Electroacupuncture Modulates Resting-State Functional Connectivity in the Default Mode Network for Healthy Older Adults.

Aging involves cognitive decline and prominent alterations in brain activity. Electroacupuncture (EA), a traditional Chinese medicine approach, is demonstrated to be effective in improving cognitive function of older adults. However, the specific neural mechanism underlying this modulation effect remains unclear. In this study, we used functional magnetic resonance imaging (fMRI) to investigate whether EA could improve cognitive performance of community-dwelling older adults and whether these potential improvements are associated with the EA-induced brain functional connectivity alterations. Thirty healthy older adults were recruited and randomly assigned to the EA group and the control group. Behaviorally, we observed an EA-induced improvement in cognitive performance of older adults in the Montreal Cognitive Assessment. On a neural perspective, the EA intervention significantly increased the functional connectivity within the default mode network. Moreover, we found a positive association between the improvement in delayed memory performance and the alterations in the ventral medial prefrontal cortex-hippocampal formation connectivity in the EA group. This study extends previous findings by showing that healthy older adults exhibit neural plasticity manifested as increased functional connectivity after EA sessions, which could induce therapeutic effects in the treatment of neurodegenerative diseases.

Sleep Quality Modulates the Association between Dynamic Functional Network Connectivity and Cognitive Function in Healthy Older Adults.

Aging is associated with changes in sleep, brain activity, and cognitive function, as well as the association among these factors; however, the precise nature of these changes has not been elucidated. This study systematically investigated the modulatory effect of sleep on the relationship between brain functional network connectivity (FNC) and cognitive function in older adults. In total, 107 community-dwelling healthy older adults were recruited and assigned into poor sleep and good sleep groups based on the Pittsburgh Sleep Quality Index. The static functional network connectivity (sFNC), the temporal variability of dynamic FNC (dFNC) from variance (dFNC-var), and the dFNC from clustering state (dFNC-state) were calculated. Corresponding cognition-predictive models were constructed for each sleep group. dFNC but not sFNC, was able to significantly predict the cognitive function in older adults. Specifically, sleep played a modulatory role in the association between dFNC and cognitive function, with sleep-specific variations at both microscopic (i.e., specific edges) and macroscopic levels (i.e., specific states) of dFNC.

Deciphering Age Differences in Experience-Based Decision-Making: The Role of Sleep.

OBJECTIVE: Recent studies have demonstrated that sleep not only facilitates memory consolidation but also benefits more complex cognitive skills such as decision-making in young adults. Older adults use different decision strategies compared with young adults, which leaves the role of sleep in older adults' decision-making unclear. We investigated the age-by-sleep effect on decision-making. METHODS: We recruited 67 young adults (ages 18 to 29 years) and 66 older adults (ages 60 to 79 years) and randomly assigned them into the "sleep" or "wake" study condition. They were given a modified Iowa gambling task to perform before and after a 12-hour interval with sleep or wakefulness. RESULTS: Using the typical model-free analysis, we found that young adults' between-session performance improved greater than that of older adults regardless of the sleep/wake condition. Furthermore, older adults with longer total sleep time showed a greater improvement in the selection of one "good" deck. To further examine the sleep effect on age-related differences in cognitive processes underlying decision-making, we conducted computational modelling. This more fine-grained analysis revealed that sleep improved feedback sensitivity for both young and older adults while it increased loss aversion for older adults but not for young adults. CONCLUSION: These findings indicate that sleep promotes learning-based decision-making performance via facilitating value representation, and such modulation is distinct in young compared to older adults.

Sleep-related brain atrophy and disrupted functional connectivity in older adults.

Aging associates with sleep dysfunction as well as brain alterations. However, the association between age-related brain alterations and their subjective sleep changes is less understood. To address this issue, we recorded T1 weighted structural and resting-state functional magnetic resonance imaging from both young (n = 62) and older adults (n = 108). In addition, all participants completed a battery of psychometric tests, including the Pittsburg Sleep Quality Index. We found that the age-related atrophy of cerebral gray matter, hippocampal and thalamic volume were associated with subjective sleep decline, and the atrophy of cerebral gray matter mediated the age effect on sleep. In addition, older adults exhibited decreased functional connectivity within the medial temporal lobe subsystem than their young counterparts. Moreover, there is a significant positive association between sleep and functional connectivity in young but not in older adults. In light of our findings, we suggest a neuropathological model in which age-related brain alterations may partially explain the well-documented declines in sleep with aging.