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While the significance of obtaining restful sleep at night and maintaining daytime alertness is well recognized for human performance and overall well-being, substantial variations exist in the development of sleepiness during diurnal waking periods. Despite the established roles of the hypothalamus and striatum in sleep-wake regulation, the specific contributions of this neural circuit in regulating individual sleep homeostasis remain elusive. This study utilized resting-state functional magnetic resonance imaging (fMRI) and mathematical modeling to investigate the role of hypothalamus-striatum connectivity in subjective sleepiness variation in a cohort of 71 healthy adults under strictly controlled in-laboratory conditions. Mathematical modeling results revealed remarkable individual differences in subjective sleepiness accumulation patterns measured by the Karolinska Sleepiness Scale (KSS). Brain imaging data demonstrated that morning hypothalamic connectivity to the dorsal striatum significantly predicts the individual accumulation of subjective sleepiness from morning to evening, while no such correlation was observed for the hypothalamus-ventral striatum connectivity. These findings underscore the distinct roles of hypothalamic connectivity to the dorsal and ventral striatum in individual sleep homeostasis, suggesting that hypothalamus-dorsal striatum circuit may be a promising target for interventions mitigating excessive sleepiness and promoting alertness.

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.

Adult language learners show distinct abilities in acquiring a new language, yet the underlying neural mechanisms remain elusive. Previous studies suggested that resting-state brain connectome may contribute to individual differences in learning ability. Here, we recorded electroencephalography (EEG) in a large cohort of 106 healthy young adults (50 males) and examined the associations between resting-state alpha band (8–12 Hz) connectome and individual learning ability during novel word learning, a key component of new language acquisition. Behavioral data revealed robust individual differences in the performance of the novel word learning task, which correlated with their performance in the language aptitude test. EEG data showed that individual resting-state alpha band coherence between occipital and frontal regions positively correlated with differential word learning performance (p = 0.001). The significant positive correlations between resting-state occipito-frontal alpha connectome and differential world learning ability were replicated in an independent cohort of 35 healthy adults. These findings support the key role of occipito-frontal network in novel word learning and suggest that resting-state EEG connectome may be a reliable marker for individual ability during new language learning.

Gender plays an important role in various aspects of second language acquisition, including lexicon learning. Many studies have suggested that compared to males, females are less likely to experience boredom, one of the frequently experienced deactivating negative emotions that may impair language learning. However, the contribution of boredom to gender-related differences in lexicon learning remains unclear. To address this question, here we conducted two experiments with a large sample of over 1,000 college students to explore the relationships between gender differences in boredom and lexicon learning. In Experiment 1, a cohort of 527 participants (238 males) completed the trait and state boredom scales as well as a novel lexicon learning task without awareness of the testing process. In Experiment 2, an independent cohort of 506 participants (228 males) completed the same novel lexicon learning task with prior knowledge of the testing procedure. Results from both experiments consistently showed significant differences between female and male participants in the rate of forgetting words and the state boredom scores, with female participants performing better than male participants. Furthermore, differences in state boredom scores partially explained differences in the rate of forgetting words between female and male participants. These findings demonstrate a novel contribution of state boredom to gender differences in lexicon learning, which provides new insights into better language-learning ability in females.

Human risk tolerance is highly idiosyncratic and individuals often show distinctive preferences when faced with similar risky situations. However, the neural underpinnings of individual differences in risk-taking remain unclear. Here we combined structural and perfusion MRI and examined the associations between brain anatomy and individual risk-taking behavior/risk tolerance in a sample of 115 healthy participants during the Balloon Analogue Risk Task, a well-established sequential risky decision paradigm. Both whole brain and region-of-interest analyses showed that the left cerebellum gray matter volume (GMV) has a strong association with individual risk-taking behavior and risk tolerance, outperforming the previously reported associations with the amygdala and right posterior parietal cortex (PPC) GMV. Left cerebellum GMV also accounted for risk tolerance and risk-taking behavior changes with aging. However, regional cerebral blood flow (CBF) provided no additional predictive power. These findings suggest a novel cerebellar anatomical contribution to individual differences in risk tolerance. Further studies are necessary to elucidate the underestimated important role of cerebellum in risk-taking.

Fatigue is a highly prevalent and debilitating non-motor symptom in Parkinson’s disease (PD), yet its’ neural mechanisms remain poorly understood. Here we combined arterial spin labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) with a sustained mental workload paradigm to examine the neural correlates of fatigue and time-on-task effects in PD patients. Twenty-one PD patients were scanned at rest and during continuous performance of a 20-min psychomotor vigilance test (PVT). Time-on-task effects were measured by the reaction time changes during the PVT and by self-reported fatigue ratings before and after the PVT. PD subjects demonstrated significant time-on-task effects, including progressively slower reaction time on the PVT and increased post-PVT fatigue ratings compared to pre-PVT. Higher levels of general fatigue were associated with larger increases in mental fatigue ratings after the PVT. ASL imaging data showed increased CBF in the right middle frontal gyrus (MFG), bilateral occipital cortex, and right cerebellum during the PVT compared to rest, and decreased CBF in the right MFG at post-task rest compared to pre-task rest. The magnitude of regional CBF changes in the right MFG and right inferior parietal lobe correlated with subjective fatigue rating increases after the PVT task. These results demonstrate the utility of continuous PVT paradigm for future studies of fatigue and cognitive fatigability in patients, and support the key role of the fronto-parietal attention network in mediating fatigue in PD.

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.

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. [ABSTRACT FROM AUTHOR]