Functional imaging of inter-individual differences in response to sleep deprivation

Chee, Michael W.L.; Dongen, Hans P. A. Van

doi:10.1017/cbo9781139088268.021

Cited by 13 publications

(12 citation statements)

References 64 publications

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“…Prior use is a function of time awake and is further modulated by task load (Van Dongen, Belenky, & Krueger, 2011b), which is determined by stimulus density and time on task (i.e., cumulative cognitive processing requirement) and is particularly high in repetitive, attention-demanding tasks such as the PVT. The effects of local sleep on performance depend on the number of functional neuronal circuits available to process information for a given task – that is, level of redundancy, or cognitive capacity – which may vary across tasks and among individuals (Chee & Van Dongen, 2013). …”

Section: Discussionmentioning

confidence: 99%

Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss

2017

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Computational models have become common tools in psychology. They provide quantitative instantiations of theories that seek to explain the functioning of the human mind. In this paper, we focus on identifying deep theoretical similarities between two very different models. Both models are concerned with how fatigue from sleep loss impacts cognitive processing. The first is based on the diffusion model and posits that fatigue decreases the drift rate of the diffusion process. The second is based on the ACT-R cognitive architecture and posits that fatigue decreases the utility of candidate actions leading to microlapses in cognitive processing. A biomathematical model of fatigue is used to control drift rate in the first account and utility in the second. We investigated the predicted response time distributions of these two integrated computational cognitive models for performance on a psychomotor vigilance test under conditions of total sleep deprivation, simulated shift work, and sustained sleep restriction. The models generated equivalent predictions of response time distributions with excellent goodness-of-fit to the human data. More importantly, although the accounts involve different modeling approaches and levels of abstraction, they represent the effects of fatigue in a functionally equivalent way: in both, fatigue decreases the signal-to-noise ratio in decision processes and decreases response inhibition. This convergence suggests that sleep loss impairs psychomotor vigilance performance through degradation of the quality of cognitive processing, which provides a foundation for systematic investigation of the effects of sleep loss on other aspects of cognition. Our findings illustrate the value of treating different modeling formalisms as vehicles for discovery.

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Section: Discussionmentioning

confidence: 99%

Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss

2017

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“…This may be seen as evidence that in resilient individuals, information processing capacity is less degraded by local sleep (Chee and Van Dongen, 2013). In terms of cognitive performance, this means greater signal-to-noise ratio or, in the context of a diffusion cognitive model for PVT performance, higher diffusion drift rate for information processing (Ratcliff and Van Dongen, 2011).…”

Section: Discussionmentioning

confidence: 99%

TNFα G308A polymorphism is associated with resilience to sleep deprivation-induced psychomotor vigilance performance impairment in healthy young adults

Satterfield

Wisor

Field

et al. 2015

Brain, Behavior, and Immunity

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Cytokines such as TNFα play an integral role in sleep/wake regulation and have recently been hypothesized to be involved in cognitive impairment due to sleep deprivation. We examined the effect of a guanine to adenine substitution at position 308 in the TNFα gene (TNFα G308A) on psychomotor vigilance performance impairment during total sleep deprivation. A total of 88 healthy women and men (ages 22–40) participated in one of five laboratory total sleep deprivation experiments. Performance on a psychomotor vigilance test (PVT) was measured every 2 to 3 h. The TNFα 308A allele, which is less common than the 308G allele, was associated with greater resilience to psychomotor vigilance performance impairment during total sleep deprivation (regardless of time of day), and also provided a small performance benefit at baseline. The effect of genotype on resilience persisted when controlling for between-subjects differences in age, gender, race/ethnicity, and baseline sleep duration. The TNFα G308A polymorphism predicted less than 10% of the overall between-subjects variance in performance impairment during sleep deprivation. Nonetheless, the differential effect of the polymorphism at the peak of performance impairment was more than 50% of median performance impairment at that time, which is sizeable compared to the effects of other genotypes reported in the literature. Our findings provided evidence for a role of TNFα in the effects of sleep deprivation on psychomotor vigilance performance. Furthermore, the TNFα G308A polymorphism may have predictive potential in a biomarker panel for the assessment of resilience to psychomotor vigilance performance impairment due to sleep deprivation.

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“…Furthermore, it has been observed that individuals highly differ in compensatory brain activity patterns. These variations presumably underlie stable inter-individual differences in vulnerability to sleep loss at the behavioral level [ 189 ].…”

Section: Working Memorymentioning

confidence: 99%

“…Under low sleep pressure, complex tasks might trigger motivational resources that help to overcome circadian nighttime troughs in cognitive performance [ 124 ]. Alternatively, compensatory brain mechanisms might operate in a more successful manner when the implicated network is more widespread, as typical for more complex cognitive processes [ 189 ]. Such compensatory mechanisms might contribute to a vulnerability to sleep loss at night.…”

Section: Working Memorymentioning

confidence: 99%

Sleep-Wake Regulation and Its Impact on Working Memory Performance: The Role of Adenosine

Reichert

Maire

Schmidt

et al. 2016

Biology

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The sleep-wake cycle is regulated by a fine-tuned interplay between sleep-homeostatic and circadian mechanisms. Compelling evidence suggests that adenosine plays an important role in mediating the increase of homeostatic sleep pressure during time spent awake and its decrease during sleep. Here, we summarize evidence that adenosinergic mechanisms regulate not only the dynamic of sleep pressure, but are also implicated in the interaction of homeostatic and circadian processes. We review how this interaction becomes evident at several levels, including electrophysiological data, neuroimaging studies and behavioral observations. Regarding complex human behavior, we particularly focus on sleep-wake regulatory influences on working memory performance and underlying brain activity, with a specific emphasis on the role of adenosine in this interplay. We conclude that a change in adenosinergic mechanisms, whether exogenous or endogenous, does not only impact on sleep-homeostatic processes, but also interferes with the circadian timing system.

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Functional imaging of inter-individual differences in response to sleep deprivation

Cited by 13 publications

References 64 publications

Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss

Computational cognitive modeling of the temporal dynamics of fatigue from sleep loss

TNFα G308A polymorphism is associated with resilience to sleep deprivation-induced psychomotor vigilance performance impairment in healthy young adults

Sleep-Wake Regulation and Its Impact on Working Memory Performance: The Role of Adenosine

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