Imaging homeostatic sleep pressure and circadian rhythm in the human brain

Imaging homeostatic sleep pressure and circadian rhythm in the human brain

Zhuo Fang1,2, Hengyi Rao1,2

1Laboratory of Applied Brain and Cognitive Sciences, Shanghai International Studies University, Shanghai 200000, China;2Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA

Correspondence to: Hengyi Rao. Center for Functional Neuroimaging, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA. Email:

Provenance: This is an invited Editorial commissioned by the Section Editor Xi-Jian Dai (Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, China).

Comment on: Muto V, Jaspar M, Meyer C, et al. Local modulation of human brain responses by circadian rhythmicity and sleep debt. Science 2016;353:687-90.

Submitted Feb 25, 2017. Accepted for publication Mar 17, 2017.

doi: 10.21037/jtd.2017.03.168

It is well-known that our sleep-wake patterns and alertness level during wakefulness are mainly modulated by two interactive processes, a homeostatic sleep debt process (S) refers to the drive for sleep that increases as a saturating exponential when we stay awake and decreases exponentially when we sleep, and a circadian processes (C) refers to the internal oscillatory rhythm that runs about 24 hours and can be reset by the environmental light (1-3). Although the detrimental effects of prolonged wakefulness with accumulative sleep debt after sleep deprivation on cognitive performances have been well documented in numerous studies (4-8), sleep duration continues decreasing in the modern societies and hundreds of millions of people does not have sufficient sleep due to life styles, family demands, and/or medical situations (9,10). A meta-analysis on 70 behavioral experiments and 147 cognitive tests has revealed that vigilance or sustained attention, which can be precisely measured by the psychomotor vigilance test (PVT), is the most significantly impaired cognitive function domain affected by sleep deprivation (6). Behavioral studies have further shown that circadian dynamics interact with sleep debt and modulate cognitive performance after sleep loss (11-14). Specifically, previous studies have demonstrated that sleep deprivation impaired vigilant attention most prominently during circadian night, the accumulative neurobehavioral deficits reached largest on the morning, and became progressively smaller across the hours of the day, particularly on the late afternoon and early evening, which may reflect a period of relatively protected alertness from circadian rhythm during prolonged wakefulness.

The negative effects of homeostatic sleep debt on brain function have also been well demonstrated by numerous sleep deprivation studies using various experimental paradigms and different neuroimaging techniques, including positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). These studies have demonstrated that sleep loss not only impairs brain activations during various cognitive tasks (5,14-16), but also alters functional connectivity at resting state without task demands (17-20). A recent meta-analysis study on 11 sleep deprivation studies across different attention tasks revealed significantly decreased activation in the frontoparietal attention network and salience network, and increased activation in the thalamus after acute total sleep loss (21).

Due to the high-demanding workloads, transdisciplinary expertise, and expensive research costs associated with brain imaging studies of sleep deprivation, most previous studies only measured brain activation or connectivity changes at one time point of the circadian cycle after sleep loss as compared to those at a similar time point following normal sleep, therefore wiped off the potential influence of circadian rhythm on brain function. Currently, a small number of neuroimaging studies have examined the effects of time-of-day on brain activation patterns in response to different cognitive tasks, including autobiographic memory (22), visual processing (23), conflict processing (24), executive attention (25,26), and working memory (27). However, these studies usually measured brain function at two time points of circadian phase and did not combine with sleep deprivation, therefore were still unable to demonstrate the time course of brain function changes across a full cycle of circadian rhythm.

In a very interesting paper published in a recent issue of SCIENCE (28), Muto and colleagues employed a repeated fMRI design and studied brain function changes in a cohort of 33 healthy volunteers who stayed awake for a 42-hour period under constant environmental and behavioral conditions. This in order to address this important yet largely neglected question about how brain function varies with the dynamic phase of circadian rhythm and the buildup of homeostatic sleep pressure. In this study, brain activation and behavioral responses to the PVT were repeatedly assessed in 12 fMRI sessions during 42 hours of wakefulness including a full cycle of circadian rhythm, and were realigned to the dim-light melatonin secretion onset (DLMO) to determine the corresponding circadian phase. An additional fMRI session was also acquired after a night of 12-hour recovery sleep. Two sophisticated analysis were conducted. The first one did not use the actual time courses of circadian rhythm but assumed that regional brain activation fluctuated as a sine wave. Not surprisingly, this analysis revealed significant circadian modulation in a large set of cortical regions. However, the phase of regional brain responses relative to DLMO varied across cortical and sub-cortical areas, with earliest phase observed in the amygdala and latest phase found in the inferior prefrontal cortex. The second analysis modeled homeostatic sleep pressure as monotonically decreasing with elapsed time awake and increasing after recovery sleep, and examined whether PVT brain responses were modulated by sleep pressure and how sleep pressure and circadian rhythm interact in the brain. This analysis found a significant negative effect of sleep debt in a large set of high-order association cortical areas in the frontal, parietal, visual, sensorimotor, insular, and cingulate cortices, while the main effect of circadian rhythm were found in much fewer cortical areas and a number of sub-cortical areas. In addition, significant interactions between homeostatic sleep pressure and circadian rhythm were observed in the occipital poles and thalamic areas. Finally, as expected, brain responses and cognitive performance returned to baseline after the recovery sleep.

This study by Muto and colleagues offers an example using non-invasive neuroimaging technique for simultaneous assessment of homeostatic sleep pressure and circadian rhythm modulation in the human brain. As commented by Czeisler (29), this study may open new doors for research on a broad range of basic questions in the sleep and circadian field, such as the role of melatonin in mediating the effects of circadian rhythm on brain responses, and the mechanisms underlying longitudinal changes in sleep/wake pattern and circadian rhythm during brain development. The study paradigm and imaging techniques in this research can also be applied for clinical research on many psychiatric and neurologic disorders in which disrupted sleep and circadian rhythm are common co-morbidities, such as alcoholism, depression, schizophrenia, and neurodegenerative diseases. However, it is noteworthy to point out a couple of important limitations in this study which have implications for future research.

The first limitation is the relatively small number of sample size. There were 33 subjects involved in this study, which is not a large sample that can be used to characterize individual differences in the magnitude of sleepiness and cognitive performance deficits after sleep loss and cross the circadian cycle. Health individuals differ in their preferred sleep-wake times and dynamics of homeostatic sleep pressure, which can be classified as different chronotypes (i.e., early/morning-type or late/evening-type) (30). Moreover, while most individuals show substantial cognitive deficits and drowsiness without sufficient sleep, some adults can maintain alertness and display little cognitive changes during sleep deprivation (31). Previous studies have indicated that differential vulnerability to sleep deprivation and chronotype both significantly modulate cognitive performance and brain activation patterns (16,26,27,32). It will be of great interest to demonstrate how time courses of brain responses during circadian rhythm varied in individuals with different chronotype and sleep deprivation vulnerability.

Another limitation is the conventional blood oxygen level dependent (BOLD) fMRI used to measure brain responses to the PVT and n-back tasks in this study. As an index reflecting a complex interaction among a number of physiological variables including cerebral blood flow (CBF), cerebral blood volume, and cerebral oxygenation metabolic rate, task-related BOLD fMRI only measures relative signal changes between different events (e.g., fastest vs. slow reaction times) or task conditions (e.g., 3-bask vs. 0-back), therefore is not able to provide absolute quantification of brain activity. In addition, due to low frequency noise in the BOLD signal, task-related BOLD fMRI has poor sensitivity to track slow neural activity changes over a time scale longer than a few minutes (33). These unfavorable characteristics of BOLD signal make it very difficult or sometimes misleading when drawing conclusions for the observed brain activation changes, particularly for sleep deprivation and circadian studies which involve slow neural activity changes over hours and days. For example, the meta-analysis on sleep deprivation and attention fMRI studies revealed significantly increased activation in the thalamus (21), which was also observed in the Muto et al. study. However, it is impossible for these studies to dissociate the effects of sleep deprivation or circadian rhythm on brain function per se from the effects of sleep deprivation or circadian rhythm on task performance that contaminates the observed brain activation differences. Consequently, it is hard for these studies to conclude if increased thalamic activation following sleep deprivation reflects increased activity during task performance, or decreased activity during resting baseline or control condition, or some combination of both. In fact, increased thalamic activation contradicts with reduced alertness level and vigilance performance after sleep loss in behavioral observations (4-6) and is opposite to decreased thalamic metabolism reported in PET studies (34-36). It is likely that increased thalamic activation may reflect a complex interaction between the de-arousing effects of sleep loss and the arousing effects of task performance (21). Future studies using more quantitative imaging techniques, such as arterial spin labeling fMRI (37-40), which offers absolute quantification of regional cerebral blood flow (CBF, in units of mL/min/100 g tissue) that is tightly coupled with brain metabolism, are necessary to verify the finding from this study and further dissociate the potential differential effects of sleep deprivation and circadian rhythm on brain activity during task performance and at resting baseline. Nevertheless, findings from the Muto et al. study provide new insights into an understanding of brain mechanisms underlying homeostatic sleep pressure, circadian rhythm, and the interactions between these two essential processes in our life.


Funding: This work is supported in part by NIH Grants R01 HL102119 and R01 MH107571, and the program for professor of special appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (TP2016020).


Conflicts of Interest: The authors have no conflicts of interest to declare.


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Cite this article as: Fang Z, Rao H. Imaging homeostatic sleep pressure and circadian rhythm in the human brain. J Thorac Dis 2017;9(5):E495-E498. doi: 10.21037/jtd.2017.03.168

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