Elsevier

Sleep Medicine

Volume 50, October 2018, Pages 137-144
Sleep Medicine

Original Article
Dissociable effects of sleep deprivation on functional connectivity in the dorsal and ventral default mode networks

https://doi.org/10.1016/j.sleep.2018.05.040Get rights and content

Highlights

  • Dissociable effects of SD on functional connectivity of DMN were detected.

  • The functional connectivity within the dorsal DMN decreased after sleep deprivation.

  • The functional connectivity between the subsystems increased after sleep deprivation.

  • Working memory was positively correlated with between-subsystem connectivity after SD.

  • Between-subsystem connectivity was negatively correlated with RT of PVT in the SD group.

Abstract

Objective

To examine changes in functional connectivity of the default mode network (DMN) that are induced by sleep deprivation, and to identify individual differences that contribute to the vulnerability of the brain's response to sleep deprivation.

Methods

Using functional magnetic resonance imaging, we scanned 51 healthy young subjects during the resting state. Of these participants, 28 were scanned following 24 h of sleep deprivation, and 23 age- and education-matched control subjects were scanned after being well rested.

Results

Independent component analysis was conducted to identify the DMN. Unlike previous studies that consider the DMN as one homogeneous network, the present study found a dissociable effect of sleep deprivation on two subsystems of the DMN. Functional connectivity within the dorsal DMN decreased; this was correlated with longer response times in a psychomotor vigilance task (PVT). An enhanced functional connectivity was found within the ventral DMN as well as between two subsystems, after sleep deprivation. In addition, between-subsystems connectivity was positively correlated with working memory and negatively correlated with the response time of PVT, suggesting a possible compensatory effect of enhanced communication across two subsystems.

Conclusions

The present findings suggest a dissociable effect of sleep deprivation on functional connectivity in the DMN. Lower functional connectivity in dorsal DMN was related to impairments of basic cognitive function. Notably, working memory was positively correlated with the putative compensatory enhanced functional connectivity across two subsystems, which in turn correlated with behavioral performance after sleep deprivation; this suggests that good working memory may play a protective role in sleep deprivation.

Introduction

It is well known that the modern 24/7 lifestyle compromises sleep duration. According to a recent report, sleep problems affect one-third of the general population, and 60–70 million Americans suffer from chronic sleep problems [1]. Disrupted sleep has been suggested to be deleterious with regard to daily function and the development of heart disease [2], obesity [3], Alzheimer's disease [4], and even premature all-cause mortality [5].

A groundbreaking study on sleep deprivation was conducted in the 19th century, inspiring numerous physiologists and psychologists to investigate the effects of sleep deprivation on neurocognitive performance and physical function [6]. Sleep deprivation has been well documented to impair cognitive function, including attention, memory, and decision-making (for review, see Refs. [7], [8]) [9], [10], [11]. However, recent studies have repeatedly shown relatively preserved performance on complex cognitive tasks [12]. To date, most studies focused on the deleterious effects of sleep deprivation. Nonetheless, it is also important to explore compensatory changes that occur after sleep deprivation, to possibly tap the potential of such changes for shift-workers. To better understand the impact of one night of sleep deprivation and to possibly benefit shift workers, the present study investigated changes in the brain that are induced by sleep deprivation.

The brain is organized into multiple distributed large-scale networks, and the default mode network (DMN) is an anti-task network whose metabolic activation decreases during external cognitive tasks. The DMN has received substantial research attention since its discovery [13], [14], [15]. Studies that investigated functional connectivity within the DMN after sleep deprivation have consistently reported lower functional connectivity within the network [16], [17]. However, a growing number of studies suggest that this network comprises at least two functionally distinct subdivisions and not simply one homogeneous network: (i) one subdivision consisting of the dorsal and anterior regions (dorsal DMN [dDMN]) is involved in introspective, self-oriented processes and (ii) a second subdivision consisting of posterior and medial temporal regions (ventral DMN [vDMN]) is engaged in decision-making, which is a more complex process requiring higher cognitive function [18], [19], [20]. The vDMN has a significantly weaker anti-correlation with the attention network compared with the dDMN. Based on findings of impairments on simple cognitive tasks and preserved performance on complex tasks after sleep deprivation, the first hypothesis of the present study was that there is a dissociable effect of sleep deprivation on functional connectivity in the two subsystems of the DMN. Functional connectivity of the dDMN decreases, consistent with the reported impairments of cognitive function. Functional connectivity of the vDMN increases and communication between the dDMN and vDMN is enhanced to play a compensatory role in preserving performance.

Accumulating studies have focused on individual differences in vulnerability to sleep deprivation. Several studies have attempted to predict sensitivity or vulnerability to worse performance based on structural or functional connectivity of the DMN after sleep deprivation [21], [22]. Lower brain activation during a working memory task at resting baseline is associated with vulnerability to the effects of sleep deprivation [23]. Some studies have sought to identify biomarkers that can predict the vulnerability of cognitive function to sleep deprivation. The factors that influence the brain's response to sleep deprivation remain unclear. Our previous study found that working memory plays a protective role in response to sleep deprivation. People with greater working memory capacity exhibited preserved performance in instrumental learning [11]. A reasonable assumption is that working memory capacity is involved in compensatory adaptations of the brain's response to sleep deprivation.

Section snippets

Participants

Fifty-one healthy college students were enrolled in the study, after selection based on multiple criteria, through advertisements. All of the participants met the following inclusion criteria: (1) right-handed, (2) nonsmokers, (3) regular sleeping habits (>6.5 h and <10 h of sleep per night), (4) not on any long-term medications, (5) no history of sleep disorders or psychiatric/neurological disorders, (6) no shift work in the past three months, (7) no traveling to a time zone with more than a

Physiological data

Demographic data, psychological traits, and sleep characteristics are shown in Table 1. Independent-sample t-tests or Mann–Whitney U tests revealed no significant differences across the two groups in age, body mass index (BMI), years of education, BDI scores, HAMA scores, BIS scores (including all three dimensions), MoCA scores, working memory capacity, PSQI scores, habitual sleep duration during the past month, averaged sleep duration in the three days before the experiment, ESS scores, or MEQ

Discussion

Numerous studies have investigated the effects of total sleep deprivation on cognitive function, but the results have not been consistent. Two variables may cause such inconsistencies, the variability of cognitive tasks and individual differences. Even for the same cognitive function, different experimental tools have been applied across studies. Acute sleep deprivation mainly affects basic cognitive function, especially executive function and attentional processes, with less influence on

Acknowledgments

This study was supported in part by the National Basic Research Program of China (no. 2015CB856400), National Natural Science Foundation of China (no. 81501158, 81521063, 91432303, and 31230033), and National Key Technology Research and Development Program of the Ministry of Science and Technology of China (no. 2015BAI13B01).

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    Authors who contributed equally to the research project.

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