Sleep: To rebound or not to rebound
Sexual arousal in flies counteracts the effects of sleep deprivation.
- Florida Atlantic University, United States
How do we know we are tired and that it is time to sleep, and why can we go without sleep when we are excited? Usually, after a sleepless night, we make up for it the following day by taking a nap (if possible) or by going to bed earlier – a process referred to as rebound sleep. According to a long-standing model, this need to catch up on our sleep is modulated by two distinct mechanisms: the sleep homeostat, which controls how much we sleep, and the circadian clock, which dictates when we sleep (Borbély, 1982). While this model lays the foundation for understanding how sleep is regulated, it neglects a variety of other social, emotional and environmental factors that impact on sleep.
Sleep is highly conserved throughout the animal kingdom at both the genetic and the functional level. Some species are also known to skip sleep in favor of migration, mating or other social interactions. Flies, for example, can forgo sleep when they are exposed to mechanical stimulation or social interactions, which makes them a popular model for studying the regulation of sleep (Gilestro et al., 2009). Now, in eLife, Giorgio Gilestro of Imperial College and co-workers – Esteban Beckwith as first author, Quentin Geissmann and Alice French – report new insights into how sexual arousal in flies affects their need for sleep (Beckwith et al., 2017).
To examine how 'social sleep deprivation' affects rebound sleep, Beckwith et al. exposed the flies to different social scenarios. First, they placed a male fly into an arena that already contained a male resident. The presence of another male caused the resident to lose sleep, but he caught up via rebound sleep once the male intruder had been removed (Figure 1). The resident also lost sleep when a receptive female fly was introduced, but he did not catch up via rebound sleep once the female was removed. This suggests that the sexual arousal induced by the female fly was sufficient to override any need for the male to catch up after a sleepless night.
Figure 1
The effect of social interactions on rebound sleep in flies.
Top panel: A male fly that has been deprived of sleep (red eye) by a male intruder (white eye) catches up on sleep the following day (rebound sleep). Bottom panel: Conversely, a male fly that has been deprived of sleep by pairing with a receptive female suppresses its need for sleep the following day, probably due to still being in a sexually aroused state (bottom panel).
What allows sexual arousal to overcome rebound sleep? Fly courtship is a multisensory experience that involves visual, tactile, acoustic and pheromonal cues. Beckwith et al. found that exposing male flies to female pheromones, or transferring them into tubes that previously contained a female fly, was sufficient to suppress rebound sleep.
To get to the bottom of why sexually aroused males did not catch up on lost sleep, Beckwith et al. looked deeper into the fly brain. Previous research has shown that male flies sense certain pheromones through neurons (and their receptor proteins) on their forelegs – this is why male flies repeatedly tap female flies with their legs during courtship. Beckwith et al. discovered that when males lacked the pheromone receptor pickpocket 23 on these leg neurons, they did not notice the pheromones and rebound sleep occurred.
Moreover, the results showed that a specific cluster of neurons, called P1 neurons, are critical for courtship-suppressed sleep. When these neurons were stimulated, rebound sleep was inhibited. Taken together, these findings suggest that pickpocket 23 neurons detect pheromones and then activate P1 neurons which, in turn, suppress sleep and prevent rebound sleep.
To better understand the mechanisms underlying the sexual arousal vs. sleep trade-off, we need to identify how pheromone circuits interface with sleep centers in the brain to modulate behavior. Two other recent papers shed light on this issue. In males, P1 neurons are activated by contact with females, and Chen et al. have shown that these neurons are connected with a set of wake-promoting neurons (Chen et al., 2017). In a separate study, Machado et al. discovered another pair of wake-promoting neurons that directly modulate courtship circuits (Machado et al., 2017).
Despite this progress, two central questions persist: how is the need for sleep sensed, and is sleep loss centrally integrated within the brain? So far, researchers have discovered many different neuronal circuits for sleep homeostasis within the fly brain, which could be directly or indirectly affected by sexual arousal and result in suppressed rebound sleep (Liu et al., 2016; Pimentel et al., 2016; Seidner et al., 2015). Identifying the neural circuits that regulate sleep and courtship will serve as a framework for determining the molecular sensors that know when we need to sleep.
Together, these findings highlight the integrated nature of sleep, and the way it is affected by the internal clock, the need for sleep and external factors, such as arousal. However, there is much that we do not know: for example, how do other external influences, such as stress, excitement or caffeine consumption, affect sleep loss and rebound sleep? Answering these questions will shed light on the basic functions of sleep.
References
Article and author information
Author details
Publication history
- Version of Record published: October 6, 2017 (version 1)
Copyright
© 2017, Stahl et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,606
- Page views
-
- 121
- Downloads
-
- 1
- Citations
Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Sleep: To rebound or not to rebound
eLife 6:e31646.
https://doi.org/10.7554/eLife.31646
Further reading
-
- Cell Biology
- Computational and Systems Biology
Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.
-
- Computational and Systems Biology
- Neuroscience
Closed-loop neuronal stimulation has a strong therapeutic potential for neurological disorders such as Parkinson’s disease. However, at the moment, standard stimulation protocols rely on continuous open-loop stimulation and the design of adaptive controllers is an active field of research. Delayed feedback control (DFC), a popular method used to control chaotic systems, has been proposed as a closed-loop technique for desynchronisation of neuronal populations but, so far, was only tested in computational studies. We implement DFC for the first time in neuronal populations and access its efficacy in disrupting unwanted neuronal oscillations. To analyse in detail the performance of this activity control algorithm, we used specialised in vitro platforms with high spatiotemporal monitoring/stimulating capabilities. We show that the conventional DFC in fact worsens the neuronal population oscillatory behaviour, which was never reported before. Conversely, we present an improved control algorithm, adaptive DFC (aDFC), which monitors the ongoing oscillation periodicity and self-tunes accordingly. aDFC effectively disrupts collective neuronal oscillations restoring a more physiological state. Overall, these results support aDFC as a better candidate for therapeutic closed-loop brain stimulation.
