The common and distinct brain basis associated with adult and adolescent risk-taking behavior: Evidence from the neuroimaging meta-analysis.

Risk-taking is a common, complex, and multidimensional behavior construct that has significant implications for human health and well-being. Previous research has identified the neural mechanisms underlying risk-taking behavior in both adolescents and adults, yet the differences between adolescents' and adults' risk-taking in the brain remain elusive. This study firstly employs a comprehensive meta-analysis approach that includes 73 adult and 20 adolescent whole-brain experiments, incorporating observations from 1986 adults and 789 adolescents obtained from online databases, including Web of Science, PubMed, ScienceDirect, Google Scholar and Neurosynth. It then combines functional decoding methods to identify common and distinct brain regions and corresponding psychological processes associated with risk-taking behavior in these two cohorts. The results indicated that the neural bases underlying risk-taking behavior in both age groups are situated within the cognitive control, reward, and sensory networks. Subsequent contrast analysis revealed that adolescents and adults risk-taking engaged frontal pole within the fronto-parietal control network (FPN), but the former recruited more ventrolateral area and the latter recruited more dorsolateral area. Moreover, adolescents' risk-taking evoked brain area activity within the ventral attention network (VAN) and the default mode network (DMN) compared with adults, consistent with the functional decoding analyses. These findings provide new insights into the similarities and disparities of risk-taking neural substrates underlying different age cohorts, supporting future neuroimaging research on the dynamic changes of risk-taking.

Sleep-stage-dependent alterations in cerebral oxygen metabolism quantified by magnetic resonance.

A key function of sleep is to provide a regular period of reduced brain metabolism, which is critical for maintenance of healthy brain function. The purpose of this work was to quantify the sleep-stage-dependent changes in brain energetics in terms of cerebral metabolic rate of oxygen (CMRO2 ) as a function of sleep stage using quantitative magnetic resonance imaging (MRI) with concurrent electroencephalography (EEG) during sleep in the scanner. Twenty-two young and older subjects with regular sleep hygiene and Pittsburgh Sleep Quality Index (PSQI) in the normal range were recruited for the study. Cerebral blood flow (CBF) and venous oxygen saturation (SvO2 ) were obtained simultaneously at 3 Tesla field strength and 2.7-s temporal resolution during an 80-min time series using OxFlow, an in-house developed imaging sequence. The method yields whole-brain CMRO2 in absolute physiologic units via Fick's Principle. Nineteen subjects yielded evaluable data free of subject motion artifacts. Among these subjects, 10 achieved slow-wave (N3) sleep, 16 achieved N2 sleep, and 19 achieved N1 sleep while undergoing the MRI protocol during scanning. Mean CMRO2 was 98 ± 7(µmol min-1 )/100 g awake, declining progressively toward deepest sleep stage: 94 ± 10.8 (N1), 91 ± 11.4 (N2), and 76 ± 9.0 µmol min-1 /100 g (N3), with each level differing significantly from the wake state. The technology described is able to quantify cerebral oxygen metabolism in absolute physiologic units along with non-REM sleep stage, indicating brain oxygen consumption to be closely associated with depth of sleep, with deeper sleep stages exhibiting progressively lower CMRO2 levels.

Health involvement modulates physician preference in the brain during online health consultation.

In traditional offline health-seeking behavior, patients consistently exhibit a preference for similar types of physicians due to limited access to physicians' information. Nevertheless, with the advent of online health consultation platforms offering comprehensive physicians' information for patients, raises the question: do patients continue to exhibit uniform preference for physicians? To address this issue, we first employed a behavioral experiment to discern patients' preferences for different types of physicians' information under different health involvement, and then conducted a functional magnetic resonance imaging (fMRI) experiment to furnish neural/physiological evidence. The results showed that health involvement modulates patients' preferences, when health involvement was low, patients had diverse preferences for physicians, that is, different types of physicians' information could individually impact patients' choice and could serve as substitutes for each other. When health involvement was high, patients' preference for physicians were uniform, highlighting that the collective influence of different types of physicians' information on patients' choice behavior. From the neural level, an explanation for the results was that the ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) brain regions, two key brain regions reflecting individual cognitive resource allocation, had different activation levels under different health involvement, indicating that patients allocated different cognitive resources.

Sleep deprivation attenuates neural responses to outcomes from risky decision-making.

Sleep loss impacts a broad range of brain and cognitive functions. However, how sleep deprivation affects risky decision-making remains inconclusive. This study used functional MRI to examine the impact of one night of total sleep deprivation (TSD) on risky decision-making behavior and the underlying brain responses in healthy adults. In this study, we analyzed data from N = 56 participants in a strictly controlled 5-day and 4-night in-laboratory study using a modified Balloon Analogue Risk Task. Participants completed two scan sessions in counter-balanced order, including one scan during rested wakefulness (RW) and another scan after one night of TSD. Results showed no differences in participants' risk-taking propensity and risk-induced activation between RW and TSD. However, participants showed significantly reduced neural activity in the anterior cingulate cortex and bilateral insula for loss outcomes, and in bilateral putamen for win outcomes during TSD compared with RW. Moreover, risk-induced activation in the insula negatively correlated with participants' risk-taking propensity during RW, while no such correlations were observed after TSD. These findings suggest that sleep loss may impact risky decision-making by attenuating neural responses to decision outcomes and impairing brain-behavior associations.

Sleep Architecture and Sleep EEG Alterations are Associated with Impaired Cognition Under Sleep Restriction.

Purpose: Many studies have investigated the cognitive, emotional, and other impairments caused by sleep restriction. However, few studies have explored the relationship between cognitive performance and changes in sleep structure and electroencephalography (EEG) during sleep. The present study aimed to examine whether changes in sleep structure and EEG can account for cognitive impairment caused by sleep restriction. Patients and Methods: Sixteen young adults spent five consecutive nights (adaptation 9h, baseline 8h, 1st restriction 6h, 2nd restriction 6h, and recovery 10h) in a sleep laboratory, with polysomnography recordings taken during sleep. Throughout waking periods in each condition, participants completed the psychomotor vigilance test (PVT), which measures vigilant attention, and the Go/No-Go task, which measures inhibition control. Results: The results showed that sleep restriction significantly decreased the proportion of N1 and N2 sleep, increased the proportion of N3 sleep, and reduced the time spent awake after sleep onset (WASO) and sleep onset latency. Poorer performance on the PVT and Go/No Go task was associated with longer WASO, a larger proportion of N3 sleep, and a smaller proportion of N2 sleep. Additionally, the power spectral density of delta waves significantly increased after sleep restriction, and this increase predicted a decrease in vigilance and inhibition control the next day. Conclusion: These findings suggest that sleep architecture and EEG signatures may partially explain cognitive impairment caused by sleep restriction.

Vigilant attention mediates the association between resting EEG alpha oscillations and word learning ability.

Individuals exhibit considerable variability in their capacity to learn and retain new information, including novel vocabulary. Prior research has established the importance of vigilance and electroencephalogram (EEG) alpha rhythm in the learning process. However, the interplay between vigilant attention, EEG alpha oscillations, and an individual's word learning ability (WLA) remains elusive. To address this knowledge gap, here we conducted two experiments with a total of 140 young and middle-aged adults who underwent resting EEG recordings prior to completing a paired-associate word learning task and a psychomotor vigilance test (PVT). The results of both experiments consistently revealed significant positive correlations between WLA and resting EEG alpha oscillations in the occipital and frontal regions. Furthermore, the association between resting EEG alpha oscillations and WLA was mediated by vigilant attention, as measured by the PVT. These findings provide compelling evidence supporting the crucial role of vigilant attention in linking EEG alpha oscillations to an individual's learning ability.

Increased posterior cingulate cortex blood flow in cancer-related fatigue.

Fatigue is a common symptom associated with cancer treatments. Brain mechanisms underlying cancer-related fatigue (CRF) and its progression following therapy are poorly understood. Previous studies have suggested a role of the default mode network (DMN) in fatigue. In this study we used arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) and compared resting cerebral blood flow (CBF) differences in the posterior cingulate cortex (PCC), a core hub of the DMN, between 16 patients treated with radiation therapy (RAT) for prostate (9 males) or breast (7 females) cancer and 18 healthy controls (HC). Resting CBF in patients was also measured immediately after the performance of a fatiguing 20-min psychomotor vigilance task (PVT). Twelve of 16 cancer patients were further followed between 3 and 7 months after completion of the RAT (post-RAT). Patients reported elevated fatigue on RAT in comparison to post-RAT, but no change in sleepiness, suggesting that the underlying neural mechanisms of CRF progression are distinct from those regulating sleep drive progression. Compared to HC, patients showed significantly increased resting CBF in the PCC and the elevated PCC CBF persisted during the follow up visit. Post-PVT, but not pre-PVT, resting CBF changes in the PCC correlated with fatigue changes after therapy in patients with CRF, suggesting that PCC CBF following a fatiguing cognitive task may be a biomarker for CRF recovery.

Antidepressant effects of acute sleep deprivation are reduced in highly controlled environments.

BACKGROUND: Numerous studies summarized in a recent meta-analysis have shown sleep deprivation rapidly improves depressive symptoms in approximately 50 % of individuals with major depressive disorder (MDD), however those studies were typically conducted in clinical settings. Here we investigated the effects of sleep deprivation utilizing a highly controlled experimental approach. METHODS: 36 antidepressant-free individuals with MDD and 10 healthy controls (HC) completed a 5 day/4-night protocol consisting of adaptation, baseline, total sleep deprivation (TSD), and recovery phases. Light was kept consistently dim (≤50 lx), meals were regulated, and activity was restricted. In-the-moment mood was assessed using a modified Hamilton Rating Scale for Depression (HRSD) at screening and each morning following the experimental nights. RESULTS: Day of study had a significant effect on mood in both groups. Post-hoc analyses revealed that significant effects were attributed to mood improvement in the MDD group following study initiation prior to beginning TSD, and in the HC group following recovery sleep, but were not due to mood improvement in the MDD group during TSD. No further improvement in mood occurred during 36 h of TSD. LIMITATIONS: Strict eligibility requirements may limit generalizability. The requirement to be medication free may have biased toward a less severely depressed sample. CONCLUSIONS: Results revealed that individuals with moderate MDD can experience a significant reduction in depressive symptoms upon entering a highly controlled laboratory environment. Environmental effects on mood can be substantial and need to be considered.

Functional connectomics in depression: insights into therapies.

Depression is a common mental disorder characterized by heterogeneous cognitive and behavioral symptoms. The emerging research paradigm of functional connectomics has provided a quantitative theoretical framework and analytic tools for parsing variations in the organization and function of brain networks in depression. In this review, we first discuss recent progress in depression-associated functional connectome variations. We then discuss treatment-specific brain network outcomes in depression and propose a hypothetical model highlighting the advantages and uniqueness of each treatment in relation to the modulation of specific brain network connectivity and symptoms of depression. Finally, we look to the future promise of combining multiple treatment types in clinical practice, using multisite datasets and multimodal neuroimaging approaches, and identifying biological depression subtypes.

Enhanced amygdala-cingulate connectivity associates with better mood in both healthy and depressive individuals after sleep deprivation.

Sleep loss robustly disrupts mood and emotion regulation in healthy individuals but can have a transient antidepressant effect in a subset of patients with depression. The neural mechanisms underlying this paradoxical effect remain unclear. Previous studies suggest that the amygdala and dorsal nexus (DN) play key roles in depressive mood regulation. Here, we used functional MRI to examine associations between amygdala- and DN-related resting-state connectivity alterations and mood changes after one night of total sleep deprivation (TSD) in both healthy adults and patients with major depressive disorder using strictly controlled in-laboratory studies. Behavioral data showed that TSD increased negative mood in healthy participants but reduced depressive symptoms in 43% of patients. Imaging data showed that TSD enhanced both amygdala- and DN-related connectivity in healthy participants. Moreover, enhanced amygdala connectivity to the anterior cingulate cortex (ACC) after TSD associated with better mood in healthy participants and antidepressant effects in depressed patients. These findings support the key role of the amygdala-cingulate circuit in mood regulation in both healthy and depressed populations and suggest that rapid antidepressant treatment may target the enhancement of amygdala-ACC connectivity.

Test-Retest Reliability of Resting Brain Small-World Network Properties across Different Data Processing and Modeling Strategies.

Resting-state functional magnetic resonance imaging (fMRI) with graph theoretical modeling has been increasingly applied for assessing whole brain network topological organization, yet its reproducibility remains controversial. In this study, we acquired three repeated resting-state fMRI scans from 16 healthy controls during a strictly controlled in-laboratory study and examined the test-retest reliability of seven global and three nodal brain network metrics using different data processing and modeling strategies. Among the global network metrics, the characteristic path length exhibited the highest reliability, whereas the network small-worldness performed the poorest. Nodal efficiency was the most reliable nodal metric, whereas betweenness centrality showed the lowest reliability. Weighted global network metrics provided better reliability than binary metrics, and reliability from the AAL90 atlas outweighed those from the Power264 parcellation. Although global signal regression had no consistent effects on the reliability of global network metrics, it slightly impaired the reliability of nodal metrics. These findings provide important implications for the future utility of graph theoretical modeling in brain network analyses.

Social Connection and Lifestyle Factors Associated With Happiness in Urban Older Adults in China: A Cross-Sectional Study With a Community Sample.

The current cross-sectional study aimed to investigate social connection and lifestyle factors associated with happiness in urban older adults in mainland China. A total of 709 community-dwelling older adults aged 60 to 99 years completed a comprehensive survey covering demographics, happiness, cognition, lifestyle, sleep, nutrition, and social connections. Samples were divided by age into two groups for analysis: young-old (aged 60 to 69 years) and old-old (aged 70 to 99 years). Social connection factors, including relationships with friends and spouse and use of social media applications, were important predictors for happiness in people in their 60s. Lifestyle factors, including nutritional status and extent of physical activity, were associated with happiness in old-old adults. Sleep quality predicted happiness for both age groups. Living with children and happiness were not significant for either age group. Results suggest that social connection and lifestyle are important factors in promoting happy and healthy successful aging in urban older adults in China. [Research in Gerontological Nursing, 16(3), 147-160.].

Culturally tailored group Qigong exercise in older Chinese immigrants: A feasibility study.

BACKGROUND: Culturally tailored group exercise bridges health disparities among new immigrants, particularly older adults. We designed a Chinese Qigong (Baduanjin) exercise intervention testing the feasibility and acceptability among older Chinese at a senior daycare center in Philadelphia, PA, US. METHODS: 10-week Qigong group in-person exercise was delivered 5 days a week, using a 12-minute video tutorial under trained research assistants' guidance. Daily attendance and attrition was recorded. Participants completed baseline self-report assessments on physical and mental health, and two computerized cognitive tests, the psychomotor vigilance test and a memory test. RESULTS: 53 older adults participated (mean age: 78, female: 88.7%). Average daily attendance was 65.28%. Stratification analysis on age groups <80 and ≥80 shows no significant differences on key variables. CONCLUSIONS: Recruitment for Baduanjin Qigong exercise was feasible in senior daycare centers, and older adults could easily learn and safely follow exercise movements. Preliminarily findings call for further research.

Dynamic brain responses to Russian word acquisition among Chinese adult learners: An event-related potential study.

Human learners are capable to acquire foreign language vocabulary at an impressive speed even in adulthood. Previous studies have examined the neural mechanisms underlying rapid acquisition of Latin-alphabet vocabulary and revealed dynamic changes in several event-related potential (ERP) components during novel word learning. However, scant attention has been paid to the acquisition of Russian words. The present study used ERP and examined dynamic brain responses to rapid Russian word acquisition in 53 native Chinese speakers with no prior knowledge of Russian language. Behavioral data showed robust individual differences in Russian word acquisition, with most participants being able to rapidly learn a subset of novel Russian words in a few exposures. ERP results revealed significant learning effects in the P200, N400, and P600 amplitudes. Moreover, P600 amplitude changes predicted participants' word acquisition after learning. These findings demonstrated dynamic brain responses to rapid Russian word learning and suggested that the P600 component may serve as a bio-marker for individual learning ability in Russian word acquisition.

Superior sagittal sinus flow as a proxy for tracking global cerebral blood flow dynamics during wakefulness and sleep.

Sleep, a state of reduced consciousness, affects brain oxygen metabolism and lowers cerebral metabolic rate of oxygen (CMRO2). Previously, we quantified CMRO2 during sleep via Fick's Principle, with a single-band MRI sequence measuring both hemoglobin O2 saturation (SvO2) and superior sagittal sinus (SSS) blood flow, which was upscaled to obtain total cerebral blood flow (tCBF). The procedure involves a brief initial calibration scan to determine the upscaling factor (fc), assumed state-invariant. Here, we used a dual-band sequence to simultaneously provide SvO2 in SSS and tCBF in the neck every 16 seconds, allowing quantification of fc dynamically. Ten healthy subjects were scanned by MRI with simultaneous EEG for 80 minutes, yielding 300 temporal image frames per subject. Four volunteers achieved slow-wave sleep (SWS), as evidenced by increased δ-wave activity (per American Academy of Sleep Medicine criteria). SWS was maintained for 13.5 ± 7.0 minutes, with CMRO2 28.6 ± 5.5% lower than pre-sleep wakefulness. Importantly, there was negligible bias between tCBF obtained by upscaling SSS-blood flow, and tCBF measured directly in the inflowing arteries of the neck (intra-class correlation 0.95 ± 0.04, averaged across all subjects), showing that the single-band approach is a valid substitute for quantifying tCBF, simplifying image data collection and analysis without sacrificing accuracy.

Mental Fatigue Is Associated with Subjective Cognitive Decline among Older Adults.

Both Subjective Cognitive Decline (SCD) and mental fatigue are becoming increasingly prevalent as global demographics shifts indicate our aging populations. SCD is a reversible precursor for Alzheimer's disease, and early identification is important for effective intervention strategies. We aim to investigate the association between mental fatigue-as well as other factors-and SCD. A total of 707 old adults (aged from 60 to 99) from Shanghai, China, participated in this study and completed self-reported instruments covering their cognitive and mental status as well as demographic information. Mental fatigue status was assessed by using four items derived from the functional impairment syndrome of the Old Adult Self Report (OASR). SCD was assessed by using the Memory/Cognition syndrome of OASR. A total of 681 old adults were included in the current study. The means of SCD significantly differed between each group of factors (age, gender, and mental fatigue). The general linear regression models showed that SCD increased with age, females scored higher than males, and SCD was positively associated with mental fatigue factors including difficulty getting things done, poor task performance, sleeping more, and a lack of energy among old adults. The study also found that SCD is negatively associated with the high-income group among young-old (aged from 60 to 75) males and associated with good marital/living status with the companion of spouses/partners among young-old females. These results suggest that gender, income level, marital/living status, and mental fatigue are crucial factors in preventing SCD among old adults and are pivotal in developing early intervention strategies to preserve the mental health of an increasingly aging population.

Lifetime air pollution exposure, cognitive deficits, and brain imaging outcomes: A systematic review.

As the amount of air pollution and human exposure has increased, the effects on human health have become an important public health issue. A field of growing interest is how air pollution exposure affects brain structure and function underlying cognitive deficits and if structural and connectivity changes mediate the relationship between the two. We conducted a systematic review to examine the literature on air pollution, brain structure and connectivity, and cognition studies. Eleven studies matched our inclusion criteria and were included in the qualitative analysis. Results suggest significant associations between air pollution and decreased volumes of specific brain structures, cortical thickness and surface area such as in the prefrontal cortex and temporal lobe, as well as the weakening of functional connectivity pathways, largely the Default Mode (DMN) and Frontal Parietal (FPN) networks, as detected by fMRI. Associations between air pollution and cognitive outcomes were found in most of the studies (n = 9), though some studies showed stronger associations than others. For children & adolescents, these deficiencies largely involved heavy reasoning, problem solving, and logic. For young and middle-aged adults, the associations were mostly seen for executive function and visuospatial cognitive domains. To our knowledge, this is the first systematic review to consolidate findings on the associations among air pollution, brain structure, and cognitive function. In the future, it will be important to conduct further longitudinal studies that follow children who have been exposed at a young age and examine associations with brain structure and cognition throughout adulthood.

Increasing diversity in connectomics with the Chinese Human Connectome Project.

Cultural differences and biological diversity play important roles in shaping human brain structure and function. To date, most large-scale multimodal neuroimaging datasets have been obtained primarily from people living in Western countries, omitting the crucial contrast with populations living in other regions. The Chinese Human Connectome Project (CHCP) aims to address these resource and knowledge gaps by acquiring imaging, genetic and behavioral data from a large sample of participants living in an Eastern culture. The CHCP collected multimodal neuroimaging data from healthy Chinese adults using a protocol comparable to that of the Human Connectome Project. Comparisons between the CHCP and Human Connectome Project revealed both commonalities and distinctions in brain structure, function and connectivity. The corresponding large-scale brain parcellations were highly reproducible across the two datasets, with the language processing task showing the largest differences. The CHCP dataset is publicly available in an effort to facilitate transcultural and cross-ethnic brain-mind studies.