This is not an Industry sponsored study. The authors have declared that no competing interests exist.
Conceived and designed the experiments: DJD JAG SNA MvS. Performed the experiments: JCL NS ELA ASL SH. Analyzed the data: JCL ELA. Wrote the paper: DJD JL JAG NS ELA ASL SH MvS SNA.
Cognitive performance deteriorates during extended wakefulness and circadian phase misalignment, and some individuals are more affected than others. Whether performance is affected similarly across cognitive domains, or whether cognitive processes involving Executive Functions are more sensitive to sleep and circadian misalignment than Alertness and Sustained Attention, is a matter of debate.
We conducted a 2 × 12-day laboratory protocol to characterize the interaction of repeated partial and acute total sleep deprivation and circadian phase on performance across seven cognitive domains in 36 individuals (18 males; mean ± SD of age = 27.6±4.0 years). The sample was stratified for the rs57875989 polymorphism in
Sleep loss has a primary effect on Sleepiness and Sustained Attention with much smaller effects on challenging Working Memory tasks. These findings have implications for understanding how sleep debt and circadian rhythmicity interact to determine waking performance across cognitive domains and individuals.
How sleep loss and circadian clocks affect brain function is a question with topical relevance because of the negative consequences of inadequate sleep and circadian disruption on health and cognition
These experiments have established that performance at any given time is determined by an interaction of the duration of the preceding wake episode, the chronic sleep debt carried by the individual, as well as the circadian phase at which performance is assessed. Nevertheless, several issues central to a basic understanding of the modulation of cognitive performance by the sleep-wake cycle and circadian rhythmicity remain unresolved - not least whether the cognitive control processes underpinning the tasks used in these studies are all similarly affected by sleep history and circadian phase. Such underpinning control processes allow us to determine and achieve task goals
Tasks that rely on executive processes (e.g. Response Selection and Inhibition) have been reported to be particularly disrupted by sleep deprivation and this has led to the notion that Executive Functions are particularly sensitive to sleep loss
However, these previous experiments have limitations, including the lack of simultaneous repeated assessment of Sustained Attention and Executive Functions. Multiple assessments of Executive Functions in sleep deprivation studies are rarely undertaken
We designed an experiment in which we combined repeated PSD and acute TSD and assessments of performance across the entire circadian cycle to investigate whether cognitive domains such as Alertness, Sustained Attention, Working Memory/Executive Functions, as well as Motor and Temporal Control were differentially affected. Executive functions were assessed by using Working Memory tasks (n-back tasks) which maintain the requirement for effective use of core executive processes even after repeated assessment
Thirty-six healthy young men and women (see
Participants repeatedly performed a test battery throughout the protocol (
Subjective Alertness, i.e. the reverse of the participants’ scores on the Karolinska Sleepiness Scale
Sustained Attention was assessed with the Psychomotor Vigilance Task (PVT)
We assessed Working Memory and Executive Functions with verbal n-back tasks in which participants repeatedly compare the current stimulus with the one presented 1 to 3 items before. As task difficulty increases from 1- to 3-back, so does the load on the three components of Executive Functions, i.e. updating of maintained information, task switching (e.g. between updating and memory comparison), and response selection
For the statistical evaluation of these effects and for the comparison of the size of the effects across tasks, we first analysed all segments of the protocol combined (i.e. baseline, D1–D6, TD1, TN1, and TD2; see
We next determined whether repeated PSD and acute TSD had differential effects on performance by contrasting effects in different segments of the protocol. The effect of
When we contrasted all the 52 performance measures of the seven cognitive domains between the Control and the SR conditions, we found a near linear increase in the effect of repeated PSD from D1 to D6 (
To further examine the differential effects of repeated PSD on Sustained Attention and Executive Functions, we contrasted the change of performance at the end of the sleep history manipulation period relative to the baseline day (i.e. D6/baseline) in the SR and the Control conditions. After six nights of restricted sleep opportunities, PVT performance was at a 79.86±1.04% (mean speed of the slowest 10% responses ± SEM) level relative to baseline, while at the end of the Control period, performance was at a 93.38±1.04% level, and these changes in performance across the sleep history manipulation period differed between the two conditions (
The effect of
To further investigate the differential effects of acute TSD on Sustained Attention and Executive Functions, we contrasted the change of performance on the second relative to the first day of the TSD period (i.e. TD2/TD1) in the SR and the Control conditions. Relative to the first day of TSD, PVT speed on the second day was reduced by about 50% in both the SR and the Control conditions (mean ± SEM: 46.28±1.08% vs. 49.46±1.08%,
We also evaluated the effects of TSD on performance during the
This indicates the robustness of these differential effects of sleep deprivation on various cognitive domains.
The effects of repeated PSD and acute TSD were computed for other measures of these tasks, e.g. lapses of attention and speed on the 10% fastest response in the PVT, errors of omission and commission of the SART, as well as tasks including measures of Motor and Temporal Control and subjective assessments of Workload (see
The three
The time course for selected performance measures throughout the protocols was assessed separately for the three genotypes. When the entire protocol was considered, there was no significant effect of Genotype on Subjective Alertness, but the interaction between Genotype and Condition was significant (
Comparison of the effect size of the interaction between Genotype and Condition across these tasks indicates that when all segments of the protocol are considered, Subjective Alertness and verbal 3-back performance during sleep loss were most influenced by Genotype (
Analyses conducted separately for the effects of repeated PSD and acute TSD revealed that whereas the Genotype effect on Subjective Alertness was more pronounced for PSD (
Please note that even in the
Circadian rhythmicity itself was affected by PSD. After repeated PSD, the circadian rhythm of melatonin was delayed by 45 minutes (mean ± standard error of dim light melatonin onset [DLMO]: 00∶13±00∶15 vs. 23∶28±00∶15; main effect of Condition:
Prominent circadian variation was observed for Subjective Alertness, Sustained Attention, and Working Memory during the TSD period (
Time course of
For the Working Memory performance measures, pairwise comparisons of performance per circadian bin suggest that significant effects of prior PSD were mainly observed in the initial part of the TSD period and during the biological night at DLMO +4 h (
Averaging the effects sizes of prior PSD across these cognitive domains but separately per circadian phase bin revealed the general pattern of largest effects in the morning and afternoon during the initial hours of TSD, followed by a decline of the effects with a minimum in the evening hours at around the DLMO, followed by a sudden subsequent increase during the biological night (
The protocol allowed for a comprehensive assessment of the interaction of circadian rhythmicity, chronic partial and acute total sleep loss, and
The longer TST during recovery sleep after Sleep Restriction relative to the Control conditions (
The data reported above provide several indications for the validity of our performance measures. The magnitude of changes in Subjective Alertness observed in the current study, are comparable to previous reports
In the present study, we compared the effects of sleep deprivation across tasks carefully selected to recruit different cognitive domains. These tasks have been widely used in cognitive research, in both laboratory and neuroimaging studies, as well as in sleep research. We used multiple tasks, with known redundancies and partial functional overlaps (e.g. 1-back verbal, spatial, visual, integrated spatial and visual) in order to counter the inherent difficulty with cognitive tasks that no task is ‘process pure’. That is, even apparently simple tasks may depend upon multiple simple processes. These simpler processes are themselves more or less influential in performance as tasks are, wittingly or otherwise, performed differently by participants on different occasions (e.g. context, time-pressure, practice, speed-accuracy trade-offs, feedback, reward, etc.). By using multiple tasks that had been extensively practiced, and almost all of which are externally paced, with minimal direct knowledge of results, we believe we can minimise many of these unwanted sources of performance variability. Our multi-task approach provides an alternative to other approaches in which the effects of sleep deprivation are investigated on the cognitive components of a single task, the interaction between which is prey to all of the influences identified above
Computation of effect sizes
Meta-analyses of studies on the effects of acute TSD on accuracy and speed measures of performance across a wide range of cognitive domains indicated that Sustained Attention was particularly affected, although only few studies included in the meta-analyses used n-back tasks
We used effects sizes, which are widely used in the psychological literature and also in meta-analyses, as our primary tool to compare the effects of sleep deprivation across tasks. The validity of this choice was confirmed by computing relative changes in performance for some of the tasks and these measures also showed that Sustained Attention task was more affected than Working Memory task even when implemented with a high executive load. In the current protocol, we also directly compared the effects of PSD and TSD and across many different tasks, thereby providing yardsticks both within and across tasks. Effect sizes, although useful in comparing across tasks, interventions, and studies, do, of course, not inform about the ‘clinical’ significance of the effect. This would require comparing the effects of sleep loss on tasks to the effects observed in specific patient populations, or using tasks that have in a quantitative way been correlated with performance in the real world.
In our protocol, sleep restriction was accomplished by a symmetrical change in bedtime and wake time because we wanted to keep the centre of light exposure unchanged and thereby minimise circadian phase shifts. Nevertheless, repeated PSD led to a delay of the melatonin rhythm. This finding provides further evidence
The effects of sleep history were greatest in the initial part of the acute TSD, became progressively smaller and then increased again during the biological night. In our protocol, sleep restriction was accomplished by a symmetrical change in bed time and wake time; hence, compared to the Control condition, in the SR condition, wake time occurred at an earlier clock time (2 h) and at any given clock time, participants had been awake for a longer duration. This can, however, not be the only explanation for the time course of the effects of sleep history because even we compared a Sleep Restriction observation at for example 12∶00 to a Control observation at 16∶00, Alertness in the SR condition was still poorer (see
At baseline, no differences in performance between the
Impairments in performance induced by sleep deprivation have been interpreted within various frameworks, such as the ‘neuropsychological hypothesis’, the ‘vigilance hypothesis’, and the ‘controlled attention hypothesis’
The ‘vigilance hypothesis’ states that Sustained Attention is much affected by sleep deprivation and that Sustained Attention is very important to higher aspects of cognition
By contrast, our data may seem to favour, to some extent, the ‘controlled attention hypothesis’
The observed small deficits after sleep deprivation in more demanding or engaging tasks, the self-reported effort to perform these tasks, and fMRI data
Our data show that the extent to which acute TSD leads to deterioration in performance depends on the task domain, prior sleep debt, circadian phase at which performance is assessed, and genetically-determined subject characteristics. Careful consideration of the task characteristics in real life working conditions during night shifts and sustained operations may reduce the risks of performance failures.
Our paradigm clearly demonstrates an interaction between the circadian and the homeostatic processes in regulating cognitive performance and implies that Sustained Attention and subjective measures of Alertness and Workload are most affected by both chronic sleep restriction and acute total sleep loss. The contribution of the circadian process was assessed during the acute TSD period. The time course of performance, with a minimum early in the morning and some indications of recovery during the next day clearly indicates the contribution of circadian processes. However, during TSD, both time awake and circadian phase change simultaneously and this paradigm does not allow the examination of the individual contribution of circadian rhythmicity and the sleep homeostat to cognitive performance. The separate contribution of circadian rhythmicity and sleep homeostasis can be assessed in forced desynchrony protocols
In addition, the differences in effect sizes between tasks may be related to the cognitive domain targeted by a specific task, but may, of course, also be related to other aspects of the task such as its duration. Future studies in which time on task effects are analysed across cognitive domains may be of interest.
The present study consisted of three phases: (1) telephone screening and screening visit, (2) pre-laboratory field study, and (3) laboratory study. Participants were recruited through flyers, emails, and newspaper and radio advertisements. Out of the 358 individuals who were successfully genotyped after the screening visit, 165 (46.1%) were
This sample consisted of 12
Note that this sample was independent of the sample used in our previous behaviour study
Genotyping was conducted as described previously
In the two-week period prior to the first laboratory session, participants completed a Karolinska Sleep Diary
This study was conducted at the Surrey Clinical Research Centre. This study adopted a balanced, cross-over design and consisted of two 12-day, i.e. 11-night, laboratory sessions in which the duration of sleep opportunity was manipulated. The order of experimental conditions was counter-balanced across participants, and the two laboratory sessions were at least 10 days apart. Both laboratory sessions started with a habituation night and a baseline night with 8-h time in bed (TIB;
During the adaptation, baseline, Control, and SR days, participants stayed indoors and no visitors were allowed. Apart from the time when cognitive performance was assessed, participants spent the majority of their waking hours in the volunteer lounge where they could interact with the staff and other participants, watch TV, listen to music, read, and play board games. In addition to normal indoor lightings, participants were also exposed to indirect natural sunlight through the windows of the volunteer lounge. Three main meals and an evening snack were served each day, and participants had free access to water and fruits (apples and pears). Napping and strenuous physical exercise were not allowed.
Total Sleep Deprivation (TSD): Upon awakening from the last 10-h or 6-h sleep episode, participants stayed awake for 39 h in the Control condition and 41 h in the SR condition under constant routine (CR) conditions modified from
A cognitive performance test battery was administered 7–8 times in total on the first two days of each laboratory session to familiarize participants with the cognitive tasks and minimize any effect of practice and learning on performance on subsequent days. On the baseline, and each Control and SR day, the test battery was administered five times which were evenly distributed across the waking episodes. During the TSD period, the test battery was presented every 2 h starting from two hours after scheduled wake time. The test battery were administered on identical computers with screen refresh rates of 60 Hz and running Active X, C#, and Exactics code to control stimulus presentation and its timing, and response detection and timing. Each test battery lasted for approximately 40 minutes. In the main text of this paper, we report the data from the Karolinska Sleepiness Scale (KSS)
The KSS assessed level of subjective sleepiness. Participants were required to rate how sleepy they were at the beginning and the end of the test battery on a 9-point Likert scale (1: very alert; 9: very sleepy, great effort to keep awake). In the main text, we focused on the first KSS score collected in the test battery.
The PVT assessed level of Sustained Attention. A counter in the middle of the computer screen started counting at random intervals which varied from 2,000 ms to 10,000 ms, and participants were required to respond with a mouse click as quickly as possible. In order to minimize the number of microsleep during this task in the TSD period, a beep was presented to alert the participants if no response was detected 6,000 ms after stimulus presentation. This task lasted for 10 minutes. The inverse of the reaction time of the 10% slowest responses and the number of lapses, i.e. responses with reaction time >500 ms, were used to indicate level of Sustained Attention since these measures are considered to be sensitive to both chronic and acute sleep deprivation
Sustained Attention was also assessed with the SART. A series of numbers from 0 to 9 was presented to the participants who were required to make a mouse click in every trial except when the target number, i.e. 8, was presented when they needed to withhold their response. The target:distractor ratio was 15∶85, and the inter-stimulus interval was 900 ms. We first derived the hit rate (the number of non-target trials the participants made a response × 100/85) and the false alarm rate (the number of target trials the participants responded to × 100/15). We then computed A’ to indicate the participant’s ability to discriminate between target and distractor trials by using the formula provided in the next section.
The verbal n-back tasks assessed participants’ Working Memory/Executive Functions. Verbal 1-back was always presented to the participants first, followed by 2- and 3-back. Participants were shown one of the letters (B, C, D, F, G, H, J, K, and M) for 500 ms and required to compare it with the letter presented n trials before. The inter-stimulus interval was 2,000 ms. The match:mismatch trial ratio was 8∶24. We first computed the hit rate (hit = number of correct match trials × 100/number of match trials) and the false alarm rate (fa = number of incorrect mismatch trials × 100/number of mismatch trials). We then computed non-parametric measures of sensitivity (A′) and response bias (B″D) which were introduced by
A′ is one of the discriminability measures in signal detection theory. It is a non-parametric analogue of the more widely used d’ and can still be derived when the hit or false alarm rate is 0 or 1. A′ ranges from 0 to 1, with 0.5 suggesting chance performance. Its corresponding bias measure is B″D which indicates whether participants (a) tended to provide a ‘Yes’ response and indicate the stimuli matched, i.e. they were liberal and more likely to detect matches when they were actually present (B″D <0), (b) tended to provide a ‘No’ response and indicate the stimuli did not match, i.e. they were conservative and less likely to detect matches when they were actually present (B″D >0), or (c) were neutral in their tendency to provide ‘Yes’ and ‘No’ responses (B″D = 0).
After each verbal n-back task, the participants were asked to report their subjective ratings of the energy, cognitive demand, mental effort, and physical effort required to perform the task on a Visual Analogue Scale. We also measured the participants’ mood with the Positive and Negative Affect Scale
The hourly blood samples collected during CR were centrifuged (15 min, 1620 ×
EEG signals in all sleep episodes were recorded using a 10-channel EEG montage (Fz-A2, Cz-A1, F3-A2, F4-A1, C3-A2, C4-A1, P3-A2, P4-A1, O1-A2, and O2-A1) according to the 10-20 system. T3-A2 and T4-A1 were added to the montage during those nights after participants had performed a declarative memory task, which will be reported elsewhere. Eye movement, muscle tone, and heart rate were recorded through left and right EOG, submental EMG, and ECG electrodes, which were respectively referenced to A2 and A1. The ground and common reference electrodes were placed at FPz and Pz, respectively. Participants also wore a thoracic band, a nasal airflow sensor, a microphone, and leg electrodes during the habituation night in the first laboratory session to monitor any sign of sleep-related breathing problems and periodic leg movements.
The EEG, EOG, and EMG signals were recorded on Siesta 802 devices (Compumedics, Abbotsford, Victoria, Australia). The sampling rate and the storage was 256 Hz. The low-pass filter was set at 70 Hz and the high-pass filter was set at 0.3 Hz. Electrode impedance was kept below 5 kΩ. Sleep staging was performed according to the Rechtschaffen and Kales criteria
This protocol was approved by the Institutional Review Board of the Air Force Research Laboratory and received a favourable opinion from the University of Surrey Ethics Committee. It was conducted in accordance with the principles of the Declaration of Helsinki. All the participants provided written informed consent after receiving a detailed explanation of the aims and procedures of the study.
Statistical analyses were performed with SAS 9.1 (SAS Institute, Cary, NC). We used a general linear mixed model with PROC MIXED to determine the effects of Genotype (
Sleep data during the habituation night were not included in the analyses. Performance data collected on the arrival and habituation days were also not included in the analyses to minimize the effect of learning and practice on the results. Due to technical problems and drop-outs, 2.8% of the performance data, 8.6% of the PSG records, and 6.4% of the blood samples could not be included in the analyses.
Effect sizes were indicated by Cohen’s
In addition to using effect sizes to quantify the effects of repeated PSD on Sustained Attention and Executive Functions, we also compared the magnitude of change in performance in the PVT and the verbal 3-back task from the baseline day to the end of the partial sleep deprivation period (expressed as the performance on D6 in the SR condition divided by the performance on the baseline day) with the change in performance across the same days in the Control condition. For the effect of acute TSD, we did a similar comparison between the change in performance from the first to the second day of the TSD period between the two conditions (expressed as performance on TD2/performance on TD1).
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We thank Prof. Michael Chee for his constructive comments on this manuscript, Dr Sigurd Johnsen and Mr Patrick McCabe for their advice on statistical procedures and SAS programming, and Mrs Ana Slak, Mr Patrick Wood, Miss Dipali Patel, and the staff of the Surrey Clinical Research Centre for their assistance in data collection.