Working around the Clock: Is a Person's Endogenous Circadian Timing for Optimal Neurobehavioral Functioning Inherently Task-Dependent?

Rachael A Muck,Shobhan Gaddameedhi,Kimberly A Honn,Amanda N Hudson,Hans P A Van Dongen

doi:10.3390/clockssleep4010005

Rachael A Muck, Shobhan Gaddameedhi + Show 3 more

Open Access

https://doi.org/10.3390/clockssleep4010005

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Abstract

Neurobehavioral task performance is modulated by the circadian and homeostatic processes of sleep/wake regulation. Biomathematical modeling of the temporal dynamics of these processes and their interaction allows for prospective prediction of performance impairment in shift-workers and provides a basis for fatigue risk management in 24/7 operations. It has been reported, however, that the impact of the circadian rhythm—and in particular its timing—is inherently task-dependent, which would have profound implications for our understanding of the temporal dynamics of neurobehavioral functioning and the accuracy of biomathematical model predictions. We investigated this issue in a laboratory study designed to unambiguously dissociate the influences of the circadian and homeostatic processes on neurobehavioral performance, as measured during a constant routine protocol preceded by three days on either a simulated night shift or a simulated day shift schedule. Neurobehavioral functions were measured every 2 h using three functionally distinct assays: a digit symbol substitution test, a psychomotor vigilance test, and the Karolinska Sleepiness Scale. After dissociating the circadian and homeostatic influences and accounting for inter-individual variability, peak circadian performance occurred in the late biological afternoon (in the “wake maintenance zone”) for all three neurobehavioral assays. Our results are incongruent with the idea of inherent task-dependent differences in the endogenous circadian impact on performance. Rather, our results suggest that neurobehavioral functions are under top-down circadian control, consistent with the way they are accounted for in extant biomathematical models.

Highlights

Because the homeostatic process is a function of time awake and not time of day, it follows that the simulated night shift condition produced an average shift of 10.6 h in the alignment of the homeostatic process relative to the circadian process during the subsequent 24 h constant routine (CR) protocol
Referring to the sleep deprivation literature is relevant here, because our results indicate that the differences we observed in the overall temporal profiles of the Karolinska Sleepiness Scale (KSS), digit symbol substitution test (DSST), and psychomotor vigilance test (PVT) with the circadian and homeostatic processes still intertwined (Figure 3) are attributable at least in part to differences between neurobehavioral functions in the influence of time awake through the homeostatic process
If there are inherent differences between tasks in the timing of the endogenous circadian peak, our carefully conducted study with comprehensive disentanglement of the circadian and homeostatic processes as well as the inter-individual differences therein would have been expected to manifestly expose them—but for the three distinct neurobehavioral tasks we investigated we found peak circadian performance clustering in the late biological afternoon during the CR protocol after both simulated day and night shift schedules

Summary

Introduction

The combined effect of these two processes governs changes in waking neurobehavioral functioning over time, such that day shift-workers tend to exhibit stable, near-optimal performance through the workday [3,4], whereas night shift-workers typically experience a steady decline of performance through the night [5,6]. Inter-individual differences in the contributions of the two processes notwithstanding [7,8], these dynamics are well understood [9,10] and have led to the development of biomathematical models predicting neurobehavioral performance across a wide range of sleep/wake/work scenarios [11,12]. Such biomathematical models can be used to prospectively predict performance impairment in shift-workers [13,14] and may be implemented in 24/7 operations as a tool for fatigue risk management [15,16]

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