The Increase of the Functional Entropy of the Human Brain with Age

Yao, Ye; Lu, Wenlian; Xu, Bing; Li, C. B.; Lin, Ching-Po; Waxman, David J.; Feng, Jianfeng

doi:10.1038/srep02853

Cited by 78 publications

(89 citation statements)

References 44 publications

(57 reference statements)

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“…In contrast, increases in graph randomness, as measured by entropy, have been shown to track changes associated with age (Yao et al, 2013). Age has been associated with increased functional connectivity in particular functional systems (e.g., sensorimotor) and decreased functional connectivity in others (e.g., DMN) (Andrews-Hanna et al, 2007; Biswal et al, 2010b) whereas HIV has been characterized as causing targeted disruption of particular systems (e.g., DMN) (Thomas et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Weighted brain networks in disease: centrality and entropy in human immunodeficiency virus and aging

Thomas

Brier

Ortega

et al. 2015

Neurobiology of Aging

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Graph theory models can produce simple, biologically informative metrics of the topology of resting-state functional connectivity (FC) networks. However, typical graph theory approaches model FC relationships between regions (nodes) as unweighted edges, complicating their interpretability in studies of disease or aging. We extended existing techniques and constructed fully-connected weighted graphs for groups of age-matched HIV positive (n=67) and HIV negative (n=77) individuals. We compared test-retest reliability of weighted vs. unweighted metrics in an independent study of healthy individuals (n=22) and found weighted measures to be more stable. We quantified two measures of node centrality (closeness centrality and eigenvector centrality) to capture the relative importance of individual nodes. We also quantified one measure of graph entropy (diversity) to measure the variability in connection strength (edge weights) at each node. HIV was primarily associated with differences in measures of centrality, and age was primarily associated with differences in diversity. HIV and age were associated with divergent measures when evaluated at the whole-graph level, within individual functional networks, and at the level of individual nodes. Graph models may allow us to distinguish previously indistinguishable effects related to HIV and age on FC.

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Section: Introductionmentioning

confidence: 99%

Weighted brain networks in disease: centrality and entropy in human immunodeficiency virus and aging

Thomas

Brier

Ortega

et al. 2015

Neurobiology of Aging

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“…Age is associated with a reduction of functional correlations within certain resting state networks (RSNs) (e.g. default mode network (DMN)) (Andrews-Hanna et al 2007; Yao et al 2013; Geerligs et al 2014). Selective brain vulnerability correlates with age-associated neurodegenerative disorders (Seeley et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Intrinsic network connectivity abnormalities in HIV-infected individuals over age 60

et al. 2015

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Individuals infected with HIV are living longer due to effective treatment with combination antiretroviral therapy (cART). Despite these advances, HIV-associated neurocognitive disorders (HAND) remain prevalent. In this study, we analyzed resting state functional connectivity (rs-fc) data from HIV-infected and matched HIV-uninfected adults aged 60 years and older to determine associations between HIV status, neuropsychological performance, and clinical variables. HIV-infected participants with detectable plasma HIV RNA exhibited decreased rs-fc within the salience (SAL) network compared to HIV-infected participants with suppressed plasma HIV RNA. We did not identify differences in rs-fc within HIV-infected individuals by HAND status. Our analysis identifies focal deficits in the SAL network that may be mitigated with suppression of plasma virus. However, these findings suggest that rs-fc may not be sensitive as a marker of HAND among individuals with suppressed plasma viral loads.

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“…Yao and his colleagues [51] regarded the correlation coefficients between brain regions as a random variable, and applied relative entropy to measure the variability in the distribution of correlation coefficients. The results demonstrated that the relative entropy increased with age.…”

Section: The Orderness Of the Functional Connectome Measured By The Nmentioning

confidence: 99%

“…These results investigated whether the FC changed with age. Jia and his colleagues [51] regarded the dynamic correlation coefficients between brain regions as a random variable, and applied sample entropy to measure the complexity of dynamic FC, while the results demonstrated that the sample entropy reduced with age. Mcintosh and his colleagues [52] used multiscale entropy (MSE) to measure brain signal variability through a collection of the electroencephalography (EEG) and magnetoenphalography (MEG) signals in tasks.…”

Section: The Orderness Of the Functional Connectome Measured By The Nmentioning

confidence: 99%

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

Fan

Zeng

Shen

et al. 2017

Entropy

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Abstract:Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying functional connectivity patterns of the developing and aging brain. Normal brain development is characterized by continuous and significant network evolution through infancy, childhood, and adolescence, following specific maturational patterns. Normal aging is related to some resting state brain networks disruption, which are associated with certain cognitive decline. It is a big challenge to design an integral metric to track connectome evolution patterns across the lifespan, which is to understand the principles of network organization in the human brain. In this study, we first defined a brain network eigen-entropy (NEE) based on the energy probability (EP) of each brain node. Next, we used the NEE to characterize the lifespan orderness trajectory of the whole-brain functional connectivity of 173 healthy individuals ranging in age from 7 to 85 years. The results revealed that during the lifespan, the whole-brain NEE exhibited a significant non-linear decrease and that the EP distribution shifted from concentration to wide dispersion, implying orderness enhancement of functional connectome over age. Furthermore, brain regions with significant EP changes from the flourishing (7-20 years) to the youth period (23-38 years) were mainly located in the right prefrontal cortex and basal ganglia, and were involved in emotion regulation and executive function in coordination with the action of the sensory system, implying that self-awareness and voluntary control performance significantly changed during neurodevelopment. However, the changes from the youth period to middle age (40-59 years) were located in the mesial temporal lobe and caudate, which are associated with long-term memory, implying that the memory of the human brain begins to decline with age during this period. Overall, the findings suggested that the human connectome shifted from a relatively anatomical driven state to an orderly organized state with lower entropy.

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The Increase of the Functional Entropy of the Human Brain with Age

Cited by 78 publications

References 44 publications

Weighted brain networks in disease: centrality and entropy in human immunodeficiency virus and aging

Weighted brain networks in disease: centrality and entropy in human immunodeficiency virus and aging

Intrinsic network connectivity abnormalities in HIV-infected individuals over age 60

Lifespan Development of the Human Brain Revealed by Large-Scale Network Eigen-Entropy

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