Dataset Information

Frequency-specific age-related decreased brain network diversity in cognitively healthy elderly: A whole-brain data-driven analysis.

ABSTRACT: Age-related changes in functional brain network have been well documented. However, recent studies have suggested the nonstationary properties of the functional connectivity of the brain, and little is known about the changes of functional connectivity dynamics during aging. In this study, a two-step singular value decomposition was introduced to capture the dynamic patterns of the time-varying functional connectivity in different frequency intervals, and the whole-brain and regional brain diversity were quantified by using Shannon entropy. The relationships between age and functional connectivity dynamics were investigated in a relatively large sample cohort of cognitively healthy elderly (N?=?188, ages 65-80). The results showed an age-related decreased diversity in the whole brain as well as in the right inferior frontal gyrus, right amygdala, right hippocampus, left parahippocampal, and left inferior parietal gyrus in the frequency interval of 0.06-0.12?Hz. In addition, the whole-brain diversity during resting state could also reflect the general mental flexibility. This study provided the first evidence of frequency-specific age effects on the functional connectivity dynamics in cognitively healthy elderly, and may shed new light on the dynamic functional connectivity analysis of aging and neurodegenerative diseases.

SUBMITTER: Lou W

PROVIDER: S-EPMC6865413 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Frequency-specific age-related decreased brain network diversity in cognitively healthy elderly: A whole-brain data-driven analysis.

Lou Wutao W Wang Defeng D Wong Adrian A Chu Winnie C W WCW Mok Vincent C T VCT Shi Lin L

Human brain mapping 20180921 1

Age-related changes in functional brain network have been well documented. However, recent studies have suggested the nonstationary properties of the functional connectivity of the brain, and little is known about the changes of functional connectivity dynamics during aging. In this study, a two-step singular value decomposition was introduced to capture the dynamic patterns of the time-varying functional connectivity in different frequency intervals, and the whole-brain and regional brain diver ...[more]

PMID: 30240493

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Project description:Obesity is a risk factor for cognitive decline and gray matter volume loss in aging. Studies have shown that different metabolic factors, e.g., dysregulated glucose metabolism and systemic inflammation, might mediate this association. Yet, even though these risk factors tend to co-occur, they have mostly been investigated separately, making it difficult to establish their joint contribution to gray matter volume structure in aging. Here, we therefore aimed to determine a metabolic profile of obesity that takes into account different anthropometric and metabolic measures to explain differences in gray matter volume in aging. We included 748 elderly, cognitively healthy participants (age range: 60 - 79 years, BMI range: 17 - 42 kg/m2) of the LIFE-Adult Study. All participants had complete information on body mass index, waist-to-hip ratio, glycated hemoglobin, total blood cholesterol, high-density lipoprotein, interleukin-6, C-reactive protein, adiponectin and leptin. Voxelwise gray matter volume was extracted from T1-weighted images acquired on a 3T Siemens MRI scanner. We used partial least squares correlation to extract latent variables with maximal covariance between anthropometric, metabolic and gray matter volume and applied permutation/bootstrapping and cross-validation to test significance and reliability of the result. We further explored the association of the latent variables with cognitive performance. Permutation tests and cross-validation indicated that the first pair of latent variables was significant and reliable. The metabolic profile was driven by negative contributions from body mass index, waist-to-hip ratio, glycated hemoglobin, C-reactive protein and leptin and a positive contribution from adiponectin. It positively covaried with gray matter volume in temporal, frontal and occipital lobe as well as subcortical regions and cerebellum. This result shows that a metabolic profile characterized by high body fat, visceral adiposity and systemic inflammation is associated with reduced gray matter volume and potentially reduced executive function in older adults. We observed the highest contributions for body weight and fat mass, which indicates that factors underlying sustained energy imbalance, like sedentary lifestyle or intake of energy-dense food, might be important determinants of gray matter structure in aging.

Dataset Information

Frequency-specific age-related decreased brain network diversity in cognitively healthy elderly: A whole-brain data-driven analysis.

Publications

Frequency-specific age-related decreased brain network diversity in cognitively healthy elderly: A whole-brain data-driven analysis.

Similar Datasets

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