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

Lou, Wutao; Wang, Defeng; Wong, Adrian; Chu, Winnie C.W.; Mok, Vincent Chung Tong; Shi, Lin

doi:10.1002/hbm.24376

Cited by 21 publications

(13 citation statements)

References 67 publications

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“…The areas correlated with low age-related complexity are mainly located in the DN and frontoparietal control network. Importantly, unlike the other studies analyzed, here complexity is more closely related to a specific cognitive aspect such as mental flexibility, adding a putative neurophysiological mechanism of cognitive flexibility, or at least a closer link between BEN and cognition (Lou et al, 2019). This link is consistent with the general decrease of the neurocognitive flexibility in aging found both on a cognitive level and on a neural signal level.…”

Section: Brain Entropy In Physiological Agingsupporting

confidence: 80%

“…Shannon entropy (SE) has been used to correlate BEN and aging, showing a decrease of age-related complexity in the whole brain as well as in the right inferior frontal gyrus, right amygdala, right hippocampus, and left parahippocampal gyrus at the frequency interval of 0.06–0.12 Hz ( Lou et al, 2019 ). However, this study points out that whole-brain resting state entropy reflects general cognitive flexibility and information processing, measured by typical executive functions neuropsychological tests.…”

Section: Entropy In Agingmentioning

confidence: 99%

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Brain Entropy During Aging Through a Free Energy Principle Approach

Cieri

Zhuang

Caldwell

et al. 2021

Front. Hum. Neurosci.

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Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of “the entropic brain hypothesis.” In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

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Section: Brain Entropy In Physiological Agingsupporting

confidence: 80%

Section: Entropy In Agingmentioning

confidence: 99%

Brain Entropy During Aging Through a Free Energy Principle Approach

Cieri

Zhuang

Caldwell

et al. 2021

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Another study (Yin et al, 2016) found that age-related changes in the functional flexibility of the brain differ in different regions of the cerebral cortex. A recent study in 188 cognitively healthy elderly individuals (Lou et al, 2019) found that frequencyspecific brain network diversity decreased with increasing age at both the whole-brain and regional levels. Thus, exploring dynamic functional connectivity promises to enrich our knowledge of the functional organization of the brain, but little is known about changes in dynamic functional connectivity during aging.…”

Section: Introductionmentioning

confidence: 97%

Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club

et al. 2020

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Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50–64 years versus older group (n = 310); age range, 65–91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local–global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

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“…It is also an important node of the DMN (Greicius et al, 2003). Previous aging studies have found age-related changes in the FC of this region and an association between these changes and cognitive decline in different domains, specifically, executive function (Lou et al, 2019;Zhao et al, 2020), semantic knowledge (Hoffman & Morcom, 2018), inhibitory control (Hu et al, 2018), and memory (Huo et al, 2018;Lamichhane et al, 2018). In line with our results, there is evidence of the loss of hub role for left IPC in aging, which was demonstrated using cortical thickness covariance networks (Carey et al, 2019).…”

Section: F I G U R Ementioning

confidence: 99%