Telling the Time with a Broken Clock: Quantifying Circadian Disruption in Animal Models

Abstract

Circadian rhythms are approximately 24 h cycles in physiology and behaviour that enable organisms to anticipate predictable rhythmic changes in their environment. These rhythms are a hallmark of normal healthy physiology, and disruption of circadian rhythms has implications for cognitive, metabolic, cardiovascular and immune function. Circadian disruption is of increasing concern, and may occur as a result of the pressures of our modern 24/7 society—including artificial light exposure, shift-work and jet-lag. In addition, circadian disruption is a common comorbidity in many different conditions, ranging from aging to neurological disorders. A key feature of circadian disruption is the breakdown of robust, reproducible rhythms with increasing fragmentation between activity and rest. Circadian researchers have developed a range of methods for estimating the period of time series, typically based upon periodogram analysis. However, the methods used to quantify circadian disruption across the literature are not consistent. Here we describe a range of different measures that have been used to measure circadian disruption, with a particular focus on laboratory rodent data. These methods include periodogram power, variability in activity onset, light phase activity, activity bouts, interdaily stability, intradaily variability and relative amplitude. The strengths and limitations of these methods are described, as well as their normal ranges and interrelationships. Whilst there is an increasing appreciation of circadian disruption as both a risk to health and a potential therapeutic target, greater consistency in the quantification of disrupted rhythms is needed.

Light and Temperature Synchronizes Locomotor Activity in the Linden Bug, Pyrrhocoris apterus

“…Unfortunately, the relatively low and particularly noisy locomotor activity makes analysis of phase shifts (determining activity on-set, off-set or acrophase) at an individual level virtually impossible. However, the noisy activity records do not prevent reliable determination of the free-running period for individual bugs (Refinetti et al, 2007;Zielinski et al, 2014;Brown et al, 2019). In this context, it is remarkable that ∼40% of males were strongly rhythmic and another ∼40% weakly rhythmic in LL with an intensity of 400 lux (Figure 6), whereas even much weaker light intensities cause complete arrhythmicity in Drosophila (Saunders, 1997).…”

“…Lomb-Scargle periodogram in ActogramJ (Schmid et al, 2011) was used to determine the rhythmicity of bugs and τ in constant conditions, and double-plotted actograms were further inspected by eye (Refinetti et al, 2007;Brown et al, 2019). Three categories were defined: (1) Strongly rhythmic males: periodogram peak crossed the significance line and PN value calculated by ActogramJ software was >65.…”

“…Data from individual bugs are very noisy. Until now we were not able to reliably determine the precise time of the locomotor activity onset, off-set or acrophase for a single bug, which is usually used for determining the exact phase of activity (Refinetti et al, 2007;Brown et al, 2019). Therefore, the average activity of all bugs was analyzed.…”

Melatonin Relations with Energy Metabolism as Possibly Involved in Fatal Mountain Road Traffic Accidents

“…From daily repetition of steady phase relationships among multiple clocks, a temporal order of the whole organism can arise. Interrelated clocks seem to constitute together a complex information handling system, keeping the organism as a whole in step with the challenges imposed by a periodically changing environment [30,[46][47][48][49]. Thus, also the central circadian system represents an ensemble of oscillators crossing different brain regions [31].…”

Enhanced Circadian Entrainment in Mice and Its Utility under Human Shiftwork Schedules

“…Thus, one goal of this study in a nocturnal rodent model was to produce an entrainment pattern where locomotor activity (a marker of subjective night) was absent from Work Blocks 1-4 (red boxes in Figure 3), but instead occurred robustly in scheduled scotophases (shaded lightly in Figure 3). Combining these two concepts, Percent Activity in the Light can be used as a good indication of overall adaptation [29]. In the middle of the experiment a technical failure caused the lights to be off for 48 consecutive hours for group B.…”