Chun-Chao Huang1,2,3, Wen-Jin Hsieh4, Pei-Lin Lee4, Li-Ning Peng5,6, Li-Kuo Liu5,6, Wei-Ju Lee5,7, Jon-Kway Huang2,3, Liang-Kung Chen5,6, Ching-Po Lin1,4,8. 1. Institute of Neuroscience, National Yang-Ming University, Taipei, Taiwan. 2. Department of Radiology, MacKay Memorial Hospital, Taipei, Taiwan. 3. Department of Medicine, MacKay Medical College, Taipei, Taiwan. 4. Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan. 5. Aging and Health Research Center, National Yang-Ming University, Taipei, Taiwan. 6. Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan. 7. Department of Family Medicine, Taipei Veterans General Hospital Yuanshan Branch, Ilan, Taiwan. 8. Brain Research Center, National Yang-Ming University, Taipei, Taiwan.
Abstract
AIMS: Population aging is burdening the society globally, and the evaluation of functional networks is the key toward understanding cognitive changes in normal aging. However, the effect of age on default mode subnetworks has not been documented well, and age-related changes in many resting-state networks remain debatable. The purpose of this study was to propose more precise results for these issues using a large sample size. METHODS: We used group-level meta-ICA analysis and dual regression approach for identifying resting-state networks from functional magnetic resonance imaging data of 430 healthy elderly participants. Partial correlation was used to observe age-related correlations within and between resting-state networks. RESULTS: In the default mode network, only the ventral subnetwork negatively correlated with age. Age-related decrease in functional connectivity was also noted in the auditory, right frontoparietal, sensorimotor, and visual medial networks. Further, some age-related increases and decreases were observed for between-network correlations. CONCLUSION: The results of this study suggest that only the ventral default mode subnetwork had age-related decline in functional connectivity and several reverse patterns of resting-state networks for network development. Understanding age-related network changes may provide solutions for the impact of population aging and diagnosis of neurodegenerative diseases.
AIMS: Population aging is burdening the society globally, and the evaluation of functional networks is the key toward understanding cognitive changes in normal aging. However, the effect of age on default mode subnetworks has not been documented well, and age-related changes in many resting-state networks remain debatable. The purpose of this study was to propose more precise results for these issues using a large sample size. METHODS: We used group-level meta-ICA analysis and dual regression approach for identifying resting-state networks from functional magnetic resonance imaging data of 430 healthy elderly participants. Partial correlation was used to observe age-related correlations within and between resting-state networks. RESULTS: In the default mode network, only the ventral subnetwork negatively correlated with age. Age-related decrease in functional connectivity was also noted in the auditory, right frontoparietal, sensorimotor, and visual medial networks. Further, some age-related increases and decreases were observed for between-network correlations. CONCLUSION: The results of this study suggest that only the ventral default mode subnetwork had age-related decline in functional connectivity and several reverse patterns of resting-state networks for network development. Understanding age-related network changes may provide solutions for the impact of population aging and diagnosis of neurodegenerative diseases.
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