Imaging the Sleep Deprived Brain: A Brief Review

Michael WL Chee, MBBS, FRCP (Edin)Neuroscience and Behavioral Disorders Program, Duke-NUS Graduate Medical School, Singapore

Key Words: fMRI, Cognitive tasks, Attention, Default mode network, Sleep deprivation.

Copyright © 2013 Korean Sleep Research Society 1

REVIEW ARTICLEJ Korean Sleep Res Soc 2013;10:1-6 ISSN 1738-608X

Introduction

Functional magnetic resonance imaging (fMRI) is a highly versatile tool used to study neurobehavioral alterations asso-ciated with sleep deprivation (SD). Task-related fMRI is the most widely used technique and an impressive list of cogni-tive domains has been evaluated using this technique (Table 1).1-40 fMRI measures relative change in blood oxygenation level dependant (BOLD) signal in capillaries and venules ad-jacent to neuronal clusters whose firing rate and consequ-ently, synaptic potentials are modulated by task performance. An increase in MR signal occurs as a result of a relatively dis-proportionate elevation in blood flow relative to oxygen con-sumption in response to sensory stimulation and/or task per-formance. In addition to task-related activation, the evaluation of task-related deactivation where signal changes fall below baseline levels can be evaluated.1,18,25,30,41

Blood oxygenation level dependant imaging measures rel-ative changes in blood flow, but does not ascertain absolute blood flow. Quantification of blood flow may occasionally be useful, for example, to study time-on-task effects,42 and other phenomena whose observation requires signal stability over several minutes as opposed to several seconds. Such measure-ments can be obtained using a variety of arterial spin labeling (ASL) techniques that have different levels of precision.43,44 A disadvantage of ASL is its inferior signal to noise ratio rela-tive to BOLD imaging. Additionally, the requirement for bl-ock sampling also makes it impossible to perform event-re-lated designs that are important in separating out trials where

the subject may have been asleep.8 The evaluation of functional connectivity, conducted by as-

sessing signal covariation in pairs of regions, or by determin-ing the extent to which signal in a ‘target’ region interacts with that of a ‘seed’ region according to state/task context provides additional characterization of altered physiology. The latter method, known as psychophysiological Interaction-PPI has been applied in studies evaluating selective attention,12,45,46 the processing of emotional pictures as well as executive func-tion/working memory.29,35

In addition to fMRI studies designed to evaluate signal changes in response to task performance, it may be informa-tive to evaluate ‘resting-state’ activity or intrinsic functional connectivity.47,48 This refers to the identification of regions sh-owing synchronous low frequency oscillations (0.1-0.01 Hz) in BOLD signal that are not time locked to task performance or sensory stimulation. Studies of this type in sleeping indivi-duals have shown changes in connectivity within the default mode network (DMN) alluded to earlier.49,50 The first study evaluating resting state networks in the setting of SD found selective reductions in DMN functional connectivity and re-duced anti-correlation with low frequency oscillations in the ‘task-positive’ network (Fig. 1).18 Analyses of resting state data hold promise of being informative of alterations in brain function without requiring motivated performance on the part of a participant.51 Related to functional connectivity, MRI in the form of diffusion tensor imaging (DTI) can be used to evaluate white matter connectivity. Strangely, only one study to date has used DTI to study sleep deprived individuals.52

Combining electroencephalography (EEG) and fMRI in SD or sleep related studies is primarily motivated by the need to monitor sleep stage although the high temporal resolution of EEG is also well suited to study transient phenomena like lapsing.53 The neural correlates of spindles and slow waves have been studied using this technique.54-56 In addition, fMRI guid-ed repetitive transcranial magnetic stimulation has been used

Received June 12, 2013Revised June 18, 2013Accepted June 18, 2013

Address for correspondenceMichael WL Chee, MBBS, FRCP (Edin)Neuroscience and Behavioral Disorders Program, Duke-NUS Graduate Med-ical School, 8 College Rd, #06-18, Singapore 169857, SingaporeTel: +65 65164916, Fax: +65 62218625E-mail: michael.chee@duke-nus.edu.sg

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Imaging the Sleep Deprived Brain

to evaluate the therapeutic potential of transcranial magnetic stimulation in alleviating SD.28

Effects of Task Difficulty, Cognitive Domain Tested and Inter-Individual Differences

The results of behavioral studies suggested that cognitive

domain engaged and task difficulty might affect neural resp-onse to SD.21 This motivated subsequent studies probing wo-rking memory to examine the effect of manipulating task dif-ficulty and/or item load.1,2,57 Although the specific areas most affected by SD differ somewhat across these studies, a com-mon set of findings concerns the decrease in higher visual cor-tex and fronto-parietal activation when performance declined during SD. In contrast, activation is relatively preserved when performance is maintained. The notion that increased task difficulty might elicit ‘compensatory’ frontal activation was then independently demonstrated in a study evaluating logical reasoning.23

As experience in fMRI cumulated with studies that recruit-ed at least 20 subjects, it became evident that inter-individual differences in response to SD could be identified reliably using imaging. A few studies suggested that a single imaging study conducted in the rested state might predict vulnerability to performance decline in the tested domain whereas later stud-ies found that a shift in activation across state may be more reliable as a marker of inter-individual differences in perfor-mance when sleep deprived.4,9,11,24,26

A wealth of behavioral data collected on behavior in sleep deprived persons suggests the loss of vigilance or sustained at-tention to be the most prominent deficit encountered in SD.14 The failure of attention and the possible maladaptive conse-quences of endogenous efforts to sustain wakefulness in the

Table 1. fMRI studies involving sleep deprivation

Cognitive domain ReferenceWorking memory Bell-McGinty et al.22

Habeck et al.57

Chee and Choo1

Choo et al.2

Caldwell et al.24

Mu et al.26

Mu et al.27

Chee et al.4

Thomas and Kwong39

Lim et al.6

Luber et al.28

Vandewalle et al.35

Attention (sustained or divided) Portas et al.40

Thomas et al.60

Drummond et al.25

Chee et al.8

Tucker et al.31

Attention (selective) Mander et al.33

Tomasi et al.37

Volkow et al.38

Chee et al.12

Lim et al.46

Chee and Tan11

Chee et al.15

Kong et al.16

Visual short-term memory Chee and Chuah5

Chuah and Chee9

Logical reasoning Drummond et al.23

Inhibition (Go/No-Go) Chuah et al.3

Risky decision making Venkatraman et al.7

Venkatraman et al.17

Emotional Processing Yoo et al.29

Sterpenich et al.61

Chuah et al.13

Gujar et al.32

Verbal learning/ Verbal episodic memory

Drummond et al.20

Yoo et al.34

Chuah et al.10

Default mode/Resting state Gujar et al.30

De Havas et al.18

No main effect of state

F value>20

16

12

8

4

0

Sig. main effect of state on functional connectivity

Fig. 1. Main effect of state on default mode network (DMN) func-tional connectivity. Schematic showing a significant main effect of state on DMN functional connectivity between 3 node pairs using a seed based analysis; left inferior parietal lobe (LIPL) and dorsal medial prefrontal cortex (dMPFC), LIPL and ventromedial prefron-tal cortex (vMPFC), and LIPL and posterior cingulate cortex (PCC; Bonferroni corrected p<0.05/21=0.002). Adapted from De Havas JA, Parimal S, Soon CS, Chee MW. Neuroimage 2012;59:1745-1751.18 LLTC: left lateral temporal cortex, RLTC: right lateral tem-poral cortex, RIPL: right inferior parietal lobe.

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Chee MW

face of mounting sleep pressure has been a central idea. A cog-ent illustration of the vital role played by attention in support-ing cognitive performance comes from an experiment origi-nally designed to evaluate visual working memory capacity in SD.5 Participants in this study were briefly shown an array of colored squares and seconds later had to verify if the test item was of a color shown in the array. The number of differ-ently colored squares shown varied from 1 to 8 squares. The key finding was that during SD, even when memory capacity and perceptual load were not taxed, task-related activation in brain regions mediating top-down control of attention and vi-sual perception in extrastriate visual cortex was significantly diminished (Fig. 2).

This indicated that a more global curtailment of process-ing resources rather than storage limitation was problematic. As both working memory and attention are intertwined pro-cesses and engage similar cortical and subcortical areas,58,59 the parametric variation of visual memory and visual item load across multiple levels in two parallel sets of scans were instrumental in proving the point.

Other studies probing the effects of SD on selective atten-tion used visual tracking or visual picture selection paradi-gms.12,37,46 They arrived at convergent observations regarding the attenuation of top-down control of attention together with diminished engagement of the visual extrastriate cortex. To-gether with deficits in responding to stimuli, attenuated acti-vation of fronto-parietal and visual extrastriate cortex also occurs in the preparatory period prior to stimulus appearance.15

In comparison to its effects on cortical activation the effects of SD on subcortical activation are more complex. For exam-ple, the thalamus, which plays an important role in mediat-ing arousal and attention, shows decreased glucose metabo-lism during SD if measurement is averaged over several mi-nutes.60 However, for individual events, activation can either be

higher or lower than during rested wakefulness depending on whether the sleep deprived volunteer is performing adequ-ately or lapsing.8,37

Evaluating Countermeasures

A majority of persons show decline in cognitive perform-ance after 24 h of SD. fMRI has been used to track the efficacy of countermeasures against, for example, to evaluate the effect of modafinil,39 and donepezil.9,10 In these studies, the effect of drug in the well-rested state was negligible but was evident in the sleep-deprived state in some volunteers. In the donepezil trials, improvement was positively correlated with the magni-tude of performance decline when undergoing SD on placebo in both short-term memory and episodic memory experi-ments in the same subjects. The smaller trial involving mo-dafanil evidenced increases in both cortical and subcortical activation in volunteers sleep deprived on modafanil.

Repetitive transcranial magnetic stimulation has been re-ported to improve verbal working memory in sleep deprived volunteers when applied to the right ‘upper middle occipital’ region that was part of the network associated with SD in-duced performance impairment.28 Improvement correlated with the extent to which performance declined during SD in sham stimulations. In contrast no benefit was observed when stimulating the midline parietal region, part of a network of areas showing reduced task-related activation in SD, or when the lower left middle occipital gyrus which was not part this network.

Affective Aspects of Behavior-Emotional Processing and Decision-Making

Most of the tasks used in experimental studies engage a fr-

Fig. 2. Deficits in attention underlie functional imaging changes when visual short-term memory is tested in the sleep-deprived state. Task-related activation of the intraparietal sulcus increases with memory load--but not visual item load when memory is not engaged--in both rest-ed wakefulness (RW) and sleep deprivation (SD). In the sleep-deprived state, even when visual short-term memory is not taxed (e.g., low test item load or no load on memory), decrements in activation are observed. This implicates a fundamental deficit in attention rather than one of storage capacity or memory. Adapted from Chee MW, Chuah YM. Proc Natl Acad Sci U S A 2007;104:9487-9492.5

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onto-parietal network involved in the control of attention and do not evaluate affective changes that constitute an important aspect of behavioral alteration in SD. Brain structures involved in affective processing include the amygdala, striatum, ven-tromedial prefrontal cortex and the insula. These structures can be expected to show altered activation if a state-related ch-ange in affect is present.

In one study, where participants graded the emotionality of faces, SD enhanced amygdala responses to negative pictures.29 Accompanying this change was reduced functional connec-tivity between the medial prefrontal cortex and amygdala (Fig. 3). In a second study,13 volunteers remembered neutral faces over a brief interval during which distracter pictures were pre-sented. The distractors could be neutral, negative emotional or noise patterns. Amygdala activation during the mainten-ance period was higher for emotional distracters than neutral distracters in both states although maintenance activity was overall, lower in the SD state for both conditions (Fig. 3). Face memoranda were less well maintained in working memory to the extent that SD reduced functional connectivity between ventromedial and dorsolateral frontal areas and the amygda-la.13 Responses to emotional stimuli during SD can thus be perturbed by disrupting the transmission of top-down control signals from regions involved in valuation and/or cognitive control. In one experiment, negative stimuli were better rec-ognized after SD than neutral or positive stimuli. The recol-lection of negative and positive stimuli was correlated with greater functional connectivity between medial frontal re-gions and the hippocampus when subjects had a normal night of sleep compared to when they were sleep-deprived.61

In another experiment, the bias towards processing emo-tional stimuli over neutral ones was extended to positive sti-muli. SD also caused volunteers to increase the number of neutral pictures that were rated positively.32 This finding was

related to enhanced hippocampal to medial frontal and hip-pocampal to orbitofrontal connectivity in the SD state.

Opportunities for Research

A critical gap in our current knowledge of the mechanisms underpinning altered behavior in SD lies in the piecemeal use of functional imaging in this state whereby a single cogni-tive domain is tested at a time. Behavioral studies show that SD may affect performance unevenly across different cognitive domains.62,63 It remains a open challenge to execute within-subject studies involving multiple, sensitive, short-duration, tasks that probe dissociable cognitive domains.64

While total SD is convenient to study in a laboratory setting, most persons encounter the effects of sleep loss through ch-ronic sleep restriction and sleep fragmentation.65 Partial SD studies where sleep is restricted to between 3-6 hours of time in bed per night suggest that the relationship between hours of sleep and cognition is not linear.66,67 The rate of build up of slow wave activity during sustained wakefulness and its dis-sipation following recovery sleep also does not correspond well with behavioral performance alteration suggesting that dif-ferent measures provide independent information regarding changes occurring in SD. It remains of interest to study how functional imaging changes evolve during partial SD-such studies can provide new understanding of compensatory brain network dynamics during the process of chronic partial sleep restriction.66

Imaging genomics seeks to identify genes that influence brain, cognition and risk for disease. For example, the candi-date gene approach was applied to study the effect of Per 35/5 on n-back task performance in subjects undergoing total SD. Widespread relative reductions in task related activation were found in frontal, parietal and occipital regions in this vulner-

Fig. 3. Right amygdala activity was elevated in response to emotional distracters relative to neutral distracters at rested wakefulness (RW). A state (rested wakefulness, sleep deprivation) by Condition (Neutral, Emotional) repeated-measures ANOVA conducted on averaged acti-vation within this region of interest indicated marginal decreases in amygdala activation following sleep deprivation. Critically, state-related change in amygdala activation correlated with the corresponding alteration of emotional distractibility while no parallel effect was present for neutral distracters. Adapted from Chuah LY, Dolcos F, Chen AK, Zheng H, Parimal S, Chee MW. Sleep 2010;33:1305-1313.13 BOLD: blood oxygenation level dependant.

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Emotionalr=-0.51

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able group when they were sleep deprived.35 The intriguing behavioral results were not replicated when a different set of sleep restricted (not total SD) subjects were studied leaving room for future studies to clarify.68

Sleep deprivation provides a unique opportunity to perturb brain networks of healthy individuals in a manner that degr-ades performance in a reversible manner. Several similarities between the behavioral deficits in SD and cognitive aging have been highlighted.69,70 There are also functional imaging paral-lels that remain to be exploited in future studies.1,71 The attrac-tion of this approach is that it may allow conspecific evaluation of cognitive enhancers in a relatively lower risk setting, keep-ing in mind that the target group of older adults may be less resilient to adverse effects should these occur.

AcknowledgmentsThis work was supported by grants awarded to M.C. from the Defence

Science and Technology Agency Singapore (POD0713897) and the Na-tional Research Foundation Singapore (STaR Award). Substantial portions of this review were derived from Ch. 16 of ‘Neuroimaging of Sleep and Sleep Disorders’ edited by Nofzinger, Maquet and Thorpy; Cambridge University Press 2013.

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