMID: 37407647 DOI: 10.1038/s41598-023-37925-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 06/29/2023] [Indexed: 07/07/2023] Open
Abstract
In this diffusion tension imaging study, voxel wise structural equation modeling was used to unravel the relation between white matter, cognition, and age. Four neurocognitive ageing models describing the interplay between age, white matter integrity, and cognition were investigated but only two models survived an Akaike information criterion-based model selection procedure. The independent factor model predicts that there is no relation between white matter integrity and cognition although both systems are affected by age. The cognitive mediation model predicts that the relation between age and white matter integrity is mediated through cognition. Roughly 60% of the observed voxels were in agreement with the independent factor model while 16% of the observed voxels were in agreement with the cognitive mediation model. Imaging results of the latter model suggest that the deterioration of fibers-that connect the two hemispheres with each other-is partly caused by an age-related decline in cognitive functioning.
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Affiliation(s)
- Jan Willem Koten
- Brain Imaging Facility of the Interdisciplinary Centre for Clinical Research of the University Hospital Rheinisch-Westfälische Technische Hochschule (RWTH), 52074, Aachen, Germany.
- Department of Psychology, Karl-Franzens-University of Graz, 8010, Graz, Austria.
| | - Karl Koschutnig
- Department of Psychology, Karl-Franzens-University of Graz, 8010, Graz, Austria
- Biotechmed Graz, 8010, Graz, Austria
| | - Guilherme Wood
- Department of Psychology, Karl-Franzens-University of Graz, 8010, Graz, Austria
- COLIBRI Graz, 8010, Graz, Austria
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Liu Y, Hsu CCH, Huang CC, Zhang Y, Zhao J, Tsai SJ, Chen LK, Lin CP, Lo CYZ. Connectivity-Based Topographical Changes of the Corpus Callosum During Aging. Front Aging Neurosci 2021; 13:753236. [PMID: 34744693 PMCID: PMC8565522 DOI: 10.3389/fnagi.2021.753236] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 09/28/2021] [Indexed: 11/13/2022] Open
Abstract
Background: The corpus callosum (CC) is the most prominent white matter connection for interhemispheric information transfer. It is implicated in a variety of cognitive functions, which tend to decline with age. The region-specific projections of the fiber bundles with microstructural heterogeneity of the CC are associated with cognitive functions and diseases. However, how the CC is associated with the information transfer within functional networks and the connectivity changes during aging remain unclear. Studying the CC topography helps to understand the functional specialization and age-related changes of CC subregions. Methods: Diffusion tractography was used to subdivide the CC into seven subregions from 1,086 healthy volunteers within a wide age range (21-90 years), based on the connections to the cortical parcellations of the functional networks. Quantitative diffusion indices and connection probability were calculated to study the microstructure differences and age-related changes in the CC subregions. Results: According to the population-based probabilistic topography of the CC, part of the default mode network (DMN) and limbic network (LN) projected fibers through the genu and rostrum; the frontoparietal network (FPN), ventral attention network (VA) and somatomotor networks (SM) were interconnected by the CC body; callosal fibers arising from the part of the default mode network (DMN), dorsal attention network (DA) and visual network (VIS) passed through the splenium. Anterior CC subregions interconnecting DMN, LN, FPN, VA, and SM showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) and radial diffusivity (RD) than posterior CC subregions interconnecting DA and VIS. All the CC subregions showed slightly increasing FA and decreasing MD, RD, and axial diffusivity (AD) at younger ages and opposite trends at older ages. Besides, the anterior CC subregions exhibited larger microstructural and connectivity changes compared with the posterior CC subregions during aging. Conclusion: This study revealed the callosal subregions related to functional networks and uncovered an overall "anterior-to-posterior" region-specific changing trend during aging, which provides a baseline to identify the presence and timing of callosal connection states.
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Affiliation(s)
- Yuchen Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Chih-Chin Heather Hsu
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Center of Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Chu-Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China.,Shanghai Changning Mental Health Center, Shanghai, China
| | - Yajuan Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jiajia Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Division of Psychiatry, Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Liang-Kung Chen
- Center of Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan.,Aging and Health Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Taipei Municipal Gan-Dau Hospital, Taipei, Taiwan
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Aging and Health Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chun-Yi Zac Lo
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
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