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Countermeasures to the neurocognitive deficits associated with sleep loss
Drug Discovery Today: Disease Models
DRUG DISCOVERY
TODAY
DISEASE
MODELS
Vol. 8, No. 4 2011
Editors-in-Chief Jan Tornell – AstraZeneca, Sweden Andrew McCulloch – University of California, SanDiego, USA
Sleep
Countermeasures to the neurocognitive deficits associated with sleep loss§ Nancy J. Wesensten1,*, John D. Hughes2, Thomas J. Balkin1 1 2
Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910-7500, USA Naval Medical Research Center, USA
Sleep loss exerts deleterious effects on nearly all aspects of neurocognitive performance evaluated to date; such effects in turn cause decreased readiness, reduced pro-
Section editor: Joel Dimsdale – Department of Psychiatry, University of California San Diego, La Jolla, CA 92093-0804, USA
ductivity and increased risk of errors and accidents. Psychostimulants help maintain neurocognitive performance during sleep loss but their effectiveness is transient, and they only delay sleep onset – they do not replace sleep. Optimizing sleep either pharmacologically or nonpharmacologically is a sustainable approach for maintaining neurocognitive performance under conditions of restricted sleep. We review these approaches and suggest avenues for further exploration, particularly with regard to nonpharmacologic augmentation of the electroencephalographic activity thought to underlie specific aspects of neurocognitive performance. Introduction – the nature of sleep loss-induced neurocognitive deficits The effect of sleep loss on neurocognitive performance in otherwise normal, healthy adults has been the subject of study for over 100 years. In that time, numerous aspects of neurocognitive performance have been evaluated to determine the extent to which they are impacted by sleep depriva§ This material has been reviewed by the Walter Reed Army Institute of Research, and there is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting the position of the Department of the Army or the Department of Defense. *Corresponding author.: N.J. Wesensten ([email protected])
1740-6757/$ .Published by Elsevier Ltd.
DOI: 10.1016/j.ddmod.2011.03.005
tion [1]. Relatively simple cognitive/psychomotor measures were employed in most early studies of sleep loss (e.g. mental addition/subtraction tasks, simple-reaction and choice-reaction time tasks and short-term memory tasks), and an acute, total sleep deprivation paradigm was utilized in almost all of these studies. In general, such studies revealed that sleep loss increases response time and errors of omission (originally thought to be the result of brief sleep episodes or ‘microsleeps’ intruding into wakefulness although they occur during electroencephalographically defined wakefulness as well). As pointed out by Horne (1993) deficits resulting from total sleep deprivation in otherwise normal, healthy volunteers resemble those seen in patients with prefrontal cortical (PFC) damage (i.e. as if sleep loss causes a temporary but reversible PFC lesion) [2]. This observation has subsequently been confirmed using functional brain imaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), which revealed that total sleep deprivation results in global brain deactivation, but with greatest levels of deactivation in the prefrontal cortex, inferior parietal/superior temporal cortex, thalamus and anterior cingulate [3]. Given the role of these brain regions (particularly the prefrontal cortex) in higher order neurocognitive functions (so-called ‘executive’ functions – e.g. planning, decision-making and goal-directed behavior), and in 139
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light of evidence that sleep loss preferentially impairs functions governed by the PFC, attention has more recently turned to cataloging and quantifying the effects of sleep loss on higher order tasks such as problem solving, risk-taking, decision-making, creative thinking and emotional processing – each of which indeed negatively impacted [4]. Not surprisingly, naturalistic studies have also shown negative effects of inadequate sleep on real-world outcomes such as medical errors [5] and automobile accidents [6]. Lack of sleep (often exacerbated by circadian factors, i.e. work during early morning hours) has been implicated in well-publicized catastrophes including the Chernobyl meltdown, the ExxonValdez oil spill, the release of poison gas in Bhopal, India, and more recently in the crash of Colgan Airlines Flight 3407. In each of these catastrophes, underlying neurocognitive deficits could best be characterized as errors of omission, narrowing of attention and/or perseveration on failed solutions – deficits known to result from sleep loss [1,2]. The most parsimonious conclusion that can be drawn from the numerous published studies on sleep loss effects and anecdotal reports is that sleep loss globally and nonspecifically impacts neurocognition. Indeed, it has been suggested that deficits in attention (which in turn are caused by reduced activation in parieto-occipital brain regions) underlie virtually all sleep loss-mediated neurocognitive deficits [7]. Although evidence for this hypothesis appears to be mixed [4], it is nevertheless clear that virtually all facets of neurocognitive functioning are impacted by sleep loss. In contrast to the numerous total sleep deprivation studies published to date, relatively few studies have addressed the neurocognitive effects of chronic, restricted sleep (‘chronic’ defined here as two or more consecutive nights and ‘restricted’ defined as less than eight hours time in bed per night). Results of the relatively few studies published to date do indicate that like acute, total sleep deprivation, chronic sleep restriction negatively impacts a wide range of neurocognitive functions, and it does so in a dose-dependent fashion [8,9]. Although there are discrepancies in the literature with respect to whether, or the extent to which, a particular neurocognitive function is impaired by sleep loss (be it total sleep deprivation or chronic sleep restriction), such discrepancies are most propably a function of methodologic differences among studies that impact the sensitivity of a given task [10]. Table 1 lists neurocognitive metrics assessed in a chronic sleep restriction paradigm and their relative sensitivity to sleep loss. Perhaps not surprisingly, and consistent with observations that psychomotor response time slows with sleep loss [1,2], highest sensitivity among measures of psychomotor performance was evident for measures involving response speed. Critically, although total sleep deprivation and chronic sleep restriction exert qualitatively similar effects on neurocognitive performance, recovery from each differs substantially: 140
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following acute, total sleep loss, one or two nights of recovery sleep is typically all that is needed to restore neurocognitive performance to well-rested (baseline) levels. In contrast, results from chronic sleep restriction studies indicate that subsequent recovery follows a slower time course in which three or more nights may be required to restore performance to well-rested levels [8,9] (Fig. 1), particularly if individuals are not fully sleepsatiated before restriction [11]. The latter findings suggest that sleep history over the past several days – or weeks – impacts current and future neurocognitive performance – that is, that chronic sleep restriction induces neurophysiologic changes that require several nights of recovery sleep to reverse. One possibility is that chronic sleep restriction leads to waning levels of extracellular adenosine in the basal forebrain coupled with increasing density (upregulation) of A1 receptors in this region – and this ratio of receptors to extracellular adenosine is what maintains the increased sleep drive/decreased capacity for neurocognitive functioning during chronic sleep restriction. Because the capacity to produce/release extracellular adenosine is rapidly restored by recovery sleep, and because it takes several days for A1 receptors to downregulate to a normal density level, recovery from chronic sleep restriction is relatively extended – that is, the result of A1 upregulationmediated super-sensitivity to the sleepiness-inducing effects of extracellular adenosine [12]. The exact relationship between (a) nightly hours of sleep/number of nights of sleep during restriction and (b) nightly hours of sleep/number of nights of sleep needed to fully recover – and the underlying neurophysiologic mechanisms governing this slow recovery – has yet to be determined. Neurocognitive responses to sleep loss vary substantially among individuals, but intraindividual responsivity appears to be trait-like: it has been shown that when exposed to repeated bouts of total sleep deprivation (separated by several weeks of recovery), individuals responded similarly both times (i.e. were either consistently vulnerable or consistently resilient to sleep loss) [13]. More recently, it was also shown that such trait-like responsivity generalizes from total sleep deprivation to chronic sleep restriction [14]. The neurobiologic underpinnings of this trait-like responsivity to sleep loss are unknown, but they may be mediated by genetic polymorphisms controlling sleep need and/or sleep timing [15]. Critically, one’s ‘neurocognitive’ vulnerability to sleep does not correlate with one’s ‘subjective’ vulnerability as measured by subjective sleepiness [13], a disparity that highlights why self-appraisals of sleepiness cannot substitute for objective assessments of neurocognitive deficits. Age appears to mediate the effects of sleep loss such that older individuals may be more resistant to sleep loss than younger individuals [16]. Finally, sleep disruption (fragmenting sleep) has much the same effect on neurocognitive performance as sleep restriction [both impact neurocognitive performance in a dosedependent fashion – i.e. higher rates of fragmentation (which
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Drug Discovery Today: Disease Models | Sleep
Table 1. Neurocognitive and other outcome measures from a chronic sleep restriction study (three, five, seven, or nine hours time in bed per night for seven nights). Measures are rank-ordered from highest to lowest sensitivity to sleep restriction. ‘Yes’ in the ‘Significant’ column indicates that the effect size for the corresponding measure was significantly greater than zero (P < 0.05). From [10], with permission Upper 95% confidence limit
Confidence interval range
Sensitivity index (ratio of effect size to interval range)
Significant
0.214
0.679
0.465
0.961
Yes
0.208
0.124
0.343
0.218
0.954
Yes
Simulated driving – lane deviation
0.186
0.063
0.378
0.315
0.591
Yes
10-Choice-reaction time – speed
0.032
0.012
0.074
0.062
0.510
Yes
Simulated driving – lane position
0.075
0.024
0.173
0.149
0.502
Yes
Wilkinson 4-choice-reaction time – speed
0.131
0.012
0.275
0.263
0.496
Yes
Stanford sleepiness scale
0.095
0.030
0.227
0.197
0.482
Yes
Serial addition subtraction – speed
0.048
0.017
0.121
0.104
0.467
Yes
10-Choice-reaction time – % correct
0.070
0.012
0.175
0.164
0.425
Yes
FIT – saccadic velocity
0.020
0.003
0.065
0.062
0.328
No
Synthetic work task
0.055
0.004
0.172
0.176
0.314
No
Simulated driving – number of accidents
0.094
0.195
0.142
0.337
0.280
No
Stroop color naming – speed
0.026
0.001
0.096
0.096
0.271
No
Stroop color naming – % correct
0.047
0.007
0.178
0.185
0.252
No
Serial addition subtraction – % correct
0.028
0.014
0.099
0.113
0.246
No
Time estimation
0.083
0.024
0.329
0.353
0.235
No
Wilkinson 4-choice-reaction time – % correct
0.034
0.012
0.134
0.147
0.231
No
FIT – latency to pupil constriction
0.012
0.003
0.048
0.052
0.229
No
FIT – impairment index
0.008
0.017
0.021
0.038
0.212
No
Running memory – % correct
0.052
0.029
0.221
0.250
0.210
No
Code substitution – speed
0.018
0.014
0.087
0.101
0.177
No
Running memory – speed
0.029
0.022
0.156
0.177
0.166
No
Logical reasoning – % correct
0.017
0.013
0.091
0.104
0.164
No
FIT – initial pupil diameter
0.000
0.002
0.001
0.003
0.139
No
FIT – amplitude of pupil constriction
0.000
0.003
0.001
0.004
0.101
No
Logical reasoning – speed
0.001
0.008
0.002
0.010
0.074
No
Outcome measure
Effect size
Sleep latency
0.447
Psychomotor Vigilance Task (PVT) – speed (1/RT)
Lower 95% confidence limit
result in decreased total sleep time) have a greater negative impact on performance] [17].
Mitigating sleep loss-induced neurocognitive deficits Stimulant effects on neurocognitive performance during sleep loss Currently, psychostimulants provide the most viable means of mitigating neurocognitive deficits associated with insufficient sleep in otherwise normal, healthy adults. Much of the relevant research to date has been focused on caffeine,
dextroamphetamine and modafinil. Caffeine (an adenosine receptor antagonist) is widely recognized as a safe and effective temporary means for reversing neurocognitive deficits associated with sleep loss [18], and its effectiveness appears to be genetically modulated [19]. Likewise, modafinil (which appears to act on multiple receptor systems [20]) is generally recognized as safe and effective, and responsivity to modafinil also appears to be genetically mediated [21]. Dextroamphetamine is effective for reversing sleep loss-induced www.drugdiscoverytoday.com
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(a)
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Adaptation and training
Sleep restriction/augmentation
Recovery
8 (h) TIB
3, 5, 7, or 9 (h) TIB
8 (h) TIB
T1
T2
B
E1 E2
E3
E4
E5
E6
E7
R1
R2 R3 Final recovery night (no testing the next day)
Days
(b) 4.50
Mean speed (1/RT*1000)
4.25 4.00 3.75 3.50 3.25 3.00
9-HR
2.75
7-HR 5-HR
2.50
3-HR
2.25 B
E1
E2
E3
E4
E5
E6
E7
R1
R2
R3
Day Drug Discovery Today: Disease Models
Figure 1. Panel (a). Study design for chronic sleep restriction study. The chronic sleep restriction phase (seven nights of three, five, seven, or nine hours time in bed [TIB]) was preceded by three nights of eight hours of sleep and followed by a recovery phase in which volunteers were allowed eight hours TIB per night for three nights. Panel (b). Psychomotor Vigilance Task (PVT) speed (1/RT 1000) for the four TIB groups across baseline (b), restriction (E1–E7) and recovery (R1–R3) phases. Note that the three, five and seven-hour TIB groups failed to fully recover even after the third recovery night. Both panels from [8], with permission.
neurocognitive deficits [18]; however, it has a less favorable abuse liability profile and it confers no additional benefits to neurocognition, compared to either caffeine or modafinil [22]. Recently, the stimulant MK-0249 (a histamine subtype-3 receptor inverse agonist currently in Phase II testing) was shown to increase alertness and improve some aspects of neurocognitive performance in sleep-deprived volunteers [23]. In short, despite differing neurophysiologic mechanisms of action, caffeine, modafinil, dextroamphetamine and MK0249 display similar neurocognitive effects, albeit with time courses that reflect their respective pharmacokinetic profiles (e.g. longer-duration effects of dextroamphetamine, modafinil and MK-0249 relative to caffeine – a feature of caffeine 142
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which may be desirable for relatively short, early morning operations). Less well studied are the effects of these compounds on various executive functions – and notably, their relative efficacy for restoring the various executive functions degraded by sleep loss. Results of two studies from our laboratory in which caffeine, modafinil and dextroamphetamine were directly compared (study 1 – results summarized in [22]; study 2 – results summarized in [4]) suggest that these stimulants variously restore some executive functions but that no single stimulant restores all functions. However, such conclusions are speculative because these studies lack the dose–response data that would allow more definitive assessment (for example in both studies from our laboratory, only a
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single dosage of each stimulant was evaluated, based on their effects on simple psychomotor speed during extended sleep loss). It may be that the dose of a given stimulant that is adequate to restore simple response speed is insufficient to restore other aspects of neurocognition. Stimulants do not replace the need for sleep, and ultimately sleep must be obtained to restore/maintain neurocognitive performance. Furthermore, chronic sleep restriction poses a more widespread problem than acute, total sleep deprivation; therefore, perhaps a better – and more sustainable – solution would be to improve the minute-by-minute recuperative value of restricted sleep. In the next sections, the feasibility of pharmacologically and nonpharmacologically enhancing the recuperative value of sleep is explored – via augmentation of polysomnographically recorded and visually scored slow-wave sleep (SWS) and electroencephalographically measured slow-wave activity (SWA).
Pharmacologically enhancing sleep’s recuperative value Evidence is accumulating that pharmacologically enhancing SWS/SWA (typically calculated as power in the 1–4 Hz range) protects against neurocognitive performance and alertness impairments normally associated with sleep restriction. In a series of studies by Walsh and colleagues, the SWS-enhancing and subsequent performance-maintaining properties of tiagabine (a GABA uptake inhibitor) [24], gaboxadol (a GABA-A agonist) [25], and sodium oxybate (gammahydroxybutyrate – a GABA-B modulator) [26] were evaluated in normal, healthy adults (these compounds also have been evaluated in healthy elderly individuals as well as elderly insomniacs, studies which are not discussed here). In the tiagabine and gaboxadol studies, volunteers underwent four nights of sleep restricted to approximately five hours per night (01:00 to approximately 06:00 – a degree of sleep restriction previously shown to degrade neurocognitive performance [8,9]). Drug or placebo was administered 30 min before lights out. Compared to baseline, tiagabine increased SWS (sum of sleep stages 3 and 4) by approximately 30 min (SWA not reported), and these increases were accompanied by next-day improvements in simple psychomotor vigilance (as measured by the Psychomotor Vigilance Task or PVT). In the gaboxadol study, gaboxadol increased SWS by just over 17 min compared to baseline, increased SWA (1–4 Hz) and 5–8 Hz activity; although PVT performance did not differ between gaboxadol and placebo, latency to sleep on the multiple sleep latency test (MSLT) was increased in the gaboxadol group. The sodium oxybate study employed a different paradigm: volunteers remained awake for two nights but were allowed a three-hour daytime (08:00– 11:00) sleep opportunity with sodium oxybate or placebo (administered 15 min before sleep) (sodium oxybate has an elimination half-life of less than one hour and therefore is suitable for use during short sleep periods). Sodium oxybate increased SWS by just over 30 min, increased SWA (1–4 Hz)
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and 5–9 Hz activity, decreased 12–13 Hz activity, improved next-day PVT performance and increased next-day sleep latency on the MSLT. Interestingly during subsequent recovery sleep, SWA (1–5 Hz) was reduced in the sodium oxybate group relative to placebo, suggesting that the increased SWA during restricted sleep served to reduce subsequent homeostatic drive during recovery. Results from these studies provide compelling evidence that under conditions of restricted sleep, waking neurocognitive performance can be improved by pharmacologically augmenting SWS/SWA. Other compounds enhance SWS/SWA in humans, including the serotonin 2A (5HT-2A) receptor antagonists ketanserin, ritanserin, seganserin and eplivanserin (reviewed in [27]). However, in most of those studies postsleep neurocognitive outcomes were not measured; therefore, the extent to which SWS augmentation benefited waking neurocognitive performance is unknown. It does not appear that the newer hypocretin receptor antagonists (which promote sleep [28]) augment SWS. Investigating the pharmacologic enhancement of SWS is hampered by several factors: first, sleep enhancement in otherwise normal, healthy adults constitute off-label use of these compounds, none of which is totally risk-free. For example, tiagabine carries a specific FDA warning regarding new onset seizures and suicidal thoughts and behaviors associated with off-label use (although neither new onset seizures nor suicidal thoughts/behavior have been reported in healthy adults such as those used in the above-indicated studies in which the compound was tested for sleep enhancement). Sodium oxybate is currently approved only for the treatment of excessive daytime sleepiness and cataplexy in patients with narcolepsy. Development of gaboxadol was cancelled in Phase III development after reports of side effects including hallucinations and disorientation during clinical trials and after the drug failed an efficacy trial. None of the 5HT-2A compounds is currently approved for use in the United States and Europe (eplivanserin was withdrawn from further development in the United States in 2009 following a letter from the FDA requesting additional risk/benefit information). Finally, as with other sleep-inducing agents such as the benzodiazepine receptor agonists zolpidem, zopiclone and temazepam, one potential disadvantage of compounds that augment SWS is impaired neurocognitive performance upon abrupt awakening (an operationally relevant issue, particularly in emergency responders). Augmenting SWS/SWA nonpharmacologically may circumvent these problems. In the next section, we explore potential nonpharmacologic means of augmenting SWS/ SWA via transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS).
Nonpharmacologically enhancing sleep’s recuperative value Within the past ten years, a slow-frequency (<1 Hz) oscillation (originally identified in animals by Steriade and colleawww.drugdiscoverytoday.com
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gues) has been characterized in the human electroencephalogram [29,30]. This neocortical-originating slow oscillation is composed of fluctuations between neuronal membrane depolarization (referred to as the ‘up’ state associated with intense cortical activity at a wide range of faster frequencies) and hyperpolarization (referred to as the ‘down’ state associated with almost complete neuronal quiescence) – fluctuations also referred to as ‘bistability’ [31]. The slow oscillation is thought to enhance the transfer of memory information from the hippocampus to the neocortex during sleep for long-term storage [29]. Figure 2 Panel (a) (from [32]) illustrates the mechanisms hypothesized to be involved in slow oscillation-mediated memory consolidation (see figure caption for detailed description). The high amplitude of electroencephalographically recorded SWA reflects robust synchronization of the slow oscillation across the cortex. Accumulating evidence from Born and colleagues suggests that enhancing the slow oscillation during sleep via TES enhances memory [29]. In a 2006 study by this group (Marshall and colleagues – reviewed in [32]), following a verbal learning (declarative memory) task, slow oscillation potential fields were induced via transcranial direct current stimulation during the early portion of nighttime sleep (Fig. 2, Panel (b) for study design). Stimulation at the slow (0.75 Hz) frequency during NREM sleep improved subsequent recall for the memory task. Subsequently, Massimini, Tononi and colleagues (reviewed in [31]) showed that TMS pulses at a rate of approximately 0.8 Hz increased SWA (an effect that was maximal when stimulation was applied to the dorsal sensorimotor cortex) – individual slow waves appeared to be identical to those spontaneously occurring in sleep. They also reported that the intensity of TMS required to exogenously elicit slow waves showed substantial interindividual variation, perhaps due to interindividual differences in extant sleep debt (the extent to which prior sleep history was controlled in that study was not reported). However, subsequent waking neurocognitive outcomes were not assessed to determine the behavioral significance of increasing SWA during sleep (the Tononi group has proposed that SWA serves to decrease synaptic strength back to baseline levels following wake-induced increases [synaptic homeostasis theory]; it follows that subsequent waking neurobehavioral performance also should benefit from such system ‘resetting’). It is not yet known whether slow oscillation enhancement during sleep facilitates other (nonmemory-related) aspects of next-day neurocognitive performance (which would be predicted by the synaptic homeostasis theory). Only a narrow range of tasks has been assessed, and it appears that procedural memory as measured by ‘tapping sequence’ or ‘mirror tracing’ tasks is not improved by augmentation of slow oscillatory activity. More intriguing – and of direct operational relevance – is the possibility that, similar to the aug144
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Figure 2. Panel (a). Proposed relationship among neocortical slow oscillations, thalamic spindles, hippocampal sharp wave-ripples and burst activity in the locus coeruleus in consolidation of memory during sleep. As per Marshall and Born, ‘the depolarizing ‘up’ phase of slow oscillations (whether endogenous or induced by stimulation) drives the replay of newly encoded memories in hippocampal circuitry (which is accompanied by sharp wave-ripples – SPW) and, in parallel, the generation of thalamic spindles and of burst activity in the locus coeruleus. This enables feedback activity from these structures, that is, hippocampal-to-neocortical replay activity, thalamo-cortical spindles and noradrenergic locus coeruleus bursts, to arrive at about the same time at the neocortex, where the co-occurrence of these inputs is probably essential for the formation of long-term memories in neocortical networks.’ Panel (b). General procedure used by Marshall and colleagues to assess memory consolidation using transcranial stimulation during sleep. PAL = paired-associates learning; MT = mirror tracing task; tDCS = transcranial direct current stimulation. Both panels from [32], with permission.
mentation of SWS/SWA seen with pharmacologic agents (described above), inducing slow oscillatory activity across a restricted period of sleep would result in the same neurocognitive benefit as a longer period of nonaugmented (naturally occurring) sleep [30]. In studies conducted to date using TES/TMS, the stimulation periods have been relatively short and have not encompassed the entire sleep period, nor has
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TES/TMS efficacy been assessed during chronic sleep restriction. Although technical issues make longer periods of stimulation more challenging (e.g. TMS coil heating), these issues can probably be overcome. In theory, all stage N2 sleep (usually comprising 50% or more of a nighttime sleep episode) could be converted to SWS via TES/TMS. A crucial question we are addressing is whether doing so enhances neurocognitive performance (or possibly even degrades aspects of neurocognitive performance thought to be supported by other sleep stages). Alternatively, it may be possible to use TES/TMS to nonpharmacologically augment oscillatory activity at other frequencies that are thought to underlie other aspects of neurocognitive performance. Although results of one recent study in which TES was used to enhance theta activity during REM (a sleep stage thought to underlie procedural memory consolidation) failed to show benefits on a procedural finger sequence tapping task and a procedural mirror drawing task [33], this line of research is worthy of further exploration. For example, enhancing REM theta activity may improve recognition memory for emotional stimuli, as suggested by results from Walker and colleagues (reviewed in [34]) in which they showed a positive correlation between right prefrontal theta power during REM and emotional memory – a possibility that we are pursuing.
Nonpharmacologically reducing sleep need A second but far more speculative avenue of exploration for maintaining neurocognitive performance under circumstances of restricted sleep involves nonpharmacologically reducing sleep need by driving slow oscillations during wakefulness itself. In the original study by Massimini and colleagues it was reported that slow waves (consisting of alternating hyperpolarization/depolarization) could not be elicited via TMS during the waking state (which they attributed to lack of bistability in thalamo-cortical circuits during waking– see [31]). The inability of TMS to generate a K-complex-like slow wave in wakefulness is likely because an induced pulse of excitation cannot produce an extensive and prolonged period of rebound hyperpolarization (due to the influence of waking cortical concentrations of acetylcholine). However, cortical neurons can probably be entrained to an applied slowly oscillating weak electrical field in the waking state: in one recent study, transcranial slow oscillatory stimulation (tSOS) applied during waking increased slow oscillations (0.4–1.2 Hz) between stimulations [35]. When applied after learning tSOS did not improve memory consolidation (verbal and nonverbal paired-associates, sequence tapping and mirror tracing); however, tSOS applied during learning improved recall both during the learning phase and during a subsequent (post-tSOS) recall trial. It should be noted, however, that performance differences between tSOS and control (sham tSOS) were relatively small, possibly due to ceiling effects – that is, under conditions of near-optimal perfor-
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mance, potential benefits of tSOS during waking (particularly without sleep debt) may not be apparent. Whether tSOS-induced SWA during waking reduces subsequent sleep need has not examined. It has been suggested that the build-up of SWA in the waking EEG during prolonged wakefulness performs the ‘surrogate’ role of sleep SWA [36]. This global increase in slower frequencies concurrently causes impaired neurocognitive performance but may represent the trade-off that allows the individual to maintain wakefulness in the face of sleep loss. We are currently pursuing the extent to which induction of slow oscillatory activity during waking reduces the homeostatic drive for subsequent sleep.
Summary and conclusions Sleep loss (whether acute total sleep loss, chronic restricted sleep, or fragmented sleep) exerts widespread negative effects on neurocognitive/neurobehavioral performance, constituting a threat to effectiveness and safety in operational environments. Stimulants can temporarily reverse sleep lossinduced deficits, but they do not reduce the eventual need for sleep. Approaches aimed at augmenting the recuperative value of available sleep afford a direct – and potentially more sustainable – means of maintaining neurocognitive performance under conditions of chronic sleep restriction. Pharmacologic approaches to augmenting slow-wave sleep during chronic sleep restriction also hold promise, but may be of relatively limited potential utility because of possible hangover effects (i.e. impaired performance upon abrupt awakening while still under the influence of the drug) – although such limitations could be reduced by developing the means to rapidly reverse their effects (not dissimilar to the full reversal of BZ receptor agonists that can be achieved by the use of the BZ receptor antagonist flumazenil). Nonpharmacologic augmentation of the recuperative value of sleep – and nonpharmacologic reduction of sleep need during wakefulness – hold promise as alternative and novel means of maintaining neurocognitive function when sleep duration and/or quality would otherwise be compromised.
Conflict of interest The authors have no conflicts of interest to disclose.
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5 Barger, L.K. et al. (2007) Impact of extended-duration shifts on medical errors, adverse events, and attentional failures. Sleep 30, 1801–1807 6 Abe, T. et al. (2010) Short sleep duration and long spells of driving are associated with the occurrence of Japanese drivers’ rear-end collisions and single-car accidents. J. Sleep Res. 19, 310–316 7 Chuah, L.Y. and Chee, M.W. (2008) Functional neuroimaging of sleep deprived healthy volunteers and persons with sleep disorders: a brief review. Ann. Acad. Med. Singapore 37, 689–694 8 Belenky, G. et al. (2003) Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose– response study. J. Sleep Res. 12, 1–12 9 Van Dongen, H.P. et al. (2003) The cumulative cost of additional wakefulness: dose–response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep 26, 117–126 10 Balkin, T.J. et al. (2004) Comparative utility of instruments for monitoring sleepiness-related performance decrements in the operational environment. J. Sleep Res. 13, 219–227 11 Rupp, T.L. et al. (2009) Banking sleep: realization of benefits during subsequent sleep restriction and recovery. Sleep 32, 311–321 12 Basheer, R. et al. (2004) Adenosine and sleep-wake regulation. Prog. Neurobiol. 73, 379–396 13 Van Dongen, H.P. et al. (2004) Systematic interindividual differences in neurobehavioral impairment from sleep loss: evidence of trait-like differential vulnerability. Sleep 27, 423–433 14 Rupp, T.L. et al. Trait-like individual differences in responses to sleep loss (manuscript in preparation) 15 Dijk, D.J. and Archer, S.N. (2010) PERIOD3, circadian phenotypes, and sleep homeostasis. Sleep Med. Rev. 14, 151–160 16 Adam, M. et al. (2006) Age-related changes in the time course of vigilant attention during 40 hours without sleep in men. Sleep 29, 55–57 17 Reynolds, A.C. and Banks, S. (2010) Total sleep deprivation, chronic sleep restriction and sleep disruption. Prog. Brain Res. 185, 91–103 18 Bonnet, M.H. et al. (2005) The use of stimulants to modify performance during sleep loss: a review by the sleep deprivation and Stimulant Task Force of the American Academy of Sleep Medicine. Sleep 28, 1163–1187 19 Landolt, H.P. (2008) Genotype-dependent differences in sleep, vigilance, and response to stimulants. Curr. Pharm. Des. 14, 3396–3407 20 Minzenberg, M.J. and Carter, C.S. (2008) Modafinil: a review of neurochemical actions and effects on cognition. Neuropsychopharmacology 33, 1477–1502
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Bodenmann, S. et al. (2009) Pharmacogenetics of modafinil after sleep loss: catechol-O-methyltransferase genotype modulates waking functions but not recovery sleep. Clin. Pharmacol. Ther. 85, 296–304 Wesensten, N.J. (2006) Effects of modafinil on cognitive performance and alertness during sleep deprivation. Curr. Pharm. Des. 12, 2457–2471 Iannone, R. et al. (2010) Acute alertness-promoting effects of a novel histamine subtype-3 receptor inverse agonist in healthy sleep-deprived male volunteers. Clin. Pharmacol. Ther. 88, 831–839 Walsh, J.K. et al. (2006) Tiagabine is associated with sustained attention during sleep restriction: evidence for the value of slow-wave sleep enhancement? Sleep 29, 433–443 Walsh, J.K. et al. (2008) Slow wave sleep enhancement with gaboxadol reduces daytime sleepiness during sleep restriction. Sleep 31, 659–672 Walsh, J.K. et al. (2010) Enhancing slow wave sleep with sodium oxybate reduces the behavioral and physiological impact of sleep loss. Sleep 33, 1217–1225 Monti, J.M. (2010) Serotonin 5-HT(2A) receptor antagonists in the treatment of insomnia: present status and future prospects. Drugs Today (Barc.) 46, 183–193 Brisbare-Roch, C. et al. (2007) RochPromotion of sleep by targeting the orexin system in rats, dogs and humans. Nat. Med. 13, 150–155 Born, J. (2010) Slow-wave sleep and the consolidation of long-term memory. World J. Biol. Psychiatry 11 (Suppl. 1), 16–21 Tononi, G. (2009) Slow wave homeostasis and synaptic plasticity. J. Clin. Sleep Med. 5 (Suppl.), S16–S19 Massimini, M. et al. (2009) Slow waves, synaptic plasticity and information processing: insights from transcranial magnetic stimulation and highdensity EEG experiments. Eur. J. Neurosci. 29, 1761–1770 Marshall, L. and Born, J. (2007) The contribution of sleep to hippocampusdependent memory consolidation. Trends Cogn. Sci. 11, 442–450 Marshall, L. et al. (2011) Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans. PLoS One 6, e16905 Walker, M.P. (2010) Sleep, memory and emotion. Prog. Brain Res. 185, 49– 68 Kirov, R. et al. (2009) Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding. Proc. Natl. Acad. Sci. U.S.A. 106, 15460–15465 Finelli, L.A. (2005) Cortical and electrographic changes. In Sleep Deprivation: Basic Science, Physiology and Behavior (Kushida, C.L., ed.), pp. 223–264, Marcel Dekker
DRUG DISCOVERY
TODAY
DISEASE
MODELS
Vol. 8, No. 4 2011
Editors-in-Chief Jan Tornell – AstraZeneca, Sweden Andrew McCulloch – University of California, SanDiego, USA
Sleep
Countermeasures to the neurocognitive deficits associated with sleep loss§ Nancy J. Wesensten1,*, John D. Hughes2, Thomas J. Balkin1 1 2
Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, 503 Robert Grant Avenue, Silver Spring, MD 20910-7500, USA Naval Medical Research Center, USA
Sleep loss exerts deleterious effects on nearly all aspects of neurocognitive performance evaluated to date; such effects in turn cause decreased readiness, reduced pro-
Section editor: Joel Dimsdale – Department of Psychiatry, University of California San Diego, La Jolla, CA 92093-0804, USA
ductivity and increased risk of errors and accidents. Psychostimulants help maintain neurocognitive performance during sleep loss but their effectiveness is transient, and they only delay sleep onset – they do not replace sleep. Optimizing sleep either pharmacologically or nonpharmacologically is a sustainable approach for maintaining neurocognitive performance under conditions of restricted sleep. We review these approaches and suggest avenues for further exploration, particularly with regard to nonpharmacologic augmentation of the electroencephalographic activity thought to underlie specific aspects of neurocognitive performance. Introduction – the nature of sleep loss-induced neurocognitive deficits The effect of sleep loss on neurocognitive performance in otherwise normal, healthy adults has been the subject of study for over 100 years. In that time, numerous aspects of neurocognitive performance have been evaluated to determine the extent to which they are impacted by sleep depriva§ This material has been reviewed by the Walter Reed Army Institute of Research, and there is no objection to its presentation and/or publication. The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting the position of the Department of the Army or the Department of Defense. *Corresponding author.: N.J. Wesensten ([email protected])
1740-6757/$ .Published by Elsevier Ltd.
DOI: 10.1016/j.ddmod.2011.03.005
tion [1]. Relatively simple cognitive/psychomotor measures were employed in most early studies of sleep loss (e.g. mental addition/subtraction tasks, simple-reaction and choice-reaction time tasks and short-term memory tasks), and an acute, total sleep deprivation paradigm was utilized in almost all of these studies. In general, such studies revealed that sleep loss increases response time and errors of omission (originally thought to be the result of brief sleep episodes or ‘microsleeps’ intruding into wakefulness although they occur during electroencephalographically defined wakefulness as well). As pointed out by Horne (1993) deficits resulting from total sleep deprivation in otherwise normal, healthy volunteers resemble those seen in patients with prefrontal cortical (PFC) damage (i.e. as if sleep loss causes a temporary but reversible PFC lesion) [2]. This observation has subsequently been confirmed using functional brain imaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), which revealed that total sleep deprivation results in global brain deactivation, but with greatest levels of deactivation in the prefrontal cortex, inferior parietal/superior temporal cortex, thalamus and anterior cingulate [3]. Given the role of these brain regions (particularly the prefrontal cortex) in higher order neurocognitive functions (so-called ‘executive’ functions – e.g. planning, decision-making and goal-directed behavior), and in 139
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light of evidence that sleep loss preferentially impairs functions governed by the PFC, attention has more recently turned to cataloging and quantifying the effects of sleep loss on higher order tasks such as problem solving, risk-taking, decision-making, creative thinking and emotional processing – each of which indeed negatively impacted [4]. Not surprisingly, naturalistic studies have also shown negative effects of inadequate sleep on real-world outcomes such as medical errors [5] and automobile accidents [6]. Lack of sleep (often exacerbated by circadian factors, i.e. work during early morning hours) has been implicated in well-publicized catastrophes including the Chernobyl meltdown, the ExxonValdez oil spill, the release of poison gas in Bhopal, India, and more recently in the crash of Colgan Airlines Flight 3407. In each of these catastrophes, underlying neurocognitive deficits could best be characterized as errors of omission, narrowing of attention and/or perseveration on failed solutions – deficits known to result from sleep loss [1,2]. The most parsimonious conclusion that can be drawn from the numerous published studies on sleep loss effects and anecdotal reports is that sleep loss globally and nonspecifically impacts neurocognition. Indeed, it has been suggested that deficits in attention (which in turn are caused by reduced activation in parieto-occipital brain regions) underlie virtually all sleep loss-mediated neurocognitive deficits [7]. Although evidence for this hypothesis appears to be mixed [4], it is nevertheless clear that virtually all facets of neurocognitive functioning are impacted by sleep loss. In contrast to the numerous total sleep deprivation studies published to date, relatively few studies have addressed the neurocognitive effects of chronic, restricted sleep (‘chronic’ defined here as two or more consecutive nights and ‘restricted’ defined as less than eight hours time in bed per night). Results of the relatively few studies published to date do indicate that like acute, total sleep deprivation, chronic sleep restriction negatively impacts a wide range of neurocognitive functions, and it does so in a dose-dependent fashion [8,9]. Although there are discrepancies in the literature with respect to whether, or the extent to which, a particular neurocognitive function is impaired by sleep loss (be it total sleep deprivation or chronic sleep restriction), such discrepancies are most propably a function of methodologic differences among studies that impact the sensitivity of a given task [10]. Table 1 lists neurocognitive metrics assessed in a chronic sleep restriction paradigm and their relative sensitivity to sleep loss. Perhaps not surprisingly, and consistent with observations that psychomotor response time slows with sleep loss [1,2], highest sensitivity among measures of psychomotor performance was evident for measures involving response speed. Critically, although total sleep deprivation and chronic sleep restriction exert qualitatively similar effects on neurocognitive performance, recovery from each differs substantially: 140
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following acute, total sleep loss, one or two nights of recovery sleep is typically all that is needed to restore neurocognitive performance to well-rested (baseline) levels. In contrast, results from chronic sleep restriction studies indicate that subsequent recovery follows a slower time course in which three or more nights may be required to restore performance to well-rested levels [8,9] (Fig. 1), particularly if individuals are not fully sleepsatiated before restriction [11]. The latter findings suggest that sleep history over the past several days – or weeks – impacts current and future neurocognitive performance – that is, that chronic sleep restriction induces neurophysiologic changes that require several nights of recovery sleep to reverse. One possibility is that chronic sleep restriction leads to waning levels of extracellular adenosine in the basal forebrain coupled with increasing density (upregulation) of A1 receptors in this region – and this ratio of receptors to extracellular adenosine is what maintains the increased sleep drive/decreased capacity for neurocognitive functioning during chronic sleep restriction. Because the capacity to produce/release extracellular adenosine is rapidly restored by recovery sleep, and because it takes several days for A1 receptors to downregulate to a normal density level, recovery from chronic sleep restriction is relatively extended – that is, the result of A1 upregulationmediated super-sensitivity to the sleepiness-inducing effects of extracellular adenosine [12]. The exact relationship between (a) nightly hours of sleep/number of nights of sleep during restriction and (b) nightly hours of sleep/number of nights of sleep needed to fully recover – and the underlying neurophysiologic mechanisms governing this slow recovery – has yet to be determined. Neurocognitive responses to sleep loss vary substantially among individuals, but intraindividual responsivity appears to be trait-like: it has been shown that when exposed to repeated bouts of total sleep deprivation (separated by several weeks of recovery), individuals responded similarly both times (i.e. were either consistently vulnerable or consistently resilient to sleep loss) [13]. More recently, it was also shown that such trait-like responsivity generalizes from total sleep deprivation to chronic sleep restriction [14]. The neurobiologic underpinnings of this trait-like responsivity to sleep loss are unknown, but they may be mediated by genetic polymorphisms controlling sleep need and/or sleep timing [15]. Critically, one’s ‘neurocognitive’ vulnerability to sleep does not correlate with one’s ‘subjective’ vulnerability as measured by subjective sleepiness [13], a disparity that highlights why self-appraisals of sleepiness cannot substitute for objective assessments of neurocognitive deficits. Age appears to mediate the effects of sleep loss such that older individuals may be more resistant to sleep loss than younger individuals [16]. Finally, sleep disruption (fragmenting sleep) has much the same effect on neurocognitive performance as sleep restriction [both impact neurocognitive performance in a dosedependent fashion – i.e. higher rates of fragmentation (which
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Drug Discovery Today: Disease Models | Sleep
Table 1. Neurocognitive and other outcome measures from a chronic sleep restriction study (three, five, seven, or nine hours time in bed per night for seven nights). Measures are rank-ordered from highest to lowest sensitivity to sleep restriction. ‘Yes’ in the ‘Significant’ column indicates that the effect size for the corresponding measure was significantly greater than zero (P < 0.05). From [10], with permission Upper 95% confidence limit
Confidence interval range
Sensitivity index (ratio of effect size to interval range)
Significant
0.214
0.679
0.465
0.961
Yes
0.208
0.124
0.343
0.218
0.954
Yes
Simulated driving – lane deviation
0.186
0.063
0.378
0.315
0.591
Yes
10-Choice-reaction time – speed
0.032
0.012
0.074
0.062
0.510
Yes
Simulated driving – lane position
0.075
0.024
0.173
0.149
0.502
Yes
Wilkinson 4-choice-reaction time – speed
0.131
0.012
0.275
0.263
0.496
Yes
Stanford sleepiness scale
0.095
0.030
0.227
0.197
0.482
Yes
Serial addition subtraction – speed
0.048
0.017
0.121
0.104
0.467
Yes
10-Choice-reaction time – % correct
0.070
0.012
0.175
0.164
0.425
Yes
FIT – saccadic velocity
0.020
0.003
0.065
0.062
0.328
No
Synthetic work task
0.055
0.004
0.172
0.176
0.314
No
Simulated driving – number of accidents
0.094
0.195
0.142
0.337
0.280
No
Stroop color naming – speed
0.026
0.001
0.096
0.096
0.271
No
Stroop color naming – % correct
0.047
0.007
0.178
0.185
0.252
No
Serial addition subtraction – % correct
0.028
0.014
0.099
0.113
0.246
No
Time estimation
0.083
0.024
0.329
0.353
0.235
No
Wilkinson 4-choice-reaction time – % correct
0.034
0.012
0.134
0.147
0.231
No
FIT – latency to pupil constriction
0.012
0.003
0.048
0.052
0.229
No
FIT – impairment index
0.008
0.017
0.021
0.038
0.212
No
Running memory – % correct
0.052
0.029
0.221
0.250
0.210
No
Code substitution – speed
0.018
0.014
0.087
0.101
0.177
No
Running memory – speed
0.029
0.022
0.156
0.177
0.166
No
Logical reasoning – % correct
0.017
0.013
0.091
0.104
0.164
No
FIT – initial pupil diameter
0.000
0.002
0.001
0.003
0.139
No
FIT – amplitude of pupil constriction
0.000
0.003
0.001
0.004
0.101
No
Logical reasoning – speed
0.001
0.008
0.002
0.010
0.074
No
Outcome measure
Effect size
Sleep latency
0.447
Psychomotor Vigilance Task (PVT) – speed (1/RT)
Lower 95% confidence limit
result in decreased total sleep time) have a greater negative impact on performance] [17].
Mitigating sleep loss-induced neurocognitive deficits Stimulant effects on neurocognitive performance during sleep loss Currently, psychostimulants provide the most viable means of mitigating neurocognitive deficits associated with insufficient sleep in otherwise normal, healthy adults. Much of the relevant research to date has been focused on caffeine,
dextroamphetamine and modafinil. Caffeine (an adenosine receptor antagonist) is widely recognized as a safe and effective temporary means for reversing neurocognitive deficits associated with sleep loss [18], and its effectiveness appears to be genetically modulated [19]. Likewise, modafinil (which appears to act on multiple receptor systems [20]) is generally recognized as safe and effective, and responsivity to modafinil also appears to be genetically mediated [21]. Dextroamphetamine is effective for reversing sleep loss-induced www.drugdiscoverytoday.com
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(a)
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Adaptation and training
Sleep restriction/augmentation
Recovery
8 (h) TIB
3, 5, 7, or 9 (h) TIB
8 (h) TIB
T1
T2
B
E1 E2
E3
E4
E5
E6
E7
R1
R2 R3 Final recovery night (no testing the next day)
Days
(b) 4.50
Mean speed (1/RT*1000)
4.25 4.00 3.75 3.50 3.25 3.00
9-HR
2.75
7-HR 5-HR
2.50
3-HR
2.25 B
E1
E2
E3
E4
E5
E6
E7
R1
R2
R3
Day Drug Discovery Today: Disease Models
Figure 1. Panel (a). Study design for chronic sleep restriction study. The chronic sleep restriction phase (seven nights of three, five, seven, or nine hours time in bed [TIB]) was preceded by three nights of eight hours of sleep and followed by a recovery phase in which volunteers were allowed eight hours TIB per night for three nights. Panel (b). Psychomotor Vigilance Task (PVT) speed (1/RT 1000) for the four TIB groups across baseline (b), restriction (E1–E7) and recovery (R1–R3) phases. Note that the three, five and seven-hour TIB groups failed to fully recover even after the third recovery night. Both panels from [8], with permission.
neurocognitive deficits [18]; however, it has a less favorable abuse liability profile and it confers no additional benefits to neurocognition, compared to either caffeine or modafinil [22]. Recently, the stimulant MK-0249 (a histamine subtype-3 receptor inverse agonist currently in Phase II testing) was shown to increase alertness and improve some aspects of neurocognitive performance in sleep-deprived volunteers [23]. In short, despite differing neurophysiologic mechanisms of action, caffeine, modafinil, dextroamphetamine and MK0249 display similar neurocognitive effects, albeit with time courses that reflect their respective pharmacokinetic profiles (e.g. longer-duration effects of dextroamphetamine, modafinil and MK-0249 relative to caffeine – a feature of caffeine 142
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which may be desirable for relatively short, early morning operations). Less well studied are the effects of these compounds on various executive functions – and notably, their relative efficacy for restoring the various executive functions degraded by sleep loss. Results of two studies from our laboratory in which caffeine, modafinil and dextroamphetamine were directly compared (study 1 – results summarized in [22]; study 2 – results summarized in [4]) suggest that these stimulants variously restore some executive functions but that no single stimulant restores all functions. However, such conclusions are speculative because these studies lack the dose–response data that would allow more definitive assessment (for example in both studies from our laboratory, only a
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single dosage of each stimulant was evaluated, based on their effects on simple psychomotor speed during extended sleep loss). It may be that the dose of a given stimulant that is adequate to restore simple response speed is insufficient to restore other aspects of neurocognition. Stimulants do not replace the need for sleep, and ultimately sleep must be obtained to restore/maintain neurocognitive performance. Furthermore, chronic sleep restriction poses a more widespread problem than acute, total sleep deprivation; therefore, perhaps a better – and more sustainable – solution would be to improve the minute-by-minute recuperative value of restricted sleep. In the next sections, the feasibility of pharmacologically and nonpharmacologically enhancing the recuperative value of sleep is explored – via augmentation of polysomnographically recorded and visually scored slow-wave sleep (SWS) and electroencephalographically measured slow-wave activity (SWA).
Pharmacologically enhancing sleep’s recuperative value Evidence is accumulating that pharmacologically enhancing SWS/SWA (typically calculated as power in the 1–4 Hz range) protects against neurocognitive performance and alertness impairments normally associated with sleep restriction. In a series of studies by Walsh and colleagues, the SWS-enhancing and subsequent performance-maintaining properties of tiagabine (a GABA uptake inhibitor) [24], gaboxadol (a GABA-A agonist) [25], and sodium oxybate (gammahydroxybutyrate – a GABA-B modulator) [26] were evaluated in normal, healthy adults (these compounds also have been evaluated in healthy elderly individuals as well as elderly insomniacs, studies which are not discussed here). In the tiagabine and gaboxadol studies, volunteers underwent four nights of sleep restricted to approximately five hours per night (01:00 to approximately 06:00 – a degree of sleep restriction previously shown to degrade neurocognitive performance [8,9]). Drug or placebo was administered 30 min before lights out. Compared to baseline, tiagabine increased SWS (sum of sleep stages 3 and 4) by approximately 30 min (SWA not reported), and these increases were accompanied by next-day improvements in simple psychomotor vigilance (as measured by the Psychomotor Vigilance Task or PVT). In the gaboxadol study, gaboxadol increased SWS by just over 17 min compared to baseline, increased SWA (1–4 Hz) and 5–8 Hz activity; although PVT performance did not differ between gaboxadol and placebo, latency to sleep on the multiple sleep latency test (MSLT) was increased in the gaboxadol group. The sodium oxybate study employed a different paradigm: volunteers remained awake for two nights but were allowed a three-hour daytime (08:00– 11:00) sleep opportunity with sodium oxybate or placebo (administered 15 min before sleep) (sodium oxybate has an elimination half-life of less than one hour and therefore is suitable for use during short sleep periods). Sodium oxybate increased SWS by just over 30 min, increased SWA (1–4 Hz)
Drug Discovery Today: Disease Models | Sleep
and 5–9 Hz activity, decreased 12–13 Hz activity, improved next-day PVT performance and increased next-day sleep latency on the MSLT. Interestingly during subsequent recovery sleep, SWA (1–5 Hz) was reduced in the sodium oxybate group relative to placebo, suggesting that the increased SWA during restricted sleep served to reduce subsequent homeostatic drive during recovery. Results from these studies provide compelling evidence that under conditions of restricted sleep, waking neurocognitive performance can be improved by pharmacologically augmenting SWS/SWA. Other compounds enhance SWS/SWA in humans, including the serotonin 2A (5HT-2A) receptor antagonists ketanserin, ritanserin, seganserin and eplivanserin (reviewed in [27]). However, in most of those studies postsleep neurocognitive outcomes were not measured; therefore, the extent to which SWS augmentation benefited waking neurocognitive performance is unknown. It does not appear that the newer hypocretin receptor antagonists (which promote sleep [28]) augment SWS. Investigating the pharmacologic enhancement of SWS is hampered by several factors: first, sleep enhancement in otherwise normal, healthy adults constitute off-label use of these compounds, none of which is totally risk-free. For example, tiagabine carries a specific FDA warning regarding new onset seizures and suicidal thoughts and behaviors associated with off-label use (although neither new onset seizures nor suicidal thoughts/behavior have been reported in healthy adults such as those used in the above-indicated studies in which the compound was tested for sleep enhancement). Sodium oxybate is currently approved only for the treatment of excessive daytime sleepiness and cataplexy in patients with narcolepsy. Development of gaboxadol was cancelled in Phase III development after reports of side effects including hallucinations and disorientation during clinical trials and after the drug failed an efficacy trial. None of the 5HT-2A compounds is currently approved for use in the United States and Europe (eplivanserin was withdrawn from further development in the United States in 2009 following a letter from the FDA requesting additional risk/benefit information). Finally, as with other sleep-inducing agents such as the benzodiazepine receptor agonists zolpidem, zopiclone and temazepam, one potential disadvantage of compounds that augment SWS is impaired neurocognitive performance upon abrupt awakening (an operationally relevant issue, particularly in emergency responders). Augmenting SWS/SWA nonpharmacologically may circumvent these problems. In the next section, we explore potential nonpharmacologic means of augmenting SWS/ SWA via transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS).
Nonpharmacologically enhancing sleep’s recuperative value Within the past ten years, a slow-frequency (<1 Hz) oscillation (originally identified in animals by Steriade and colleawww.drugdiscoverytoday.com
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gues) has been characterized in the human electroencephalogram [29,30]. This neocortical-originating slow oscillation is composed of fluctuations between neuronal membrane depolarization (referred to as the ‘up’ state associated with intense cortical activity at a wide range of faster frequencies) and hyperpolarization (referred to as the ‘down’ state associated with almost complete neuronal quiescence) – fluctuations also referred to as ‘bistability’ [31]. The slow oscillation is thought to enhance the transfer of memory information from the hippocampus to the neocortex during sleep for long-term storage [29]. Figure 2 Panel (a) (from [32]) illustrates the mechanisms hypothesized to be involved in slow oscillation-mediated memory consolidation (see figure caption for detailed description). The high amplitude of electroencephalographically recorded SWA reflects robust synchronization of the slow oscillation across the cortex. Accumulating evidence from Born and colleagues suggests that enhancing the slow oscillation during sleep via TES enhances memory [29]. In a 2006 study by this group (Marshall and colleagues – reviewed in [32]), following a verbal learning (declarative memory) task, slow oscillation potential fields were induced via transcranial direct current stimulation during the early portion of nighttime sleep (Fig. 2, Panel (b) for study design). Stimulation at the slow (0.75 Hz) frequency during NREM sleep improved subsequent recall for the memory task. Subsequently, Massimini, Tononi and colleagues (reviewed in [31]) showed that TMS pulses at a rate of approximately 0.8 Hz increased SWA (an effect that was maximal when stimulation was applied to the dorsal sensorimotor cortex) – individual slow waves appeared to be identical to those spontaneously occurring in sleep. They also reported that the intensity of TMS required to exogenously elicit slow waves showed substantial interindividual variation, perhaps due to interindividual differences in extant sleep debt (the extent to which prior sleep history was controlled in that study was not reported). However, subsequent waking neurocognitive outcomes were not assessed to determine the behavioral significance of increasing SWA during sleep (the Tononi group has proposed that SWA serves to decrease synaptic strength back to baseline levels following wake-induced increases [synaptic homeostasis theory]; it follows that subsequent waking neurobehavioral performance also should benefit from such system ‘resetting’). It is not yet known whether slow oscillation enhancement during sleep facilitates other (nonmemory-related) aspects of next-day neurocognitive performance (which would be predicted by the synaptic homeostasis theory). Only a narrow range of tasks has been assessed, and it appears that procedural memory as measured by ‘tapping sequence’ or ‘mirror tracing’ tasks is not improved by augmentation of slow oscillatory activity. More intriguing – and of direct operational relevance – is the possibility that, similar to the aug144
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Figure 2. Panel (a). Proposed relationship among neocortical slow oscillations, thalamic spindles, hippocampal sharp wave-ripples and burst activity in the locus coeruleus in consolidation of memory during sleep. As per Marshall and Born, ‘the depolarizing ‘up’ phase of slow oscillations (whether endogenous or induced by stimulation) drives the replay of newly encoded memories in hippocampal circuitry (which is accompanied by sharp wave-ripples – SPW) and, in parallel, the generation of thalamic spindles and of burst activity in the locus coeruleus. This enables feedback activity from these structures, that is, hippocampal-to-neocortical replay activity, thalamo-cortical spindles and noradrenergic locus coeruleus bursts, to arrive at about the same time at the neocortex, where the co-occurrence of these inputs is probably essential for the formation of long-term memories in neocortical networks.’ Panel (b). General procedure used by Marshall and colleagues to assess memory consolidation using transcranial stimulation during sleep. PAL = paired-associates learning; MT = mirror tracing task; tDCS = transcranial direct current stimulation. Both panels from [32], with permission.
mentation of SWS/SWA seen with pharmacologic agents (described above), inducing slow oscillatory activity across a restricted period of sleep would result in the same neurocognitive benefit as a longer period of nonaugmented (naturally occurring) sleep [30]. In studies conducted to date using TES/TMS, the stimulation periods have been relatively short and have not encompassed the entire sleep period, nor has
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TES/TMS efficacy been assessed during chronic sleep restriction. Although technical issues make longer periods of stimulation more challenging (e.g. TMS coil heating), these issues can probably be overcome. In theory, all stage N2 sleep (usually comprising 50% or more of a nighttime sleep episode) could be converted to SWS via TES/TMS. A crucial question we are addressing is whether doing so enhances neurocognitive performance (or possibly even degrades aspects of neurocognitive performance thought to be supported by other sleep stages). Alternatively, it may be possible to use TES/TMS to nonpharmacologically augment oscillatory activity at other frequencies that are thought to underlie other aspects of neurocognitive performance. Although results of one recent study in which TES was used to enhance theta activity during REM (a sleep stage thought to underlie procedural memory consolidation) failed to show benefits on a procedural finger sequence tapping task and a procedural mirror drawing task [33], this line of research is worthy of further exploration. For example, enhancing REM theta activity may improve recognition memory for emotional stimuli, as suggested by results from Walker and colleagues (reviewed in [34]) in which they showed a positive correlation between right prefrontal theta power during REM and emotional memory – a possibility that we are pursuing.
Nonpharmacologically reducing sleep need A second but far more speculative avenue of exploration for maintaining neurocognitive performance under circumstances of restricted sleep involves nonpharmacologically reducing sleep need by driving slow oscillations during wakefulness itself. In the original study by Massimini and colleagues it was reported that slow waves (consisting of alternating hyperpolarization/depolarization) could not be elicited via TMS during the waking state (which they attributed to lack of bistability in thalamo-cortical circuits during waking– see [31]). The inability of TMS to generate a K-complex-like slow wave in wakefulness is likely because an induced pulse of excitation cannot produce an extensive and prolonged period of rebound hyperpolarization (due to the influence of waking cortical concentrations of acetylcholine). However, cortical neurons can probably be entrained to an applied slowly oscillating weak electrical field in the waking state: in one recent study, transcranial slow oscillatory stimulation (tSOS) applied during waking increased slow oscillations (0.4–1.2 Hz) between stimulations [35]. When applied after learning tSOS did not improve memory consolidation (verbal and nonverbal paired-associates, sequence tapping and mirror tracing); however, tSOS applied during learning improved recall both during the learning phase and during a subsequent (post-tSOS) recall trial. It should be noted, however, that performance differences between tSOS and control (sham tSOS) were relatively small, possibly due to ceiling effects – that is, under conditions of near-optimal perfor-
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mance, potential benefits of tSOS during waking (particularly without sleep debt) may not be apparent. Whether tSOS-induced SWA during waking reduces subsequent sleep need has not examined. It has been suggested that the build-up of SWA in the waking EEG during prolonged wakefulness performs the ‘surrogate’ role of sleep SWA [36]. This global increase in slower frequencies concurrently causes impaired neurocognitive performance but may represent the trade-off that allows the individual to maintain wakefulness in the face of sleep loss. We are currently pursuing the extent to which induction of slow oscillatory activity during waking reduces the homeostatic drive for subsequent sleep.
Summary and conclusions Sleep loss (whether acute total sleep loss, chronic restricted sleep, or fragmented sleep) exerts widespread negative effects on neurocognitive/neurobehavioral performance, constituting a threat to effectiveness and safety in operational environments. Stimulants can temporarily reverse sleep lossinduced deficits, but they do not reduce the eventual need for sleep. Approaches aimed at augmenting the recuperative value of available sleep afford a direct – and potentially more sustainable – means of maintaining neurocognitive performance under conditions of chronic sleep restriction. Pharmacologic approaches to augmenting slow-wave sleep during chronic sleep restriction also hold promise, but may be of relatively limited potential utility because of possible hangover effects (i.e. impaired performance upon abrupt awakening while still under the influence of the drug) – although such limitations could be reduced by developing the means to rapidly reverse their effects (not dissimilar to the full reversal of BZ receptor agonists that can be achieved by the use of the BZ receptor antagonist flumazenil). Nonpharmacologic augmentation of the recuperative value of sleep – and nonpharmacologic reduction of sleep need during wakefulness – hold promise as alternative and novel means of maintaining neurocognitive function when sleep duration and/or quality would otherwise be compromised.
Conflict of interest The authors have no conflicts of interest to disclose.
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