Diffusion model for one-choice reaction-time tasks and the cognitive effects of sleep deprivation.
ABSTRACT: One-choice reaction-time (RT) tasks are used in many domains, including assessments of motor vehicle driving and assessments of the cognitive/behavioral consequences of sleep deprivation. In such tasks, subjects are asked to respond when they detect the onset of a stimulus; the dependent variable is RT. We present a cognitive model for one-choice RT tasks that uses a one-boundary diffusion process to represent the accumulation of stimulus information. When the accumulated evidence reaches a decision criterion, a response is initiated. This model is distinct in accounting for the RT distributions observed for one-choice RT tasks, which can have long tails that have not been accurately captured by earlier cognitive modeling approaches. We show that the model explains performance on a brightness-detection task (a "simple RT task") and on a psychomotor vigilance test. The latter is used extensively to examine the clinical and behavioral effects of sleep deprivation. For the brightness-detection task, the model explains the behavior of RT distributions as a function of brightness. For the psychomotor vigilance test, it accounts for lapses in performance under conditions of sleep deprivation and for changes in the shapes of RT distributions over the course of sleep deprivation. The model also successfully maps the rate of accumulation of stimulus information onto independently derived predictions of alertness. The model is a unified, mechanistic account of one-choice RT under conditions of sleep deprivation.
Project description:<h4>Study objective</h4>Sleep deprivation significantly reduces the ability to maintain a consistent alertness level and impairs vigilant attention. Previous studies have shown that longer inter-stimulus interval (ISI) are associated with faster reaction times (RTs) on the Psychomotor Vigilance Test (PVT). However, whether and how sleep deprivation interacts with this ISI effect remains unclear.<h4>Methods</h4>N = 70 healthy adults (age range 20-50 years, 41 males) participated in a 5-day and 4-night in-laboratory controlled sleep deprivation study, including N = 54 in the experimental group with one night of total sleep deprivation and N = 16 in the control group without sleep loss. All participants completed a neurobehavioral test battery every 2 hours while awake, including a 10-minute standard PVT (PVT-S, N = 1626) and a 3-minute brief PVT (PVT-B, N = 1622). The linear approach to threshold with ergodic rate (LATER) model was used to fit the RT data.<h4>Results</h4>RT decreased significantly with longer ISI on the PVT-S and PVT-B. Increased ISI effect was found for both PVT-S and PVT-B during sleep deprivation compared to baseline or recovery sleep in the experimental group, whereas no differences in the ISI effect were found in the control group. The LATER model fitting indicated that changes in perceptual sensitivity rather than threshold adjustment may underlie the ISI effect.<h4>Conclusions</h4>Both standard and brief PVT showed a similar ISI effect on vigilant attention performance. Sleep deprivation increased the ISI effect on both PVT-S and PVT-B, which may be due to impaired temporal resolution and time estimation after sleep loss.
Project description:The rat psychomotor vigilance task (rPVT) was developed as a rodent analog of the human psychomotor vigilance task (hPVT). We examined whether rPVT performance displays time-on-task effects similar to those observed on the hPVT.The rPVT requires rats to respond to a randomly presented light stimulus to obtain a water reward. Rats were water deprived for 22 h prior to each 30-min rPVT session to motivate performance. We analyzed rPVT performance over time on task and as a function of the response-stimulus interval, at baseline and after sleep deprivation.The study was conducted in an academic research vivarium.Male Long-Evans rats were trained to respond to a 0.5 sec stimulus light within 3 sec of stimulus onset. Complete data were available for n = 20 rats.Rats performed the rPVT for 30 min at baseline and after 24 h total sleep deprivation by gentle handling.Compared to baseline, sleep deprived rats displayed increased performance lapses and premature responses, similar to hPVT lapses of attention and false starts. However, in contrast to hPVT performance, the time-on-task performance decrement was not significantly enhanced by sleep deprivation. Moreover, following sleep deprivation, rPVT response times were not consistently increased after short response-stimulus intervals.The rPVT manifests similarities to the hPVT in global performance outcomes, but not in post-sleep deprivation effects of time on task and response-stimulus interval.
Project description:There is a long-standing debate about the best way to characterize performance deficits on the psychomotor vigilance test (PVT), a widely used assay of cognitive impairment in human sleep deprivation studies. Here, we address this issue through the theoretical framework of the diffusion model and propose to express PVT performance in terms of signal-to-noise ratio (SNR).From the equations of the diffusion model for one-choice, reaction-time tasks, we derived an expression for a novel SNR metric for PVT performance. We also showed that LSNR-a commonly used log-transformation of SNR-can be reasonably well approximated by a linear function of the mean response speed, LSNRapx. We computed SNR, LSNR, LSNRapx, and number of lapses for 1284 PVT sessions collected from 99 healthy young adults who participated in laboratory studies with 38 hr of total sleep deprivation.All four PVT metrics captured the effects of time awake and time of day on cognitive performance during sleep deprivation. The LSNR had the best psychometric properties, including high sensitivity, high stability, high degree of normality, absence of floor and ceiling effects, and no bias in the meaning of change scores related to absolute baseline performance.The theoretical motivation of SNR and LSNR permits quantitative interpretation of PVT performance as an assay of the fidelity of information processing in cognition. Furthermore, with a conceptual and statistical meaning grounded in information theory and generalizable across scientific fields, LSNR in particular is a useful tool for systems-integrated fatigue risk management.
Project description:Maintaining optimal cognitive performance in astronauts during spaceflight is critical to crewmember safety and mission success. To investigate the combined effects of confinement, isolation, and sleep deprivation on cognitive performance during spaceflight, we administered the computerized neurobehavioral test battery "Cognition" to crew members of simulated spaceflight missions as part of NASA's ground-based Human Exploration Research Analog project. Cognition was administered to N = 32 astronaut-like subjects in four 1-week missions (campaign 1) and four 2 weeks missions (campaign 2), with four crewmembers per mission. In both campaigns, subjects performed significantly faster on Cognition tasks across time in mission without sacrificing accuracy, which is indicative of a learning effect. On an alertness and affect survey, subjects self-reported significant improvement in several affective domains with time in mission. During the sleep restriction challenge, subjects in campaign 1 were significantly less accurate on a facial emotion identification task during a night of partial sleep restriction. Subjects in campaign 2 were significantly slower and less accurate on psychomotor vigilance, and slower on cognitive throughput and motor praxis tasks during a night of total sleep deprivation. On the survey, subjects reported significantly worsening mood during the sleep loss challenge on several affective domains. These findings suggest that confinement and relative isolation of up to 2 weeks in this environment do not induce a significant negative impact on cognitive performance in any of the domains examined by Cognition, although the concurrent practice effect may have masked some of the mission's effects. Conversely, a night of total sleep deprivation significantly decreased psychomotor vigilance and cognitive throughput performance in astronaut-like subjects. This underscores the importance of using cognitive tests designed specifically for the astronaut population, and that survey a range of cognitive domains to detect the differential effects of the wide range of stressors common to the spaceflight environment.
Project description:Cytokines such as TNF? 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 TNF? gene (TNF? 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 2-3h. The TNF? 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 TNF? 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 TNF? in the effects of sleep deprivation on psychomotor vigilance performance. Furthermore, the TNF? G308A polymorphism may have predictive potential in a biomarker panel for the assessment of resilience to psychomotor vigilance performance impairment due to sleep deprivation.
Project description:To identify measures derived from baseline psychomotor vigilance task (PVT) performance that can reliably predict vulnerability to sleep deprivation.Subjects underwent total sleep deprivation and completed a 10-min PVT every 1-2 h in a controlled laboratory setting. Participants were categorized as vulnerable or resistant to sleep deprivation, based on a median split of lapses that occurred following sleep deprivation. Standard reaction time, drift diffusion model (DDM), and wavelet metrics were derived from PVT response times collected at baseline. A support vector machine model that incorporated maximum relevance and minimum redundancy feature selection and wrapper-based heuristics was used to classify subjects as vulnerable or resistant using rested data.Two academic sleep laboratories.Independent samples of 135 (69 women, age 18 to 25 y), and 45 (3 women, age 22 to 32 y) healthy adults.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.In both datasets, DDM measures, number of consecutive reaction times that differ by more than 250 ms, and two wavelet features were selected by the model as features predictive of vulnerability to sleep deprivation. Using the best set of features selected in each dataset, classification accuracy was 77% and 82% using fivefold stratified cross-validation, respectively.Despite differences in experimental conditions across studies, drift diffusion model parameters associated reliably with individual differences in performance during total sleep deprivation. These results demonstrate the utility of drift diffusion modeling of baseline performance in estimating vulnerability to psychomotor vigilance decline following sleep deprivation.
Project description: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 Adaptive Control of Thought - Rational (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.
Project description:Sleep deprivation can impair human health and performance. Habitual total sleep time and homeostatic sleep response to sleep deprivation are quantitative traits in humans. Genetic loci for these traits have been identified in model organisms, but none of these potential animal models have a corresponding human genotype and phenotype. We have identified a mutation in a transcriptional repressor (hDEC2-P385R) that is associated with a human short sleep phenotype. Activity profiles and sleep recordings of transgenic mice carrying this mutation showed increased vigilance time and less sleep time than control mice in a zeitgeber time- and sleep deprivation-dependent manner. These mice represent a model of human sleep homeostasis that provides an opportunity to probe the effect of sleep on human physical and mental health.
Project description:Several groups undergo extended periods without sleep due to working conditions or mental illness. Such sleep deprivation (SD) can deleteriously affect attentional processes and disrupt work and family functioning. Understanding the biological underpinnings of SD effects may assist in developing sleep therapies and cognitive enhancers. Utilizing cross-species tests of attentional processing in humans and rodents would aid in mechanistic studies examining SD-induced inattention. We assessed the effects of 36h of: (1) Total SD (TSD) in healthy male and female humans (n=50); and (2) REM SD (RSD) in male C57BL/6 mice (n=26) on performance in the cross-species 5-choice continuous performance test (5C-CPT). The 5C-CPT includes target trials on which subjects were required to respond and non-target trials on which subjects were required to inhibit from responding. TSD-induced effects on human psychomotor vigilance test (PVT) were also examined. Effects of SD were also examined on mice split into good and poor performance groups based on pre-deprivation scores. In the human 5C-CPT, TSD decreased hit rate and vigilance with trend-level effects on accuracy. In the PVT, TSD slowed response times and increased lapses. In the mouse 5C-CPT, RSD reduced accuracy and hit rate with trend-level effects on vigilance, primarily in good performers. In conclusion, SD induced impaired 5C-CPT performance in both humans and mice and validates the 5C-CPT as a cross-species translational task. The 5C-CPT can be used to examine mechanisms underlying SD-induced deficits in vigilance and assist in testing putative cognitive enhancers.
Project description:Background:The number of studies on gender differences in psychomotor performance and sleepiness is small and the results are contradictory. The aim of this study was to assess the changes in psychomotor performance, due to 24 h of sleep deprivation in young women and men. Participants:Eighty-nine students (49 women and 40 men) took part in the study. Participants were randomized into two groups: experimental (sleep deprived) and control (non-sleep deprived). Methods:The research was carried out using computer-based tests of the Vienna Test System (COG, DT, WAFF) and pupillography (F2D Fit-For-Duty). Results:There were no statistically significant effects of the main genders and groups on sleepiness measured by the pupillography. There was no deterioration in the results after deprivation among women and men in the COG test. Changes were noted in the DT and WAFF tests, and their size depended on the test. The number of false responses in psychomotor test was higher in women after sleep deprivation. Conclusion:One night of sleep deprivation may not have been a negative enough stimulus for young, healthy women and men to reveal gender differences in psychomotor tests. Low sleep levels can lead to low productivity at work and accidents due to reduced vigilance. Insufficient sleep in the long term can lead to poor health, resulting in hypertension, obesity and depression.