Progression to deep sleep is characterized by changes to BOLD dynamics in sensory cortices

Auditory inputs modulate intrinsic neuronal timescales during sleep

Functional magnetic resonance imaging (fMRI) studies have demonstrated that intrinsic neuronal timescales (INT) undergo modulation by external stimulation during consciousness. It remains unclear if INT keep the ability for significant stimulus-induced modulation during primary unconscious states, such as sleep. This fMRI analysis addresses this question via a dataset that comprises an awake resting-state plus rest and stimulus states during sleep. We analyzed INT measured via temporal autocorrelation supported by median frequency (MF) in the frequency-domain. Our results were replicated using a biophysical model. There were two main findings: (1) INT prolonged while MF decreased from the awake resting-state to the N2 resting-state, and (2) INT shortened while MF increased during the auditory stimulus in sleep. The biophysical model supported these results by demonstrating prolonged INT in slowed neuronal populations that simulate the sleep resting-state compared to an awake state. Conversely, under sine wave input simulating the stimulus state during sleep, the model's regions yielded shortened INT that returned to the awake resting-state level. Our results highlight that INT preserve reactivity to stimuli in states of unconsciousness like sleep, enhancing our understanding of unconscious brain dynamics and their reactivity to stimuli.

fMRI spectral signatures of sleep

The conventional wisdom that sleep is a global state, affecting the whole brain uniformly and simultaneously, was overturned by the discovery of local sleep, where individual neuronal populations were found to be asleep and the rest of the brain awake. However, due to the difficulty of monitoring local neuronal states in humans, our understanding of local sleep remains limited. Using simultaneous functional MRI (fMRI) and electroencephalography, we find that the oscillations of brain hemodynamic activity provide signatures of sleep at a local neuronal population level. We show that the fMRI signatures of sleep can be employed to monitor local neuronal states and investigate which brain regions are the first to fall asleep or wake up at wake–sleep transitions.

Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level–dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake–sleep transitions, and investigate local homeostatic sleep processes.

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

Falling asleep is common in fMRI studies. By using long eyelid closures to detect microsleep onset, we showed that the onset and termination of short sleep episodes invokes a systematic sequence of BOLD signal changes that are large, widespread, and consistent across different microsleep durations. The signal changes are intimately intertwined with shifts in respiration and heart rate, indicating that autonomic contributions are integral to the brain physiology evaluated using fMRI and cannot be simply treated as nuisance signals. Additionally, resting state functional connectivity (RSFC) was altered in accord with the frequency of falling asleep and in a manner that global signal regression does not eliminate. Our findings point to the need to develop a consensus among neuroscientists using fMRI on how to deal with microsleep intrusions. SIGNIFICANCE STATEMENT: Sleep, breathing and cardiac action are influenced by common brainstem nuclei. We show that falling asleep and awakening are associated with a sequence of BOLD signal changes that are large, widespread and consistent across varied durations of sleep onset and awakening. These signal changes follow closely those associated with deceleration and acceleration of respiration and heart rate, calling into question the separation of the latter signals as 'noise' when the frequency of falling asleep, which is commonplace in RSFC studies, correlates with the extent of RSFC perturbation. Autonomic and central nervous system contributions to BOLD signal have to be jointly considered when interpreting fMRI and RSFC studies.

Cerebral functional networks during sleep in young and older individuals

Even though sleep modification is a hallmark of the aging process, age-related changes in functional connectivity using functional Magnetic Resonance Imaging (fMRI) during sleep, remain unknown. Here, we combined electroencephalography and fMRI to examine functional connectivity differences between wakefulness and light sleep stages (N1 and N2 stages) in 16 young (23.1 ± 3.3y; 7 women), and 14 older individuals (59.6 ± 5.7y; 8 women). Results revealed extended, distributed (inter-between) and local (intra-within) decreases in network connectivity during sleep both in young and older individuals. However, compared to the young participants, older individuals showed lower decreases in connectivity or even increases in connectivity between thalamus/basal ganglia and several cerebral regions as well as between frontal regions of various networks. These findings reflect a reduced ability of the older brain to disconnect during sleep that may impede optimal disengagement for loss of responsiveness, enhanced lighter and fragmented sleep, and contribute to age effects on sleep-dependent brain plasticity.

The connectivity between the olfactory and auditory cortex predicts an individual's sleep quality

Sleep disorders and multiple sensory impairments have been noticed as the potential first sign of neurodegenerative diseases such as the Parkinson disease. The relationship between sleep quality and the sensory neural basis would help us consider their combination in early diagnosis. In the present study, 32 out of 45 healthy subjects' resting-state functional magnetic resonance imaging data survived from motion correction and entered into the connectivity analysis. We found that the connectivity between two regions of interest (the left olfactory gyrus and the left superior temporal pole) and the regional homogeneity in the left middle temporal gyrus were negatively correlated with their Pittsburgh sleep quality index. These results suggest that these sensory-related brain regions are related to sleep quality and they may together predict the diseases.

Functional consequences of acute tryptophan depletion on raphe nuclei connectivity and network organization in healthy women

Previous research on central nervous serotonin (5-HT) function provided evidence for a substantial involvement of 5-HT in the regulation of brain circuitries associated with cognitive and affective processing. The underlying neural networks comprise core subcortical/cortical regions such as amygdala and medial prefrontal cortex, which are assumed to be modulated amongst others by 5-HT. Beside the use of antidepressants, acute tryptophan depletion (ATD) is a widely accepted technique to manipulate of 5-HT synthesis and its respective metabolites in humans by means of a dietary and non-pharmacological tool. We used a double-blind, randomized, cross-over design with two experimental challenge conditions, i.e. ATD and tryptophan (TRP) supplementation (TRYP+) serving as a control. The aim was to perturb 5-HT synthesis and to detect its impact on brain functional connectivity (FC) of the upper serotonergic raphe nuclei, the amygdala and the ventromedial prefrontal cortex as well as on network organization using resting state fMRI. 30 healthy adult female participants (age: M ​= ​24.5 ​± ​4.4 ​yrs) were included in the final analysis. ATD resulted in a 90% decrease of TRP in the serum relative to baseline. Compared to TRYP ​+ ​for the ATD condition a significantly lower FC of the raphe nucleus to the frontopolar cortex was detected, as well as greater functional coupling between the right amygdala and the ventromedial prefrontal cortex. FC of the raphe nucleus correlated significantly with the magnitude of TRP changes for both challenge conditions (ATD & TRYP+). Network-based statistical analysis using time series from 260 independent anatomical ROIs revealed significantly greater FC after ATD compared to TRYP+ in several brain regions being part of the default-mode (DMN) and the executive-control networks (ECN), but also of salience or visual networks. Finally, we observed an impact of ATD on the rich-club organization in terms of decreased rich-club coefficients compared to TRYP+. In summary we could confirm previous findings that the putative decrease in brain 5-HT synthesis via ATD significantly alters FC of the raphe nuclei as well as of specific subcortical/cortical regions involved in affective, but also in cognitive processes. Moreover, an ATD-effect on the so-called rich-club organization of some nodes with the high degree was demonstrated. This may indicate effects of brain 5-HT on the integration of information flow from several brain networks.

Human non-REM sleep and the mean global BOLD signal

A hallmark of non-rapid eye movement (REM) sleep is the decreased brain activity as measured by global reductions in cerebral blood flow, oxygen metabolism, and glucose metabolism. It is unknown whether the blood oxygen level dependent (BOLD) signal undergoes similar changes. Here we show that, in contrast to the decreases in blood flow and metabolism, the mean global BOLD signal increases with sleep depth in a regionally non-uniform manner throughout gray matter. We relate our findings to the circulatory and metabolic processes influencing the BOLD signal and conclude that because oxygen consumption decreases proportionately more than blood flow in sleep, the resulting decrease in paramagnetic deoxyhemoglobin accounts for the increase in mean global BOLD signal.

Emergence of mature cortical activity in wakefulness and sleep in healthy preterm and full-term infants

Study Objectives

Cortical activity patterns develop rapidly over the equivalent of the last trimester of gestation, in parallel with the establishment of sleep architecture. However, the emergence of mature cortical activity in wakefulness compared with sleep states in healthy preterm infants is poorly understood.

Methods

To investigate whether the cortical activity has a different developmental profile in each sleep-wake state, we recorded 11-channels electroencephalography (EEG), electrooculography (EOG), and respiratory movement for 1 hr from 115 infants 34 to 43 weeks-corrected age, with 0.5-17 days of postnatal age. We characterized the trajectory of δ, θ, and α-β oscillations in wakefulness, rapid eye movement (REM) sleep, and non-REM sleep by calculating the power spectrum of the EEG, averaged across artifact-free epochs.

Results

δ-Oscillations in wakefulness and REM sleep decrease with corrected age, particularly in the temporal region, but not in non-REM sleep. θ-Oscillations increase with corrected age in sleep, especially non-REM sleep, but not in wakefulness. On the other hand, α-β oscillations decrease predominantly with postnatal age, independently of sleep-wake state, particularly in the occipital region.

Conclusions

The developmental trajectory of δ and θ rhythms is state-dependent and results in changed cortical activity patterns between states with corrected age, which suggests that these frequency bands may have particular functional roles in each state. Interestingly, postnatal age is associated with a decrease in α-β oscillations overlying primary visual cortex in every sleep-wake state, suggesting that postnatal experience (including the first visual input through open eyes during periods of wakefulness) is associated with resting-state visual cortical activity changes.

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Reduced resting-state thalamostriatal functional connectivity is associated with excessive daytime sleepiness in persons with and without depressive disorders

BACKGROUND

Excessive daytime sleepiness (EDS) is a common and significant problem encountered in affective illness, however, the biological underpinnings of EDS in persons with psychiatric disorders are not clear. This study evaluated the associations between thalamic connectivity with cortical and subcortical brain regions with EDS in persons with and without depressive disorders (DD).

METHODS

Resting-state functional connectivity magnetic resonance imaging scans from 67 unmedicated young to middle-aged women with current DD (n = 30), remitted DD (n = 13), and healthy controls (n = 24) were utilized to examine the associations between thalamic connectivity with cortical/subcortical structures and EDS.

RESULTS

After correction for multiple comparisons and adjustment for age, habitual sleep duration, and depressive symptomatology, reduced resting-state connectivity between the bilateral thalamus and left rostral striatum (caudate/putamen) was significantly associated with EDS.

LIMITATIONS

Causal inferences between thalamostriatal connectivity and EDS could not be determined.

CONCLUSIONS

These results further implicate the role of the striatum and thalamus as central components of the experience of EDS. Further research is indicated to clarify the specific role these structures play in EDS in psychiatric disorders.

Multivariate Heteroscedasticity Models for Functional Brain Connectivity

Functional brain connectivity is the co-occurrence of brain activity in different areas during resting and while doing tasks. The data of interest are multivariate timeseries measured simultaneously across brain parcels using resting-state fMRI (rfMRI). We analyze functional connectivity using two heteroscedasticity models. Our first model is low-dimensional and scales linearly in the number of brain parcels. Our second model scales quadratically. We apply both models to data from the Human Connectome Project (HCP) comparing connectivity between short and conventional sleepers. We find stronger functional connectivity in short than conventional sleepers in brain areas consistent with previous findings. This might be due to subjects falling asleep in the scanner. Consequently, we recommend the inclusion of average sleep duration as a covariate to remove unwanted variation in rfMRI studies. A power analysis using the HCP data shows that a sample size of 40 detects 50% of the connectivity at a false discovery rate of 20%. We provide implementations using R and the probabilistic programming language Stan.

Mapping visual dominance in human sleep

Sleep is a universal behavior, essential for humans and animals alike to survive. Its importance to a person's physical and mental health cannot be overstated. Although lateralization of function is well established in the lesion, split-brain and task based neuroimaging literature, and more recently in functional imaging studies of spontaneous fluctuations of the fMRI BOLD signal during wakeful rest, it is unknown if these asymmetries are present during sleep. We investigated hemispheric asymmetries in the global brain signal during non-REM sleep. Here we show that increasing sleep depth is accompanied by an increasing rightward asymmetry of regions in visual cortex including primary bilaterally and in the right hemisphere along the lingual gyrus and middle temporal cortex. In addition, left hemisphere language regions largely maintained their leftward asymmetry during sleep. Right hemisphere attention related regions expressed a more complicated relation with some regions maintaining a rightward asymmetry while this was lost in others. These results suggest that asymmetries in the human brain are state dependent.

Sleep duration and resting fMRI functional connectivity: examination of short sleepers with and without perceived daytime dysfunction

BACKGROUND

Approximately 30% of the U.S. population reports recurrent short sleep; however, perceived sleep need varies widely among individuals. Some "habitual short sleepers" routinely sleep 4-6 hr/night without self-reported adverse consequences. Identifying neural mechanisms underlying individual differences in perceived sleep-related dysfunction has important implications for understanding associations between sleep duration and health.

METHOD

This study utilized data from 839 subjects of the Human Connectome Project to examine resting functional connectivity associations with self-reported short sleep duration, as well as differences between short sleepers with versus without reported dysfunction. Functional connectivity was analyzed using a parcellation covering the cortical, subcortical, and cerebellar gray matter at 5 mm resolution.

RESULTS

Self-reported sleep duration predicts one of the primary patterns of intersubject variance in resting functional connectivity. Compared to conventional sleepers, both short sleeper subtypes exhibited resting fMRI (R-fMRI) signatures consistent with diminished wakefulness, potentially indicating inaccurate perception of functionality among those denying dysfunction. Short sleepers denying dysfunction exhibited increased connectivity between sensory cortices and bilateral amygdala and hippocampus, suggesting that efficient sleep-related memory consolidation may partly explain individual differences in perceived daytime dysfunction.

CONCLUSIONS

Overall, current findings indicate that R-fMRI investigations should include assessment of average sleep duration during the prior month. Furthermore, short sleeper subtype findings provide a candidate neural mechanism underlying differences in perceived daytime impairment associated with short sleep duration.