Longitudinal Changes in the Cerebral Cortex Functional Organization of Healthy Elderly.

Healthy aging is accompanied by disruptions in the functional modular organization of the human brain. Cross-sectional studies have shown age-related reductions in the functional segregation and distinctiveness of brain networks. However, less is known about the longitudinal changes in brain functional modular organization and their associations with aging-related cognitive decline. We examined age- and aging-related changes in functional architecture of the cerebral cortex using a dataset comprising a cross-sectional healthy young cohort of 57 individuals (mean ± SD age, 23.71 ± 3.61 years, 22 males) and a longitudinal healthy elderly cohort of 72 individuals (mean ± baseline age, 68.22 ± 5.80 years, 39 males) with 2-3 time points (18-24 months apart) of task-free fMRI data. We found both cross-sectional (elderly vs young) and longitudinal (in elderly) global decreases in network segregation (decreased local efficiency), integration (decreased global efficiency), and module distinctiveness (increased participation coefficient and decreased system segregation). At the modular level, whereas cross-sectional analyses revealed higher participation coefficient across all modules in the elderly compared with young participants, longitudinal analyses revealed focal longitudinal participation coefficient increases in three higher-order cognitive modules: control network, default mode network, and salience/ventral attention network. Cross-sectionally, elderly participants also showed worse attention performance with lower local efficiency and higher mean participation coefficient, and worse global cognitive performance with higher participation coefficient in the dorsal attention/control network. These findings suggest that healthy aging is associated with whole-brain connectome-wide changes in the functional modular organization of the brain, accompanied by loss of functional segregation, particularly in higher-order cognitive networks.SIGNIFICANCE STATEMENT Cross-sectional studies have demonstrated age-related reductions in the functional segregation and distinctiveness of brain networks. However, longitudinal aging-related changes in brain functional modular architecture and their links to cognitive decline remain relatively understudied. Using graph theoretical and community detection approaches to study task-free functional network changes in a cross-sectional young and longitudinal healthy elderly cohort, we showed that aging was associated with global declines in network segregation, integration, and module distinctiveness, and specific declines in distinctiveness of higher-order cognitive networks. Further, such functional network deterioration was associated with poorer cognitive performance cross-sectionally. Our findings suggest that healthy aging is associated with system-level changes in brain functional modular organization, accompanied by functional segregation loss particularly in higher-order networks specialized for cognition.

Vigilance declines following sleep deprivation are associated with two previously identified dynamic connectivity states.

Robustly linking dynamic functional connectivity (DFC) states to behaviour is important for establishing the utility of the method as a functional measurement. We previously used a sliding window approach to identify two dynamic connectivity states (DCS) related to vigilance. A new sample of 32 healthy participants underwent two sets of task-free functional magnetic resonance imaging (fMRI) scans, once in a well-rested state and once after a single night of total sleep deprivation. Using a temporal difference method, DFC and clustering analysis on the task-free fMRI data revealed five centroids that were highly correlated with those found in previous work. In particular, two of these states were associated with high and low arousal respectively. Individual differences in vulnerability to sleep deprivation were measured by assessing state-related changes in Psychomotor Vigilance Test (PVT) performance. Changes in the duration spent in each of the arousal states from the well-rested to the sleep-deprived condition correlated with declines in PVT performance. The reproducibility of DFC measures and their association with vigilance highlight their utility in serving as a neuroimaging method with behavioural relevance. (178 words).

Pace yourself: Neural activation and connectivity changes over time vary by task type and pacing.

Performance deterioration over time, or time-on-task (TOT) effects, can be observed across a variety of tasks, but little attention has been paid to how TOT-related brain activity may differ based on task pacing and cognitive demands. Here, we employ a set of three closely related tasks to investigate the effect of these variables on fMRI activation and connectivity. When participants dictated the pace of their own responses, activation and network connectivity within the dorsal attention network (DAN) increased over short time scales (~2-3 min), a phenomenon that was not observed when participants had no control over their pace of work. Reaction time slowing was also the most pronounced in this self-paced task. In contrast, TOT-related changes in default-mode network (DMN) activity and connectivity, DAN-DMN anti-correlations, and pupil diameter did not differ based on pacing or task instructions. Over a longer (~10 min) time scale, task-positive activation and connectivity decreased in all paradigms, in agreement with older findings. These results highlight dynamic patterns of resource allocation that have not previously been observed in fMRI experiments, and speak to the idea that the brain may strategically allocate resources depending on the task at hand and the time scale of work.

Dynamic functional connectivity and its behavioral correlates beyond vigilance.

Fluctuations in resting-state functional connectivity and global signal have been found to correspond with vigilance fluctuations, but their associations with other behavioral measures are unclear. We evaluated 52 healthy adolescents after a week of adequate sleep followed by five nights of sleep restriction to unmask inter-individual differences in cognition and mood. Resting state scans obtained at baseline only, analyzed using sliding window analysis, consistently yielded two polar dynamic functional connectivity states (DCSs) corresponding to previously reported 'low arousal' and 'high arousal' states. We found that the relative temporal preponderance of two dynamic connectivity states (DCS) in well-rested participants, indexed by a median split of participants, based on the relative time spent in these DCS, revealed highly significant group differences in vigilance at baseline and its decline following multiple nights of sleep restriction. Group differences in processing speed and working memory following manipulation but not at baseline suggest utility of DCS in predicting cognitive vulnerabilities unmasked by a stressor like sleep restriction. DCS temporal predominance was uninformative about mood and sleepiness speaking to specificity in its behavioral predictions. Global signal fluctuation provided information confined to vigilance. This appears to be related to head motion, which increases during periods of low arousal.

Dynamic functional connectivity markers of objective trait mindfulness.

While mindfulness is commonly viewed as a skill to be cultivated through practice, untrained individuals can also vary widely in dispositional mindfulness. Prior research has identified static neural connectivity correlates of this trait. Here, we use dynamic functional connectivity (DFC) analysis of resting-state fMRI to study time-varying connectivity patterns associated with naturally varying and objectively measured trait mindfulness. Participants were selected from the top and bottom tertiles of performers on a breath-counting task to form high trait mindfulness (HTM; N = 21) and low trait mindfulness (LTM; N = 18) groups. DFC analysis of resting state fMRI data revealed that the HTM group spent significantly more time in a brain state associated with task-readiness - a state characterized by high within-network connectivity and greater anti-correlations between task-positive networks and the default-mode network (DMN). The HTM group transitioned between brain states more frequently, but the dwell time in each episode of the task-ready state was equivalent between groups. These results persisted even after controlling for vigilance. Across individuals, certain connectivity metrics were weakly correlated with self-reported mindfulness as measured by the Five Facet Mindfulness Questionnaire, though these did not survive multiple comparisons correction. In the static connectivity maps, HTM individuals had greater within-network connectivity in the DMN and the salience network, and greater anti-correlations between the DMN and task-positive networks. In sum, DFC features robustly distinguish HTM and LTM individuals, and may be useful biological markers for the measurement of dispositional mindfulness.

Longitudinal brain structure and cognitive changes over 8 years in an East Asian cohort.

Although East Asia harbors the largest number of aging adults in the world, there is currently little data clarifying the longitudinal brain-cognition relationships in this group. Here, we report structural MRI and neuropsychological findings from relatively healthy Chinese older adults of the Singapore-Longitudinal Aging Brain Study cohort over 8 years of follow up (n=111, mean age=67.1 years, range=56.1-83.1 years at baseline). Aging-related change in structural volume was observed, with total cerebral atrophy at -0.56%/year, hippocampal atrophy at -0.94%/year and ventricular expansion at 3.56%/year. Only speed of processing showed an aging-related decline, while other cognitive domains were relatively maintained. Faster decline in global cognition was associated with total cerebral, hippocampal and gray matter volume losses over time. Faster total cerebral atrophy and white matter atrophy (frontal and parietal regions) was associated with faster decline in verbal memory. Hippocampal atrophy and ventricular expansion were both associated with greater decline in verbal memory and executive function. Our findings provide a benchmark for research on brain structural and cognitive changes with aging in East Asians.

Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation.

Significant inter-individual differences in vigilance decline following sleep deprivation exist. We characterized functional connectivity in 68 healthy young adult participants in rested wakefulness and following a night of total sleep deprivation. After whole brain signal regression, functionally connected cortical networks during the well-rested state exhibited reduced correlation following sleep deprivation, suggesting that highly integrated brain regions become less integrated during sleep deprivation. In contrast, anti-correlations in the well-rested state became less so following sleep deprivation, suggesting that highly segregated networks become less segregated during sleep deprivation. Subjects more resilient to vigilance decline following sleep deprivation showed stronger anti-correlations among several networks. The weaker anti-correlations overlapped with connectivity alterations following sleep deprivation. Resilient individuals thus evidence clearer separation of highly segregated cortical networks in the well-rested state. In contrast to corticocortical connectivity, subcortical-cortical connectivity was comparable across resilient and vulnerable groups despite prominent state-related changes in both groups. Because sleep deprivation results in a significant elevation of whole brain signal amplitude, the aforesaid signal changes and group contrasts may be masked in analyses omitting their regression, suggesting possible value in regressing whole brain signal in certain experimental contexts.

Co-activated yet disconnected-Neural correlates of eye closures when trying to stay awake.

Spontaneous eye-closures that herald sleep onset become more frequent when we are sleep deprived. Although these are typically associated with decreased responsiveness to external stimuli, it is less clear what occurs in the brain at these transitions to drowsiness and light sleep. To investigate this, task-free fMRI of sleep-deprived participants was acquired. BOLD activity associated with periods of spontaneously occurring eye closures were marked and analyzed. We observed concurrent and extensive hypnagogic co-activation of the extrastriate visual, auditory, and somatosensory cortices as well as the default mode network, consistent with internal sensory activity without external stimulation. Co-activation of fronto-parietal areas known to mediate attentional control could correspond with participants resisting sleep or additional engagement of mental imagery. This constellation of signal changes differed from those elicited by cued eye closures of similar duration and distribution in the same, rested participants. They also differ from signal changes associated with mind-wandering and consolidated light sleep. Concurrent with the observed event-related changes, eye closures elicited additional reduction in functional connectivity within nodes of the DMN and DAN, superposed on already reduced connectivity associated with sleep deprivation. There was concurrent deactivation of the thalamus during eye-closure during the sleep-deprived state but almost similar changes occurred in the well-rested state that may also be relevant. These findings highlight the dynamic shifts in brain activity and connectivity at border between wakefulness and sleep.

NeuroBlu, an electronic health record (EHR) trusted research environment (TRE) to support mental healthcare analytics with real-world data.

PURPOSE: NeuroBlu is a real-world data (RWD) repository that contains deidentified electronic health record (EHR) data from US mental healthcare providers operating the MindLinc EHR system. NeuroBlu enables users to perform statistical analysis through a secure web-based interface. Structured data are available for sociodemographic characteristics, mental health service contacts, hospital admissions, International Classification of Diseases ICD-9/ICD-10 diagnosis, prescribed medications, family history of mental disorders, Clinical Global Impression-Severity and Improvement (CGI-S/CGI-I) and Global Assessment of Functioning (GAF). To further enhance the data set, natural language processing (NLP) tools have been applied to obtain mental state examination (MSE) and social/environmental data. This paper describes the development and implementation of NeuroBlu, the procedures to safeguard data integrity and security and how the data set supports the generation of real-world evidence (RWE) in mental health. PARTICIPANTS: As of 31 July 2021, 562 940 individuals (48.9% men) were present in the data set with a mean age of 33.4 years (SD: 18.4 years). The most frequently recorded diagnoses were substance use disorders (1 52 790 patients), major depressive disorder (1 29 120 patients) and anxiety disorders (1 03 923 patients). The median duration of follow-up was 7 months (IQR: 1.3 to 24.4 months). FINDINGS TO DATE: The data set has supported epidemiological studies demonstrating increased risk of psychiatric hospitalisation and reduced antidepressant treatment effectiveness among people with comorbid substance use disorders. It has also been used to develop data visualisation tools to support clinical decision-making, evaluate comparative effectiveness of medications, derive models to predict treatment response and develop NLP applications to obtain clinical information from unstructured EHR data. FUTURE PLANS: The NeuroBlu data set will be further analysed to better understand factors related to poor clinical outcome, treatment responsiveness and the development of predictive analytic tools that may be incorporated into the source EHR system to support real-time clinical decision-making in the delivery of mental healthcare services.

Cortical thinning and sleep slow wave activity reductions mediate age-related improvements in cognition during mid-late adolescence.

STUDY OBJECTIVES: Gains in cognitive test performance that occur during adolescence are associated with brain maturation. Cortical thinning and reduced sleep slow wave activity (SWA) are markers of such developmental changes. Here we investigate whether they mediate age-related improvements in cognition. METHODS: 109 adolescents aged 15-19 years (49 males) underwent magnetic resonance imaging, polysomnography (PSG), and a battery of cognitive tasks within a 2-month time window. Cognitive tasks assessed nonverbal intelligence, sustained attention, speed of processing and working memory and executive function. To minimize the effect of sleep history on SWA and cognitive performance, PSG and test batteries were administered only after at least 8 nights of 9-h time-in-bed (TIB) sleep opportunity. RESULTS: Age-related improvements in speed of processing (r = 0.33, p = 0.001) and nonverbal intelligence (r = 0.24, p = 0.01) domains were observed. These cognitive changes were associated with reduced cortical thickness, particularly in bilateral temporoparietal regions (rs = -0.21 to -0.45, ps < 0.05), as well as SWA (r = -0.35, p < 0.001). Serial mediation models found that ROIs in the middle/superior temporal cortices, together with SWA mediated the age-related improvement observed on cognition. CONCLUSIONS: During adolescence, age-related improvements in cognition are mediated by reductions in cortical thickness and sleep SWA.

Large-scale data from wearables reveal regional disparities in sleep patterns that persist across age and sex.

Prior reports on geographical differences in sleep duration have relied on samples collected at different time points with a variety of subjective instruments. Using sleep data from a total of 553,559 nights from 23,680 Fitbit users (aged 15-80y), we found objective evidence for regional disparities in sleep duration of 32-43 min between Oceanian and East Asian users on weekdays. This was primarily driven by later bedtimes in East Asians. Although users in all countries extended sleep on weekends, East Asians continued to sleep less than their Oceanian counterparts. Women generally slept more than men, and older users slept less than younger users. Reasons for shorter sleep duration in East Asians on both weekdays and weekends, across the lifespan and in both sexes remain to be investigated.

Multiple nights of partial sleep deprivation do not affect prospective remembering at long delays.

Prospective memory is defined as remembering to do something at a particular moment in the future and may be modulated by sleep. Here, we investigated whether multiple nights of partial sleep deprivation would affect the successful retrieval of intentions. Fifty-nine adolescents (mean age ± SD: 16.1 ± 0.6 years) were instructed to remember to press specific keys in response to the target words presented during a semantic categorization task in the future. Their memory was tested after five nights of either 5-h (sleep restriction group) or 9-h time-in-bed (control group). The average percentage of target words correctly responded to was small and did not significantly differ between the two groups (mean ± SEM for the sleep restriction group: 15.52 ± 6.61%; the control group: 23.33 ± 7.48%, p = 0.44). Thus, after the extended retention interval, prospective remembering was poor and did not appear to be affected by post-learning sleep restriction. These findings suggest a temporal boundary beyond which intentions fall below requisite levels of activation, potentially masking any benefits for retrieval conferred by sleep.

Sustained benefits of delaying school start time on adolescent sleep and well-being.

Study Objectives: To investigate the short- and longer-term impact of a 45-min delay in school start time on sleep and well-being of adolescents. Methods: The sample consisted of 375 students in grades 7-10 (mean age ± SD: 14.6 ± 1.15 years) from an all-girls' secondary school in Singapore that delayed its start time from 07:30 to 08:15. Self-reports of sleep timing, sleepiness, and well-being (depressive symptoms and mood) were obtained at baseline prior to the delay, and at approximately 1 and 9 months after the delay. Total sleep time (TST) was evaluated via actigraphy. Results: After 1 month, bedtimes on school nights were delayed by 9.0 min, while rise times were delayed by 31.6 min, resulting in an increase in time in bed (TIB) of 23.2 min. After 9 months, the increase in TIB was sustained, and TST increased by 10.0 min relative to baseline. Participants also reported lower levels of subjective sleepiness and improvement in well-being at both follow-ups. Notably, greater increase in sleep duration on school nights was associated with greater improvement in alertness and well-being. Conclusions: Delaying school start time can result in sustained benefits on sleep duration, daytime alertness, and mental well-being even within a culture where trading sleep for academic success is widespread.