Examining the role of dopamine in methylphenidate's effects on resting brain function.

The amplitude of low-frequency fluctuations (ALFF) and global functional connectivity density (gFCD) are fMRI (Functional MRI) metrics widely used to assess resting brain function. However, their differential sensitivity to stimulant-induced dopamine (DA) increases, including the rate of DA rise and the relationship between them, have not been investigated. Here we used, simultaneous PET-fMRI to examine the association between dynamic changes in striatal DA and brain activity as assessed by ALFF and gFCD, following placebo, intravenous (IV), or oral methylphenidate (MP) administration, using a within-subject double-blind placebo-controlled design. In putamen, MP significantly reduced D2/3 receptor availability and strongly reduced ALFF and increased gFCD in the brain for IV-MP (Cohen's d > 1.6) but less so for oral-MP (Cohen's d < 0.6). Enhanced gFCD was associated with both the level and the rate of striatal DA increases, whereas decreased ALFF was only associated with the level of DA increases. These findings suggest distinct representations of neurovascular activation with ALFF and gFCD by stimulant-induced DA increases with differential sensitivity to the rate and the level of DA increases. We also observed an inverse association between gFCD and ALFF that was markedly enhanced during IV-MP, which could reflect an increased contribution from MP's vasoactive properties.

Seasonality in regional brain glucose metabolism.

BACKGROUND: Daylength and the rates of changes in daylength have been associated with seasonal fluctuations in psychiatric symptoms and in cognition and mood in healthy adults. However, variations in human brain glucose metabolism in concordance with seasonal changes remain under explored. METHODS: In this cross-sectional study, we examined seasonal effects on brain glucose metabolism, which we measured using 18F-fluorodeoxyglucose-PET in 97 healthy participants. To maximize the sensitivity of regional effects, we computed relative metabolic measures by normalizing the regional measures to white matter metabolism. Additionally, we explored the role of rest-activity rhythms/sleep-wake activity measured with actigraphy in the seasonal variations of regional brain metabolic activity. RESULTS: We found that seasonal variations of cerebral glucose metabolism differed across brain regions. Glucose metabolism in prefrontal regions increased with longer daylength and with greater day-to-day increases in daylength. The cuneus and olfactory bulb had the maximum and minimum metabolic values around the summer and winter solstice respectively (positively associated with daylength), whereas the temporal lobe, brainstem, and postcentral cortex showed maximum and minimum metabolic values around the spring and autumn equinoxes, respectively (positively associated with faster daylength gain). Longer daylength was associated with greater amplitude and robustness of diurnal activity rhythms suggesting circadian involvement. CONCLUSIONS: The current findings advance our knowledge of seasonal patterns in a key indicator of brain function relevant for mood and cognition. These data could inform treatment interventions for psychiatric symptoms that peak at specific times of the year.

Preterm birth associated alterations in brain structure, cognitive functioning and behavior in children from the ABCD dataset.

BACKGROUND: Preterm birth is a global health problem and associated with increased risk of long-term developmental impairments, but findings on the adverse outcomes of prematurity have been inconsistent. METHODS: Data were obtained from the baseline session of the ongoing longitudinal Adolescent Brain and Cognitive Development (ABCD) Study. We identified 1706 preterm children and 1865 matched individuals as Control group and compared brain structure (MRI data), cognitive function and mental health symptoms. RESULTS: Results showed that preterm children had higher psychopathological risk and lower cognitive function scores compared to controls. Structural MRI analysis indicated that preterm children had higher cortical thickness in the medial orbitofrontal cortex, parahippocampal gyrus, temporal and occipital gyrus; smaller volumes in the temporal and parietal gyrus, cerebellum, insula and thalamus; and smaller fiber tract volumes in the fornix and parahippocampal-cingulum bundle. Partial correlation analyses showed that gestational age and birth weight were associated with ADHD symptoms, picvocab, flanker, reading, fluid cognition composite, crystallized cognition composite and total cognition composite scores, and measures of brain structure in regions involved with emotional regulation, attention and cognition. CONCLUSIONS: These findings suggest a complex interplay between psychopathological risk and cognitive deficits in preterm children that is associated with changes in regional brain volumes, cortical thickness, and structural connectivity among cortical and limbic brain regions critical for cognition and emotional well-being.

Effects of family income on brain functional connectivity in US children: associations with cognition.

Higher family income (FI) is associated with larger cortical gray matter volume and improved cognitive performance in children. However, little is known about the effects of FI on brain functional and structural connectivity. This cross-sectional study investigates the effects of FI on brain connectivity and cognitive performance in 9- to 11-years old children (n = 8739) from the Adolescent Brain Cognitive Development (ABCD) study. Lower FI was associated with decreased global functional connectivity density (gFCD) in the default-mode network (DMN), inferior and superior parietal cortices and in posterior cerebellum, and increased gFCD in motor, auditory, and extrastriate visual areas, and in subcortical regions both for girls and boys. Findings demonstrated high reproducibility in Discovery and Reproducibility samples. Cognitive performance partially mediated the association between FI and DMN connectivity, whereas DMN connectivity did not mediate the association between FI and cognitive performance. In contrast, there was no significant association between FI and structural connectivity. Findings suggest that poor cognitive performance, which likely reflects multiple factors (genetic, nutritional, the level and quality of parental interactions, and educational exposure [1]), contributes to reduced DMN functional connectivity in children from low-income families. Follow-up studies are needed to help clarify if this leads to reductions in structural connectivity as these children age.

Activation of brain arousal networks coincident with eye blinks during resting state.

Eye-blinking has been implicated in arousal and attention. Here we test the hypothesis that blinking-moments represent arousal surges associated with activation of the ascending arousal network (AAN) and its thalamic projections. For this purpose, we explored the temporal relationship between eye-blinks and fMRI BOLD activity in AAN and thalamic nuclei, as well as whole brain cluster corrected activations during eyes-open, resting-state fMRI scanning. We show that BOLD activations in the AAN nuclei peaked prior to the eye blinks and in thalamic nuclei peaked prior to and during the blink, consistent with the role of eye blinking in arousal surges. Additionally, we showed visual cortex peak activation prior to the eye blinks, providing further evidence of the visual cortex's role in arousal, and document cerebellar peak activation post eye blinks, which might reflect downstream engagement from arousal surges.

Associations among body mass index, working memory performance, gray matter volume, and brain activation in healthy children.

To investigate the neural mechanisms underlying the association between poorer working memory performance and higher body mass index (BMI) in children. We employed structural-(sMRI) and functional magnetic resonance imaging (fMRI) with a 2-back working memory task to examine brain abnormalities and their associations with BMI and working memory performance in 232 children with overweight/obesity (OW/OB) and 244 normal weight children (NW) from the Adolescent Brain Cognitive Development dataset. OW/OB had lower working memory accuracy, which was associated with higher BMI. They showed smaller gray matter (GM) volumes in the left superior frontal gyrus (SFG_L), dorsal anterior cingulate cortex, medial orbital frontal cortex, and medial superior frontal gyrus, which were associated with lower working memory accuracy. During the working memory task, OW/OB relative to NW showed weaker activation in the left superior temporal pole, amygdala, insula, and bilateral caudate. In addition, caudate activation mediated the relationship between higher BMI and lower working memory accuracy. Higher BMI is associated with smaller GM volumes and weaker brain activation in regions involved with working memory. Task-related caudate dysfunction may account for lower working memory accuracy in children with higher BMI.

Obesity is associated with decreased gray matter volume in children: a longitudinal study.

Childhood obesity has become a global health problem. Previous studies showed that childhood obesity is associated with brain structural differences relative to controls. However, few studies have been performed with longitudinal evaluations of brain structural developmental trajectories in childhood obesity. We employed voxel-based morphometry (VBM) analysis to assess gray matter (GM) volume at baseline and 2-year follow-up in 258 obese children (OB) and 265 normal weight children (NW), recruited as part of the National Institutes of Health Adolescent Brain and Cognitive Development study. Significant group × time effects on GM volume were observed in the prefrontal lobe, thalamus, right precentral gyrus, caudate, and parahippocampal gyrus/amygdala. OB compared with NW had greater reductions in GM volume in these regions over the 2-year period. Body mass index (BMI) was negatively correlated with GM volume in prefrontal lobe and with matrix reasoning ability at baseline and 2-year follow-up. In OB, Picture Test was positively correlated with GM volume in the left orbital region of the inferior frontal gyrus (OFCinf_L) at baseline and was negatively correlated with reductions in OFCinf_L volume (2-year follow-up vs. baseline). These findings indicate that childhood obesity is associated with GM volume reduction in regions involved with reward evaluation, executive function, and cognitive performance.

Habenular connectivity predict weight loss and negative emotional-related eating behavior after laparoscopic sleeve gastrectomy.

Habenular (Hb) processes negative emotions that may drive compulsive food-intake. Its functional changes were reported following laparoscopic-sleeve-gastrectomy (LSG). However, structural connectivity (SC) of Hb-homeostatic/hedonic circuits after LSG remains unclear. We selected regions implicated in homeostatic/hedonic regulation that have anatomical connections with Hb as regions-of-interest (ROIs), and used diffusion-tensor-imaging with probabilistic tractography to calculate SC between Hb and these ROIs in 30 obese participants before LSG (PreLSG) and at 12-month post-LSG (PostLSG12) and 30 normal-weight controls. Three-factor-eating-questionnaire (TFEQ) and Dutch-eating-behavior-questionnaire (DEBQ) were used to assess eating behaviors. LSG significantly decreased weight, negative emotion, and improved self-reported eating behavior. LSG increased SC between the Hb and homeostatic/hedonic regions including hypothalamus (Hy), bilateral superior frontal gyri (SFG), left amygdala (AMY), and orbitofrontal cortex (OFC). TFEQ-hunger negatively correlated with SC of Hb-Hy at PostLSG12; and increased SC of Hb-Hy correlated with reduced depression and DEBQ-external eating. TFEQ-disinhibition negatively correlated with SC of Hb-bilateral SFG at PreLSG. Increased SC of Hb-left AMY correlated with reduced DEBQ-emotional eating. Higher percentage of total weight-loss negatively correlated with SC of Hb-left OFC at PreLSG. Enhanced SC of Hb-homeostatic/hedonic regulatory regions post-LSG may contribute to its beneficial effects in improving eating behaviors including negative emotional eating, and long-term weight-loss.

Sex differences in methylphenidate-induced dopamine increases in ventral striatum.

Sex differences in the prevalence of dopamine-related neuropsychiatric diseases and in the sensitivity to dopamine-boosting drugs such as stimulants is well recognized. Here we assessed whether there are sex differences in the brain dopamine system in humans that could contribute to these effects. We analyzed data from two independent [11C]raclopride PET brain imaging studies that measured methylphenidate-induced dopamine increases in the striatum using different routes of administration (Cohort A = oral 60 mg; Cohort B = intravenous 0.5 mg/kg; total n = 95; 65 male, 30 female), in blinded placebo-controlled designs. Females when compared to males reported stronger feeling of "drug effects" and showed significantly greater dopamine release in the ventral striatum (where nucleus accumbens is located) to both oral and intravenous methylphenidate. In contrast, there were no significant differences in methylphenidate-induced increases in dorsal striatum for either oral or intravenous administration nor were there differences in levels of methylphenidate in plasma. The greater dopamine increases with methylphenidate in ventral but not dorsal striatum in females compared to males suggests an enhanced sensitivity specific to the dopamine reward system that might underlie sex differences in the vulnerability to substance use disorders and to attention-deficit/hyperactivity disorder (ADHD).

Associations of family income with cognition and brain structure in USA children: prevention implications.

Poverty, as assessed by several socioeconomic (SES) factors, has been linked to worse cognitive performance and reduced cortical brain volumes in children. However, the relative contributions of the various SES factors on brain development and the mediating effects between cognition and brain morphometry have not been investigated. Here we used cross-sectional data from the ABCD Study to evaluate associations among various SES and demographic factors, brain morphometrics, and cognition and their reproducibility in two independent subsamples of 3892 children. Among the SES factors, family income (FI) best explained individual differences in cognitive test scores (stronger for crystallized than for fluid cognition), cortical volume (CV), and thickness (CT). Other SES factors that showed significant associations with cognition and brain morphometrics included parental education and neighborhood deprivation, but when controlling for FI, their effect sizes were negligible and their regional brain patterns were not reproducible. Mediation analyses showed that cognitive scores, which we used as surrogate markers of the children's level of cognitive stimulation, partially mediated the association of FI and CT, whereas the mediations of brain morphometrics on the association of FI and cognition were not significant. These results suggest that lack of supportive/educational stimulation in children from low-income families might drive the reduced CV and CT. Thus, strategies to enhance parental supportive stimulation and the quality of education for children in low-income families could help counteract the negative effects of poverty on children's brain development.

Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction.

Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-based classifier (MC) was developed to identify subcortical volumes that distinguished 32 healthy controls (HCs) from 33 AUD patients, who were scanned twice, during early and later withdrawal, to assess the effect of abstinence on MC-features (Discovery cohort). We validated the novel classifier in an independent Validation cohort (19 AUD patients and 20 HCs). MC-accuracy reached 80% (Discovery) and 72% (Validation). MC features included the hippocampus, amygdala, cerebellum, putamen, corpus callosum, and brain stem, which were smaller and showed stronger age-related decreases in AUD than HCs, and the ventricles and cerebrospinal fluid, which were larger in AUD and older participants. The volume of the amygdala showed a positive association with anxiety and negative urgency in AUD. Repeated imaging during the third week of detoxification revealed slightly larger subcortical volumes in AUD patients, consistent with partial recovery during abstinence. The steeper age-associated volumetric reductions in stress- and reward-related subcortical regions in AUD are consistent with accelerated aging, whereas the amygdalar associations with negative urgency and anxiety in AUD patients support its involvement in the "dark side of addiction".

Connectome-Based Prediction of Optimal Weight Loss Six Months After Bariatric Surgery.

Despite bariatric surgery being the most effective treatment for obesity, a proportion of subjects have suboptimal weight loss post-surgery. Therefore, it is necessary to understand the mechanisms behind the variance in weight loss and identify specific baseline biomarkers to predict optimal weight loss. Here, we employed functional magnetic resonance imaging (fMRI) with baseline whole-brain resting-state functional connectivity (RSFC) and a multivariate prediction framework integrating feature selection, feature transformation, and classification to prospectively identify obese patients that exhibited optimal weight loss at 6 months post-surgery. Siamese network, which is a multivariate machine learning method suitable for small sample analysis, and K-nearest neighbor (KNN) were cascaded as the classifier (Siamese-KNN). In the leave-one-out cross-validation, the Siamese-KNN achieved an accuracy of 83.78%, which was substantially higher than results from traditional classifiers. RSFC patterns contributing to the prediction consisted of brain networks related to salience, reward, self-referential, and cognitive processing. Further RSFC feature analysis indicated that the connection strength between frontal and parietal cortices was stronger in the optimal versus the suboptimal weight loss group. These findings show that specific RSFC patterns could be used as neuroimaging biomarkers to predict individual weight loss post-surgery and assist in personalized diagnosis for treatment of obesity.

Brain structural changes in cannabis dependence: association with MAGL.

Cannabis use is rising, yet there is poor understanding of biological processes that might link chronic cannabis use to brain structural abnormalities. To lend insight into this topic, we examined white matter microstructural integrity and gray matter cortical thickness/density differences between 89 individuals with cannabis dependence (CD) and 89 matched controls (64 males, 25 females in each group) from the Human Connectome Project. We tested whether cortical patterns for expression of genes relevant for cannabinoid signaling (from Allen Human Brain Atlas postmortem tissue) were associated with spatial patterns of cortical thickness/density differences in CD. CD had lower fractional anisotropy than controls in white matter bundles innervating posterior cingulate and parietal cortex, basal ganglia, and temporal cortex. The CD group also had significantly less gray matter thickness and density in precuneus, relative to controls. Sibling-pair analysis found support for causal and graded liability effects of cannabis on precuneus structure. Spatial patterns of gray matter differences in CD were significantly associated with regional differences in monoacylglycerol lipase (MAGL) expression in postmortem brain tissue, such that regions with higher MAGL expression (but not fatty-acid amide hydrolase or FAAH) were more vulnerable to cortical thinning. In sum, chronic cannabis use is associated with structural differences in white and gray matter, which was most prominent in precuneus and associated white matter tracts. Regions with high MAGL expression, and therefore with potentially physiologically restricted endogenous cannabinoid signaling, may be more vulnerable to the effects of chronic cannabis use on cortical thickness.

Brain Network Segregation and Glucose Energy Utilization: Relevance for Age-Related Differences in Cognitive Function.

The human brain is organized into segregated networks with strong within-network connections and relatively weaker between-network connections. This "small-world" organization may be essential for maintaining an energetically efficient system, crucial to the brain which consumes 20% of the body's energy. Brain network segregation and glucose energy utilization both change throughout the lifespan. However, it remains unclear whether these processes interact to contribute to differences in cognitive performance with age. To address this, we examined fluorodeoxyglucose-positron emission tomography and resting-state functional magnetic resonance imaging from 88 participants aged 18-73 years old. Consistent with prior work, brain network segregation showed a negative association with age across both sensorimotor and association networks. However, relative glucose metabolism demonstrated an interaction with age, showing a negative slope in association networks but a positive slope in sensorimotor networks. Overall, brain networks with lower segregation showed significantly steeper age-related differences in glucose metabolism, compared with highly segregated networks. Sensorimotor network segregation mediated the association between age and poorer spatial cognition performance, and sensorimotor network metabolism mediated the association between age and slower response time. These data provide evidence that sensorimotor segregation and glucose metabolism underlie some age-related changes in cognition. Interventions that stimulate somatosensory networks could be important for treatment of age-related cognitive decline.

Resting activity of the hippocampus and amygdala in obese individuals predicts their response to food cues.

Obese individuals exhibit brain functional abnormalities in multiple regions implicated in reward/motivation, emotion/memory, homeostatic regulation, and executive control when exposed to food cues and during rest. However, it remains unclear whether abnormal brain responses to food cues might account for or relate to their abnormal activity in resting state. This information would be useful for understanding the neural mechanisms behind hyperactive responses to food cues, a critical marker of obesity. Resting-state functional magnetic resonance imaging (RS-fMRI) and a cue-reactivity fMRI task with high- (HiCal) and low-caloric (LoCal) food cues were employed to investigate brain baseline activity and food cue-induced activation differences in 44 obese participants (OB), in 37 overweight participants (OW), and in 37 normal weight (NW) controls. One-way analyses of variance showed there was a group difference in the left hippocampus/amygdala activity during resting state and during food-cue stimulation (pFWE < 0.05); post-hoc tests showed the OB group had both greater basal activity and greater food cue-induced activation than the OW and NW groups; OW had higher activity in the hippocampus/amygdala than the NW group, which was only significant during resting state. In the OB group, resting-state activity in the left hippocampus/amygdala was positively correlated with activation induced by HiCal food cues, and both of these measures correlated with body mass index (BMI). Mediation analysis showed that the relationship between BMI and hippocampus/amygdala response to HiCal food cues was mediated by their resting-state activity. These findings suggest a close association between obesity and brain functional abnormality in the hippocampus/amygdala. They also indicate that resting-state activity in the hippocampus/amygdala may impact these regions' responses to food cues.

ß-Amyloid accumulation in the human brain after one night of sleep deprivation.

The effects of acute sleep deprivation on ß-amyloid (Aß) clearance in the human brain have not been documented. Here we used PET and 18F-florbetaben to measure brain Aß burden (ABB) in 20 healthy controls tested after a night of rested sleep (baseline) and after a night of sleep deprivation. We show that one night of sleep deprivation, relative to baseline, resulted in a significant increase in Aß burden in the right hippocampus and thalamus. These increases were associated with mood worsening following sleep deprivation, but were not related to the genetic risk (APOE genotype) for Alzheimer's disease. Additionally, baseline ABB in a range of subcortical regions and the precuneus was inversely associated with reported night sleep hours. APOE genotyping was also linked to subcortical ABB, suggesting that different Alzheimer's disease risk factors might independently affect ABB in nearby brain regions. In summary, our findings show adverse effects of one-night sleep deprivation on brain ABB and expand on prior findings of higher Aß accumulation with chronic less sleep.

Network connectivity predicts language processing in healthy adults.

Brain imaging has been used to predict language skills during development and neuropathology but its accuracy in predicting language performance in healthy adults has been poorly investigated. To address this shortcoming, we studied the ability to predict reading accuracy and single-word comprehension scores from rest- and task-based functional magnetic resonance imaging (fMRI) datasets of 424 healthy adults. Using connectome-based predictive modeling, we identified functional brain networks with >400 edges that predicted language scores and were reproducible in independent data sets. To simplify these complex models we identified the overlapping edges derived from the three task-fMRI sessions (language, working memory, and motor tasks), and found 12 edges for reading recognition and 11 edges for vocabulary comprehension that accounted for 20% of the variance of these scores, both in the training sample and in the independent sample. The overlapping edges predominantly emanated from language areas within the frontoparietal and default-mode networks, with a strong precuneus prominence. These findings identify a small subset of edges that accounted for a significant fraction of the variance in language performance that might serve as neuromarkers for neuromodulation interventions to improve language performance or for presurgical planning to minimize language impairments.

Reduced Local and Increased Long-Range Functional Connectivity of the Thalamus in Autism Spectrum Disorder.

It is hypothesized that brain network abnormalities in autism spectrum disorder (ASD) reflect local overconnectivity and long-range underconnectivity. However, this is not a consistent finding in recent studies, which could reflect the developmental nature and the heterogeneity of ASD. Here, we tested 565 ASD and 602 neurotypical (NT) males, and 91 ASD and 233 NT females using local functional connectivity density (lFCD) mapping and seed-voxel correlation analyses to assess how local and long-range connectivities differ in ASD. Compared with NT males, ASD males had lower and weaker age-related increases in thalamic lFCD, which were associated with symptoms of autism. Post-hoc seed-voxel correlation analyses for the thalamus cluster revealed stronger connectivity with auditory, somatosensory, motoric, and interoceptive cortices for ASD than for NT, both in males and in females, which decreased with age in both ASD and NT. These results document the disruption of local thalamic connectivity and dysregulation of thalamo-cortical networks, which might contribute to perceptual, motoric, and interoceptive impairments, and are also consistent with a developmental delay in functional connectivity in ASD.

Association Between Brain Activation and Functional Connectivity.

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

Apparent diffusion coefficient changes in human brain during sleep - Does it inform on the existence of a glymphatic system?

The role of sleep in brain physiology is poorly understood. Recently rodent studies have shown that the glymphatic system clears waste products from brain more efficiently during sleep compared to wakefulness due to the expansion of the interstitial fluid space facilitating entry of cerebrospinal fluid (CSF) into the brain. Here, we studied water diffusivity in the brain during sleep and awake conditions, hypothesizing that an increase in water diffusivity during sleep would occur concomitantly with an expansion of CSF volume - an effect that we predicted based on preclinical findings would be most prominent in cerebellum. We used MRI to measure slow and fast components of the apparent diffusion coefficient (ADC) of water in the brain in 50 healthy participants, in 30 of whom we compared awake versus sleep conditions and in 20 of whom we compared rested-wakefulness versus wakefulness following one night of sleep-deprivation. Sleep compared to wakefulness was associated with increases in slow-ADC in cerebellum and left temporal pole and with decreases in fast-ADC in thalamus, insula, parahippocampus and striatal regions, and the density of sleep arousals was inversely associated with ADC changes. The CSF volume was also increased during sleep and was associated with sleep-induced changes in ADCs in cerebellum. There were no differences in ADCs with wakefulness following sleep deprivation compared to rested-wakefulness. Although we hypothesized increases in ADC with sleep, our findings uncovered both increases in slow ADC (mostly in cerebellum) as well as decreases in fast ADC, which could reflect the distinct biological significance of fast- and slow-ADC values in relation to sleep. While preliminary, our findings suggest a more complex sleep-related glymphatic function in the human brain compared to rodents. On the other hand, our findings of sleep-induced changes in CSF volume provide preliminary evidence that is consistent with a glymphatic transport process in the human brain.