Oscillatory brain activity in spontaneous and induced sleep stages in flies

FlyVISTA, an Integrated Machine Learning Platform for Deep Phenotyping of Sleep in Drosophila

Animal behavior depends on internal state. While subtle movements can signify significant changes in internal state, computational methods for analyzing these "microbehaviors" are lacking. Here, we present FlyVISTA, a machine-learning platform to characterize microbehaviors in freely-moving flies, which we use to perform deep phenotyping of sleep. This platform comprises a high-resolution closed-loop video imaging system, coupled with a deep-learning network to annotate 35 body parts, and a computational pipeline to extract behaviors from high-dimensional data. FlyVISTA reveals the distinct spatiotemporal dynamics of sleep-associated microbehaviors in flies. We further show that stimulation of dorsal fan-shaped body neurons induces micromovements, not sleep, whereas activating R5 ring neurons triggers rhythmic proboscis extension followed by persistent sleep. Importantly, we identify a novel microbehavior ("haltere switch") exclusively seen during quiescence that indicates a deeper sleep stage. These findings enable the rigorous analysis of sleep in Drosophila and set the stage for computational analyses of microbehaviors.

Why study sleep in flatworms?

The behaviors that characterize sleep have been observed across a broad range of different species. While much attention has been placed on vertebrates (mostly mammals and birds), the grand diversity of invertebrates has gone largely unexplored. Here, we introduce the intrigue and special value in the study of sleeping platyhelminth flatworms. Flatworms are closely related to annelids and mollusks, and yet are comparatively simple. They lack a circulatory system, respiratory system, endocrine glands, a coelom, and an anus. They retain a central and peripheral nervous system, various sensory systems, and an ability to learn. Flatworms sleep, like other animals, a state which is regulated by prior sleep/wake history and by the neurotransmitter GABA. Furthermore, they possess a remarkable ability to regenerate from a mere fragment of the original animal. The regenerative capabilities of flatworms make them a unique bilaterally symmetric animal to study a link between sleep and neurodevelopment. Lastly, the recent applications of tools for probing the flatworm genome, metabolism, and brain activity make their entrance into the field of sleep research all the more timely.

An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context

The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.

Drosophila noktochor regulates night sleep via a local mushroom body circuit

We show that a sleep-regulating, Ig-domain protein (NKT) is secreted from Drosophila mushroom body (MB) α'/β' neurons to act locally on other MB cell types. Pan-neuronal or broad MB expression of membrane-tethered NKT (tNkt) protein reduced sleep, like that of an NKT null mutant, suggesting blockade of a receptor mediating endogenous NKT action. In contrast, expression in neurons requiring NKT (the MB α'/β' cells), or non-MB sleep-regulating centers, did not reduce night sleep, indicating the presence of a local MB sleep-regulating circuit consisting of communicating neural subtypes. We suggest that the leucocyte-antigen-related like (Lar) transmembrane receptor may mediate NKT action. Knockdown or overexpression of Lar in the MB increased or decreased sleep, respectively, indicating the receptor promotes wakefulness. Surprisingly, selective expression of tNkt or knockdown of Lar in MB wake-promoting cells increased rather than decreased sleep, suggesting that NKT acts on wake- as well as sleep-promoting cell types to regulate sleep.

Neuronal dynamics direct cerebrospinal fluid perfusion and brain clearance

The accumulation of metabolic waste is a leading cause of numerous neurological disorders, yet we still have only limited knowledge of how the brain performs self-cleansing. Here we demonstrate that neural networks synchronize individual action potentials to create large-amplitude, rhythmic and self-perpetuating ionic waves in the interstitial fluid of the brain. These waves are a plausible mechanism to explain the correlated potentiation of the glymphatic flow1,2 through the brain parenchyma. Chemogenetic flattening of these high-energy ionic waves largely impeded cerebrospinal fluid infiltration into and clearance of molecules from the brain parenchyma. Notably, synthesized waves generated through transcranial optogenetic stimulation substantially potentiated cerebrospinal fluid-to-interstitial fluid perfusion. Our study demonstrates that neurons serve as master organizers for brain clearance. This fundamental principle introduces a new theoretical framework for the functioning of macroscopic brain waves.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Identifying different sleep stages in humans and other mammals has traditionally relied on electroencephalograms. Such an approach is not feasible in certain animals such as invertebrates, although these animals could also be sleeping in stages. Here, we perform long-term multichannel local field potential recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We acquired consistent spatial recordings of local field potentials across multiple flies, allowing us to compare brain activity across awake and sleep periods. Using machine learning, we uncover distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of microbehaviors associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

A two-process model of Drosophila sleep reveals an inter-dependence between circadian clock speed and the rate of sleep pressure decay

Sleep is controlled by two processes-a circadian clock that regulates its timing and a homeostat that regulates the drive to sleep. Drosophila has been an insightful model for understanding both processes. For four decades, Borbély and Daan's two-process model has provided a powerful framework for understanding sleep regulation. However, the field of fly sleep has not employed such a model as a framework for the investigation of sleep. To this end, we have adapted the two-process model to the fly and established its utility by showing that it can provide empirically testable predictions regarding the circadian and homeostatic control of fly sleep. We show that the ultradian rhythms previously reported for loss-of-function clock mutants in the fly are robustly detectable and a predictable consequence of a functional sleep homeostat in the absence of a functioning circadian system. We find that a model in which the circadian clock speed and homeostatic rates act without influencing each other provides imprecise predictions regarding how clock speed influences the strength of sleep rhythms and the amount of daily sleep. We also find that quantitatively good fits between empirical values and model predictions were achieved only when clock speeds were positively correlated with rates of decay of sleep pressure. Our results indicate that longer sleep bouts better reflect the homeostatic process than the current definition of sleep as any inactivity lasting 5 minutes or more. This two-process model represents a powerful framework for work on the molecular and physiological regulation of fly sleep.

Experimentally induced active and quiet sleep engage non-overlapping transcriptional programs in Drosophila

Sleep in mammals can be broadly classified into two different physiological categories: rapid eye movement (REM) sleep and slow-wave sleep (SWS), and accordingly REM and SWS are thought to achieve a different set of functions. The fruit fly Drosophila melanogaster is increasingly being used as a model to understand sleep functions, although it remains unclear if the fly brain also engages in different kinds of sleep as well. Here, we compare two commonly used approaches for studying sleep experimentally in Drosophila: optogenetic activation of sleep-promoting neurons and provision of a sleep-promoting drug, gaboxadol. We find that these different sleep-induction methods have similar effects on increasing sleep duration, but divergent effects on brain activity. Transcriptomic analysis reveals that drug-induced deep sleep ('quiet' sleep) mostly downregulates metabolism genes, whereas optogenetic 'active' sleep upregulates a wide range of genes relevant to normal waking functions. This suggests that optogenetics and pharmacological induction of sleep in Drosophila promote different features of sleep, which engage different sets of genes to achieve their respective functions.

Experimentally induced active and quiet sleep engage non-overlapping transcriptional programs in Drosophila

Sleep in mammals can be broadly classified into two different physiological categories: rapid eye movement (REM) sleep and slow wave sleep (SWS), and accordingly REM and SWS are thought to achieve a different set of functions. The fruit fly Drosophila melanogaster is increasingly being used as a model to understand sleep functions, although it remains unclear if the fly brain also engages in different kinds of sleep as well. Here, we compare two commonly used approaches for studying sleep experimentally in Drosophila: optogenetic activation of sleep-promoting neurons and provision of a sleep-promoting drug, Gaboxadol. We find that these different sleep-induction methods have similar effects on increasing sleep duration, but divergent effects on brain activity. Transcriptomic analysis reveals that drug-induced deep sleep ('quiet' sleep) mostly downregulates metabolism genes, whereas optogenetic 'active' sleep upregulates a wide range of genes relevant to normal waking functions. This suggests that optogenetics and pharmacological induction of sleep in Drosophila promote different features of sleep, which engage different sets of genes to achieve their respective functions.

How far neuroscience is from understanding brains

The cellular biology of brains is relatively well-understood, but neuroscientists have not yet generated a theory explaining how brains work. Explanations of how neurons collectively operate to produce what brains can do are tentative and incomplete. Without prior assumptions about the brain mechanisms, I attempt here to identify major obstacles to progress in neuroscientific understanding of brains and central nervous systems. Most of the obstacles to our understanding are conceptual. Neuroscience lacks concepts and models rooted in experimental results explaining how neurons interact at all scales. The cerebral cortex is thought to control awake activities, which contrasts with recent experimental results. There is ambiguity distinguishing task-related brain activities from spontaneous activities and organized intrinsic activities. Brains are regarded as driven by external and internal stimuli in contrast to their considerable autonomy. Experimental results are explained by sensory inputs, behavior, and psychological concepts. Time and space are regarded as mutually independent variables for spiking, post-synaptic events, and other measured variables, in contrast to experimental results. Dynamical systems theory and models describing evolution of variables with time as the independent variable are insufficient to account for central nervous system activities. Spatial dynamics may be a practical solution. The general hypothesis that measurements of changes in fundamental brain variables, action potentials, transmitter releases, post-synaptic transmembrane currents, etc., propagating in central nervous systems reveal how they work, carries no additional assumptions. Combinations of current techniques could reveal many aspects of spatial dynamics of spiking, post-synaptic processing, and plasticity in insects and rodents to start with. But problems defining baseline and reference conditions hinder interpretations of the results. Furthermore, the facts that pooling and averaging of data destroy their underlying dynamics imply that single-trial designs and statistics are necessary.

Sleepiness, not total sleep amount, increases seizure risk

Sleep loss has been associated with increased seizure risk since antiquity. Despite this observation standing the test of time, how poor sleep drives susceptibility to seizures remains unclear. To identify underlying mechanisms, we restricted sleep in Drosophila epilepsy models and developed a method to identify spontaneous seizures using quantitative video tracking. Here we find that sleep loss exacerbates seizures but only when flies experience increased sleep need, or sleepiness , and not necessarily with reduced sleep quantity. This is supported by the paradoxical finding that acute activation of sleep-promoting circuits worsens seizures, because it increases sleep need without changing sleep amount. Sleep-promoting circuits become hyperactive after sleep loss and are associated with increased whole-brain activity. During sleep restriction, optogenetic inhibition of sleep-promoting circuits to reduce sleepiness protects against seizures. Downregulation of the 5HT1A serotonin receptor in sleep-promoting cells mediates the effect of sleep need on seizures, and we identify an FDA-approved 5HT1A agonist to mitigate seizures. Our findings demonstrate that while homeostatic sleep is needed to recoup lost sleep, it comes at the cost of increasing seizure susceptibility. We provide an unexpected perspective on interactions between sleep and seizures, and surprisingly implicate sleep- promoting circuits as a therapeutic target for seizure control.

Pallidin function in Drosophila surface glia regulates sleep and is dependent on amino acid availability

The Pallidin protein is a central subunit of a multimeric complex called biogenesis of lysosome-related organelles complex 1 (BLOC1) that regulates specific endosomal functions and has been linked to schizophrenia. We show here that downregulation of Pallidin and other members of BLOC1 in the surface glia, the Drosophila equivalent of the blood-brain barrier, reduces and delays nighttime sleep in a circadian-clock-dependent manner. In agreement with BLOC1 involvement in amino acid transport, downregulation of the large neutral amino acid transporter 1 (LAT1)-like transporters JhI-21 and mnd, as well as of TOR (target of rapamycin) amino acid signaling, phenocopy Pallidin knockdown. Furthermore, supplementing food with leucine normalizes the sleep/wake phenotypes of Pallidin downregulation, and we identify a role for Pallidin in the subcellular trafficking of JhI-21. Finally, we provide evidence that Pallidin in surface glia is required for GABAergic neuronal activity. These data identify a BLOC1 function linking essential amino acid availability and GABAergic sleep/wake regulation.

Re-examining the role of the dorsal fan-shaped body in promoting sleep in Drosophila

The needs fulfilled by sleep are unknown, though the effects of insufficient sleep are manifold. To better understand how the need to sleep is sensed and discharged, much effort has gone into identifying the neural circuits involved in regulating arousal, especially those that promote sleep. In prevailing models, the dorsal fan-shaped body (dFB) plays a central role in this process in the fly brain. In the present study we manipulated various properties of the dFB including its electrical activity, synaptic output, and endogenous gene expression. In each of these experimental contexts we were unable to identify any effect on sleep that could be unambiguously mapped to the dFB. Furthermore, we found evidence that sleep phenotypes previously attributed to the dFB were caused by genetic manipulations that inadvertently targeted the ventral nerve cord. We also examined expression of two genes whose purported effects have been attributed to functions within a specific subpopulation of dFB neurons. In both cases we found little to no expression in the expected cells. Collectively, our results cast doubt on the prevailing hypothesis that the dFB plays a central role in promoting sleep.

Modulation and neural correlates of postmating sleep plasticity in Drosophila females

Sleep is essential, but animals may forgo sleep to engage in other critical behaviors, such as feeding and reproduction. Previous studies have shown that female flies exhibit decreased sleep after mating, but our understanding of the process is limited. Here, we report that postmating nighttime sleep loss is modulated by diet and sleep deprivation, demonstrating a complex interaction among sleep, reproduction, and diet. We also find that female-specific pC1 neurons and sleep-promoting dorsal fan-shaped body (dFB) neurons are required for postmating sleep plasticity. Activating pC1 neurons leads to sleep suppression on standard fly culture media but has little sleep effect on sucrose-only food. Published connectome data suggest indirect, inhibitory connections among pC1 subtypes. Using calcium imaging, we show that activating the pC1e subtype inhibits dFB neurons. We propose that pC1 and dFB neurons integrate the mating status, food context, and sleep drive to modulate postmating sleep plasticity.

Multivariate classification of multichannel long-term electrophysiology data identifies different sleep stages in fruit flies

Sleep is observed in most animals, which suggests it subserves a fundamental process associated with adaptive biological functions. However, the evidence to directly associate sleep with a specific function is lacking, in part because sleep is not a single process in many animals. In humans and other mammals, different sleep stages have traditionally been identified using electroencephalograms (EEGs), but such an approach is not feasible in different animals such as insects. Here, we perform long-term multichannel local field potential (LFP) recordings in the brains of behaving flies undergoing spontaneous sleep bouts. We developed protocols to allow for consistent spatial recordings of LFPs across multiple flies, allowing us to compare the LFP activity across awake and sleep periods and further compare the same to induced sleep. Using machine learning, we uncover the existence of distinct temporal stages of sleep and explore the associated spatial and spectral features across the fly brain. Further, we analyze the electrophysiological correlates of micro-behaviours associated with certain sleep stages. We confirm the existence of a distinct sleep stage associated with rhythmic proboscis extensions and show that spectral features of this sleep-related behavior differ significantly from those associated with the same behavior during wakefulness, indicating a dissociation between behavior and the brain states wherein these behaviors reside.

Neural Ensemble Fragmentation in the Anesthetized Drosophila Brain

General anesthetics cause a profound loss of behavioral responsiveness in all animals. In mammals, general anesthesia is induced in part by the potentiation of endogenous sleep-promoting circuits, although "deep" anesthesia is understood to be more similar to coma (Brown et al., 2011). Surgically relevant concentrations of anesthetics, such as isoflurane and propofol, have been shown to impair neural connectivity across the mammalian brain (Mashour and Hudetz, 2017; Yang et al., 2021), which presents one explanation why animals become largely unresponsive when exposed to these drugs. It remains unclear whether general anesthetics affect brain dynamics similarly in all animal brains, or whether simpler animals, such as insects, even display levels of neural connectivity that could be disrupted by these drugs. Here, we used whole-brain calcium imaging in behaving female Drosophila flies to investigate whether isoflurane anesthesia induction activates sleep-promoting neurons, and then inquired how all other neurons across the fly brain behave under sustained anesthesia. We were able to track the activity of hundreds of neurons simultaneously during waking and anesthetized states, for spontaneous conditions as well as in response to visual and mechanical stimuli. We compared whole-brain dynamics and connectivity under isoflurane exposure to optogenetically induced sleep. Neurons in the Drosophila brain remain active during general anesthesia as well as induced sleep, although flies become behaviorally inert under both treatments. We identified surprisingly dynamic neural correlation patterns in the waking fly brain, suggesting ensemble-like behavior. These become more fragmented and less diverse under anesthesia but remain wake-like during induced sleep.SIGNIFICANCE STATEMENT When humans are rendered immobile and unresponsive by sleep or general anesthetics, their brains do not shut off - they just change how they operate. We tracked the activity of hundreds of neurons simultaneously in the brains of fruit flies that were anesthetized by isoflurane or genetically put to sleep, to investigate whether these behaviorally inert states shared similar brain dynamics. We uncovered dynamic patterns of neural activity in the waking fly brain, with stimulus-responsive neurons constantly changing through time. Wake-like neural dynamics persisted during induced sleep but became more fragmented under isoflurane anesthesia. This suggests that, like larger brains, the fly brain might also display ensemble-like behavior, which becomes degraded rather than silenced under general anesthesia.

Regulation of sleep by cholinergic neurons located outside the central brain in Drosophila

Sleep is a complex and plastic behavior regulated by multiple brain regions and influenced by numerous internal and external stimuli. Thus, to fully uncover the function(s) of sleep, cellular resolution of sleep-regulating neurons needs to be achieved. Doing so will help to unequivocally assign a role or function to a given neuron or group of neurons in sleep behavior. In the Drosophila brain, neurons projecting to the dorsal fan-shaped body (dFB) have emerged as a key sleep-regulating area. To dissect the contribution of individual dFB neurons to sleep, we undertook an intersectional Split-GAL4 genetic screen focusing on cells contained within the 23E10-GAL4 driver, the most widely used tool to manipulate dFB neurons. In this study, we demonstrate that 23E10-GAL4 expresses in neurons outside the dFB and in the fly equivalent of the spinal cord, the ventral nerve cord (VNC). Furthermore, we show that 2 VNC cholinergic neurons strongly contribute to the sleep-promoting capacity of the 23E10-GAL4 driver under baseline conditions. However, in contrast to other 23E10-GAL4 neurons, silencing these VNC cells does not block sleep homeostasis. Thus, our data demonstrate that the 23E10-GAL4 driver contains at least 2 different types of sleep-regulating neurons controlling distinct aspects of sleep behavior.

The evolution and diversification of sleep

The evolutionary origins of sleep and its sub-states, rapid eye movement (REM) and non-REM (NREM) sleep, found in mammals and birds, remain a mystery. Although the discovery of a single type of sleep in jellyfish suggests that sleep evolved much earlier than previously thought, it is unclear when and why sleep diversified into multiple types of sleep. Intriguingly, multiple types of sleep have recently been found in animals ranging from non-avian reptiles to arthropods to cephalopods. Although there are similarities between these states and those found in mammals and birds, notable differences also exist. The diversity in the way sleep is expressed confounds attempts to trace the evolution of sleep states, but also serves as a rich resource for exploring the functions of sleep.

A brain-wide form of presynaptic active zone plasticity orchestrates resilience to brain aging in Drosophila

The brain as a central regulator of stress integration determines what is threatening, stores memories, and regulates physiological adaptations across the aging trajectory. While sleep homeostasis seems to be linked to brain resilience, how age-associated changes intersect to adapt brain resilience to life history remains enigmatic. We here provide evidence that a brain-wide form of presynaptic active zone plasticity ("PreScale"), characterized by increases of active zone scaffold proteins and synaptic vesicle release factors, integrates resilience by coupling sleep, longevity, and memory during early aging of Drosophila. PreScale increased over the brain until mid-age, to then decreased again, and promoted the age-typical adaption of sleep patterns as well as extended longevity, while at the same time it reduced the ability of forming new memories. Genetic induction of PreScale also mimicked early aging-associated adaption of sleep patterns and the neuronal activity/excitability of sleep control neurons. Spermidine supplementation, previously shown to suppress early aging-associated PreScale, also attenuated the age-typical sleep pattern changes. Pharmacological induction of sleep for 2 days in mid-age flies also reset PreScale, restored memory formation, and rejuvenated sleep patterns. Our data suggest that early along the aging trajectory, PreScale acts as an acute, brain-wide form of presynaptic plasticity to steer trade-offs between longevity, sleep, and memory formation in a still plastic phase of early brain aging.

Long-range connections are crucial for synchronization transition in a computational model of Drosophila brain dynamics

The synchronization transition type has been the focus of attention in recent years because it is associated with many functional characteristics of the brain. In this paper, the synchronization transition in neural networks with sleep-related biological drives in Drosophila is investigated. An electrical synaptic neural network is established to research the difference between the synchronization transition of the network during sleep and wake, in which neurons regularly spike during sleep and chaotically spike during wake. The synchronization transition curves are calculated mainly using the global instantaneous order parameters S. The underlying mechanisms and types of synchronization transition during sleep are different from those during wake. During sleep, regardless of the network structure, a frustrated (discontinuous) transition can be observed. Moreover, the phenomenon of quasi periodic partial synchronization is observed in ring-shaped regular network with and without random long-range connections. As the network becomes dense, the synchronization of the network only needs to slightly increase the coupling strength g. While during wake, the synchronization transition of the neural network is very dependent on the network structure, and three mechanisms of synchronization transition have emerged: discontinuous synchronization (explosive synchronization and frustrated synchronization), and continuous synchronization. The random long-range connections is the main topological factor that plays an important role in the resulting synchronization transition. Furthermore, similarities and differences are found by comparing synchronization transition research for the Hodgkin-Huxley neural network in the beta-band and gammma-band, which can further improve the synchronization phase transition research of biologically motivated neural networks. A complete research framework can also be used to study coupled nervous systems, which can be extended to general coupled dynamic systems.

Intrinsic maturation of sleep output neurons regulates sleep ontogeny in Drosophila

The maturation of sleep behavior across a lifespan (sleep ontogeny) is an evolutionarily conserved phenomenon. Mammalian studies have shown that in addition to increased sleep duration, early life sleep exhibits stark differences compared with mature sleep with regard to sleep states. How the intrinsic maturation of sleep output circuits contributes to sleep ontogeny is poorly understood. The fruit fly Drosophila melanogaster exhibits multifaceted changes to sleep from juvenile to mature adulthood. Here, we use a non-invasive probabilistic approach to investigate the changes in sleep architecture in juvenile and mature flies. Increased sleep in juvenile flies is driven primarily by a decreased probability of transitioning to wake and characterized by more time in deeper sleep states. Functional manipulations of sleep-promoting neurons in the dorsal fan-shaped body (dFB) suggest that these neurons differentially regulate sleep in juvenile and mature flies. Transcriptomic analysis of dFB neurons at different ages and a subsequent RNAi screen implicate the genes involved in dFB sleep circuit maturation. These results reveal that the dynamic transcriptional states of sleep output neurons contribute to the changes in sleep across the lifespan.

Neurotransmitters of sleep and wakefulness in flatworms

STUDY OBJECTIVES

Sleep is a prominent behavioral and biochemical state observed in all animals studied, including platyhelminth flatworms. Investigations into the biochemical mechanisms associated with sleep-and wakefulness-are important for understanding how these states are regulated and how that regulation changed with the evolution of new types of animals. Unfortunately, beyond a handful of vertebrates, such studies on invertebrates are rare.

METHODS

We investigated the effect of seven neurotransmitters, and one pharmacological compound, that modulate either sleep or wakefulness in mammals, on flatworms (Girardia tigrina). Flatworms were exposed via ingestion and diffusion to four neurotransmitters that promote wakefulness in vertebrates (acetylcholine, dopamine, glutamate, histamine), and three that induce sleep (adenosine, GABA, serotonin) along with the H1 histamine receptor antagonist pyrilamine. Compounds were administered over concentrations spanning three to five orders of magnitude. Flatworms were then transferred to fresh water and video recorded for analysis.

RESULTS

Dopamine and histamine decreased the time spent inactive and increased distance traveled, consistent with their wake-promoting effect in vertebrates and fruit flies; pyrilamine increased restfulness and GABA showed a nonsignificant trend towards promoting restfulness in a dose-dependent manner, in agreement with their sleep-inducing effect in vertebrates, fruit flies, and Hydra. Similar to Hydra, acetylcholine, glutamate, and serotonin, but also adenosine, had no apparent effect on flatworm behavior.

CONCLUSIONS

These data demonstrate the potential of neurotransmitters to regulate sleep and wakefulness in flatworms and highlight the conserved action of some neurotransmitters across species.

Roles for Sleep in Neural and Behavioral Plasticity: Reviewing Variation in the Consequences of Sleep Loss

Sleep is a vital physiological state that has been broadly conserved across the evolution of animal species. While the precise functions of sleep remain poorly understood, a large body of research has examined the negative consequences of sleep loss on neural and behavioral plasticity. While sleep disruption generally results in degraded neural plasticity and cognitive function, the impact of sleep loss can vary widely with age, between individuals, and across physiological contexts. Additionally, several recent studies indicate that sleep loss differentially impacts distinct neuronal populations within memory-encoding circuitry. These findings indicate that the negative consequences of sleep loss are not universally shared, and that identifying conditions that influence the resilience of an organism (or neuron type) to sleep loss might open future opportunities to examine sleep's core functions in the brain. Here, we discuss the functional roles for sleep in adaptive plasticity and review factors that can contribute to individual variations in sleep behavior and responses to sleep loss.

Non-REM and REM/paradoxical sleep dynamics across phylogeny

All animals carefully studied sleep, suggesting that sleep as a behavioral state exists in all animal life. Such evolutionary maintenance of an otherwise vulnerable period of environmental detachment suggests that sleep must be integral in fundamental biological needs. Despite over a century of research, the knowledge of what sleep does at the tissue, cellular or molecular levels remain cursory. Currently, sleep is defined based on behavioral criteria and physiological measures rather than at the cellular or molecular level. Physiologically, sleep has been described as two main states, non-rapid eye moment (NREM) and REM/paradoxical sleep (PS), which are defined in the neocortex by synchronous oscillations and paradoxical wake-like activity, respectively. For decades, these two sleep states were believed to be defining characteristics of only mammalian and avian sleep. Recent work has revealed slow oscillation, silencing, and paradoxical/REM-like activities in reptiles, fish, flies, worms, and cephalopods suggesting that these sleep dynamics and associated physiological states may have emerged early in animal evolution. Here, we discuss these recent developments supporting the conservation of neural dynamics (silencing, oscillation, paradoxical activity) of sleep states across phylogeny.

Hugin + neurons provide a link between sleep homeostat and circadian clock neurons

Sleep is controlled by homeostatic mechanisms, which drive sleep after wakefulness, and a circadian clock, which confers the 24-h rhythm of sleep. These processes interact with each other to control the timing of sleep in a daily cycle as well as following sleep deprivation. However, the mechanisms by which they interact are poorly understood. We show here that hugin ⁺ neurons, previously identified as neurons that function downstream of the clock to regulate rhythms of locomotor activity, are also targets of the sleep homeostat. Sleep deprivation decreases activity of hugin ⁺ neurons, likely to suppress circadian-driven activity during recovery sleep, and ablation of hugin ⁺ neurons promotes sleep increases generated by activation of the homeostatic sleep locus, the dorsal fan-shaped body (dFB). Also, mutations in peptides produced by the hugin ⁺ locus increase recovery sleep following deprivation. Transsynaptic mapping reveals that hugin ⁺ neurons feed back onto central clock neurons, which also show decreased activity upon sleep loss, in a Hugin peptide-dependent fashion. We propose that hugin ⁺ neurons integrate circadian and sleep signals to modulate circadian circuitry and regulate the timing of sleep.

Balancing Prediction and Surprise: A Role for Active Sleep at the Dawn of Consciousness?

The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising, and this typically evokes prediction error signatures in mammalian brains. In humans such mismatched expectations are often associated with an emotional response as well, and emotional dysregulation can lead to cognitive disorders such as depression or schizophrenia. Emotional responses are understood to be important for memory consolidation, suggesting that positive or negative 'valence' cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolishing error detection and surprise entirely (as could happen by generalization or habituation) is probably maladaptive, as this might undermine the very mechanism that brains use to become better prediction machines. This paradoxical view of brain function as an ongoing balance between prediction and surprise suggests a compelling approach to study and understand the evolution of consciousness in animals. In particular, this view may provide insight into the function and evolution of 'active' sleep. Here, we propose that active sleep - when animals are behaviorally asleep but their brain seems awake - is widespread beyond mammals and birds, and may have evolved as a mechanism for optimizing predictive processing in motile creatures confronted with constantly changing environments. To explore our hypothesis, we progress from humans to invertebrates, investigating how a potential role for rapid eye movement (REM) sleep in emotional regulation in humans could be re-examined as a conserved sleep function that co-evolved alongside selective attention to maintain an adaptive balance between prediction and surprise. This view of active sleep has some interesting implications for the evolution of subjective awareness and consciousness in animals.

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly's head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

Do animals dream?

The understanding of biological functions of sleep has improved recently, including an understanding of the deep evolutionary roots of sleep among animals. However, dreaming as an element of sleep may be particularly difficult to address in non-human animals because in humans dreaming involves a non-wakeful form of awareness typically identified through verbal report. Here, we argue that parallels that exist between the phenomenology, physiology, and sleep behaviors during human dreaming provide an avenue to investigate dreaming in non-human animals. We review three alternative measurements of human dreaming - neural correlates of dreaming, 'replay' of newly-acquired memories, and dream-enacting behaviors - and consider how these may be applied to non-human animal models. We suggest that while animals close in brain structure to humans (such as mammals and birds) may be optimal models for the first two of these measurements, cephalopods, especially octopuses, may be particularly good candidates for the third.

Optogenetic activation of SIFamide (SIFa) neurons induces a complex sleep-promoting effect in the fruit fly Drosophila melanogaster

Sleep is a universal and extremely complicated function. Sleep is regulated by two systems-sleep homeostasis and circadian rhythms. In a wide range of species, neuropeptides have been found to play a crucial role in the communication and synchronization between different components of both systems. In the fruit fly Drosophila melanogaster, SIFamide (SIFa) is a neuropeptide that has been reported to be expressed in 4 neurons in the pars intercerebralis (PI) area of the brain. Previous work has shown that transgenic ablation of SIFa neurons, mutation of SIFa itself, or knockdown of SIFa receptors reduces sleep, suggesting that SIFa is sleep-promoting. However, those were all constitutive manipulations that could have affected development or resulted in compensation, so the role of SIFa signaling in sleep regulation during adulthood remains unclear. In the current study, we examined the sleep-promoting effect of SIFa through an optogenetic approach, which allowed for neuronal activation with high temporal resolution, while leaving development unaffected. We found that activation of the red-light sensor Chrimson in SIFa neurons promoted sleep in flies in a sexually dimorphic manner, where the magnitude of the sleep effect was greater in females than in males. Because neuropeptidergic neurons often also release other transmitters, we used RNA interference to knock down SIFa while also optogenetically activating SIFa neurons. SIFa knockdown only partially reduced the magnitude of the sleep effect, suggesting that release of other transmitters may contribute to the sleep induction when SIFa neurons are activated. Video-based analysis showed that activation of SIFa neurons for as brief a period as 1 second was able to decrease walking behavior for minutes after the stimulus. Future studies should aim to identify the transmitters that are utilized by SIFa neurons and characterize their upstream activators and downstream targets. It would also be of interest to determine how acute optogenetic activation of SIFa neurons alters other behaviors that have been linked to SIFa, such as mating and feeding.

Honeybee Brain Oscillations Are Generated by Microtubules. The Concept of a Brain Central Oscillator

Microtubules (MTs) are important structures of the cytoskeleton in neurons. Mammalian brain MTs act as biomolecular transistors that generate highly synchronous electrical oscillations. However, their role in brain function is largely unknown. To gain insight into the MT electrical oscillatory activity of the brain, we turned to the honeybee (Apis mellifera) as a useful model to isolate brains and MTs. The patch clamp technique was applied to MT sheets of purified honeybee brain MTs. High resistance seal patches showed electrical oscillations that linearly depended on the holding potential between ± 200 mV and had an average conductance in the order of ~9 nS. To place these oscillations in the context of the brain, we also explored local field potential (LFP) recordings from the Triton X-permeabilized whole honeybee brain unmasking spontaneous oscillations after but not before tissue permeabilization. Frequency domain spectral analysis of time records indicated at least two major peaks at approximately ~38 Hz and ~93 Hz in both preparations. The present data provide evidence that MT electrical oscillations are a novel signaling mechanism implicated in brain wave activity observed in the insect brain.

Fly seizure EEG: field potential activity in the Drosophila brain

Hypersynchronous neural activity is a characteristic feature of seizures. Although many Drosophila mutants of epilepsy-related genes display clear behavioral spasms and motor unit hyperexcitability, field potential measurements of aberrant hypersynchronous activity across brain regions during seizures have yet to be described. Here, we report a straightforward method to observe local field potentials (LFPs) from the Drosophila brain to monitor ensemble neural activity during seizures in behaving tethered flies. High frequency stimulation across the brain reliably triggers a stereotypic sequence of electroconvulsive seizure (ECS) spike discharges readily detectable in the dorsal longitudinal muscle (DLM) and coupled with behavioral spasms. During seizure episodes, the LFP signal displayed characteristic large-amplitude oscillations with a stereotypic temporal correlation to DLM flight muscle spiking. ECS-related LFP events were clearly distinct from rest- and flight-associated LFP patterns. We further characterized the LFP activity during different types of seizures originating from genetic and pharmacological manipulations. In the 'bang-sensitive' sodium channel mutant bangsenseless (bss), the LFP pattern was prolonged, and the temporal correlation between LFP oscillations and DLM discharges was altered. Following administration of the pro-convulsant GABA_A blocker picrotoxin, we uncovered a qualitatively different LFP activity pattern, which consisted of a slow (1-Hz), repetitive, waveform, closely coupled with DLM bursting and behavioral spasms. Our approach to record brain LFPs presents an initial framework for electrophysiological analysis of the complex brain-wide activity patterns in the large collection of Drosophila excitability mutants.

The Regulation of Drosophila Sleep

Sleep is critical for diverse aspects of brain function in animals ranging from invertebrates to humans. Powerful genetic tools in the fruit fly Drosophila melanogaster have identified - at an unprecedented level of detail - genes and neural circuits that regulate sleep. This research has revealed that the functions and neural principles of sleep regulation are largely conserved from flies to mammals. Further, genetic approaches to studying sleep have uncovered mechanisms underlying the integration of sleep and many different biological processes, including circadian timekeeping, metabolism, social interactions, and aging. These findings show that in flies, as in mammals, sleep is not a single state, but instead consists of multiple physiological and behavioral states that change in response to the environment, and is shaped by life history. Here, we review advances in the study of sleep in Drosophila, discuss their implications for understanding the fundamental functions of sleep that are likely to be conserved among animal species, and identify important unanswered questions in the field.

Molecular resolution of a behavioral paradox: sleep and arousal are regulated by distinct acetylcholine receptors in different neuronal types in Drosophila

Sleep and arousal are both important for animals. The neurotransmitter acetylcholine (ACh) has long been found to promote both sleep and arousal in mammals, an apparent paradox which has also been found to exist in flies, causing much confusion in understanding sleep and arousal. Here, we have systematically studied all 13 ACh receptors (AChRs) in Drosophila to understand mechanisms underlying ACh function in sleep and arousal. We found that exogenous stimuli-induced arousal was decreased in nAChRα3 mutants, whereas sleep was decreased in nAChRα2 and nAChRβ2 mutants. nAChRα3 functions in dopaminergic neurons to promote exogenous stimuli-induced arousal, whereas nAChRα2 and β2 function in octopaminergic neurons to promote sleep. Our studies have revealed that a single transmitter can promote endogenous sleep and exogenous stimuli-induced arousal through distinct receptors in different types of downstream neurons.

Collective Dynamics of Neural Networks With Sleep-Related Biological Drives in Drosophila

The collective electrophysiological dynamics of the brain as a result of sleep-related biological drives in Drosophila are investigated in this paper. Based on the Huber-Braun thermoreceptor model, the conductance-based neurons model is extended to a coupled neural network to analyze the local field potential (LFP). The LFP is calculated by using two different metrics: the mean value and the distance-dependent LFP. The distribution of neurons around the electrodes is assumed to have a circular or grid distribution on a two-dimensional plane. Regardless of which method is used, qualitatively similar results are obtained that are roughly consistent with the experimental data. During wake, the LFP has an irregular or a regular spike. However, the LFP becomes regular bursting during sleep. To further analyze the results, wavelet analysis and raster plots are used to examine how the LFP frequencies changed. The synchronization of neurons under different network structures is also studied. The results demonstrate that there are obvious oscillations at approximately 8 Hz during sleep that are absent during wake. Different time series of the LFP can be obtained under different network structures and the density of the network will also affect the magnitude of the potential. As the number of coupled neurons increases, the neural network becomes easier to synchronize, but the sleep and wake time described by the LFP spectrogram do not change. Moreover, the parameters that affect the durations of sleep and wake are analyzed.

Challenging sleep homeostasis

In this commentary, I play the Devil’s advocate and assume the title of High Contrarian. I intend to be provocative to challenge long-standing ideas about sleep. I blame all on Professor Craig Heller, who taught me to think this way as a graduate student in his laboratory. Scientists should fearlessly jump into the foaming edge of what we know, but also consider how safe are their intellectual harbors. There are many ideas we accept as ‘known’: that sleep is ubiquitous in the animal kingdom, that it serves vital functions, that it plays an essential role in brain plasticity. All of this could be wrong. As one example, I reexamine the idea that sleep is regulated by a mysterious ‘homeostat’ that determines sleep need based on prior wake time.

Spontaneous electrical low-frequency oscillations: a possible role in Hydra and all living systems

As one of the first model systems in biology, the basal metazoan Hydra has been revealing fundamental features of living systems since it was first discovered by Antonie van Leeuwenhoek in the early eighteenth century. While it has become well-established within cell and developmental biology, this tiny freshwater polyp is only now being re-introduced to modern neuroscience where it has already produced a curious finding: the presence of low-frequency spontaneous neural oscillations at the same frequency as those found in the default mode network in the human brain. Surprisingly, increasing evidence suggests such spontaneous electrical low-frequency oscillations (SELFOs) are found across the wide diversity of life on Earth, from bacteria to humans. This paper reviews the evidence for SELFOs in diverse phyla, beginning with the importance of their discovery in Hydra, and hypothesizes a potential role as electrical organism organizers, which supports a growing literature on the role of bioelectricity as a ‘template’ for developmental memory in organism regeneration.

This article is part of the theme issue ‘Basal cognition: conceptual tools and the view from the single cell’.

A deep sleep stage in Drosophila with a functional role in waste clearance

Sleep is a highly conserved state, suggesting that sleep's benefits outweigh the increased vulnerability it brings. Yet, little is known about how sleep fulfills its functions. Here, we used video tracking in tethered flies to identify a discrete deep sleep stage in Drosophila, termed proboscis extension sleep, that is defined by repeated stereotyped proboscis extensions and retractions. Proboscis extension sleep is accompanied by highly elevated arousal thresholds and decreased brain activity, indicative of a deep sleep state. Preventing proboscis extensions increases injury-related mortality and reduces waste clearance. Sleep deprivation reduces waste clearance and during subsequent rebound sleep, sleep, proboscis extensions, and waste clearance are increased. Together, these results provide evidence of a discrete deep sleep stage that is linked to a specific function and suggest that waste clearance is a core and ancient function of deep sleep.

Sleep Induction by Mechanosensory Stimulation in Drosophila

People tend to fall asleep when gently rocked or vibrated. Experimental studies have shown that rocking promotes sleep in humans and mice. However, the mechanisms underlying the phenomenon are not well understood. A habituation model proposes that habituation, a form of non-associative learning, mediates sleep induction by monotonous stimulation. Here, we show that gentle vibration promotes sleep in Drosophila in part through habituation. Vibration-induced sleep (VIS) leads to increased homeostatic sleep credit and reduced arousability, and can be suppressed by heightened arousal or reduced GABA signaling. Multiple mechanosensory organs mediate VIS, and the magnitude of VIS depends on vibration frequency and genetic background. Sleep induction improves over successive blocks of vibration. Furthermore, training with continuous vibration does not generalize to intermittent vibration, demonstrating stimulus specificity, a characteristic of habituation. Our findings suggest that habituation plays a significant role in sleep induction by vibration.

Öztürk-Çolak et al. demonstrate that gentle vibration induces sleep in Drosophila. The authors show that sleep induction improves over multiple vibration sessions, which suggests that habituation, a form of simple learning, plays a significant role in vibration-induced sleep.

A Paradoxical Kind of Sleep in Drosophila melanogaster

The dynamic nature of sleep in many animals suggests distinct stages that serve different functions. Genetic sleep induction methods in animal models provide a powerful way to disambiguate these stages and functions, although behavioral methods alone are insufficient to accurately identify what kind of sleep is being engaged. In Drosophila, activation of the dorsal fan-shaped body (dFB) promotes sleep, but it remains unclear what kind of sleep this is, how the rest of the fly brain is behaving, or if any specific sleep functions are being achieved. Here, we developed a method to record calcium activity from thousands of neurons across a volume of the fly brain during spontaneous sleep and compared this to dFB-induced sleep. We found that spontaneous sleep typically transitions from an active "wake-like" stage to a less active stage. In contrast, optogenetic activation of the dFB promotes sustained wake-like levels of neural activity even though flies become unresponsive to mechanical stimuli. When we probed flies with salient visual stimuli, we found that the activity of visually responsive neurons in the central brain was blocked by transient dFB activation, confirming an acute disconnect from the external environment. Prolonged optogenetic dFB activation nevertheless achieved a key sleep function by correcting visual attention defects brought on by sleep deprivation. These results suggest that dFB activation promotes a distinct form of sleep in Drosophila, where brain activity appears similar to wakefulness, but responsiveness to external sensory stimuli is profoundly suppressed.

Oscillations in the central brain of Drosophila are phase locked to attended visual features

Object-based attention describes the brain's capacity to prioritize one set of stimuli while ignoring others. Human research suggests that the binding of diverse stimuli into one attended percept requires phase-locked oscillatory activity in the brain. Even insects display oscillatory brain activity during visual attention tasks, but it is unclear if neural oscillations in insects are selectively correlated to different features of attended objects. We addressed this question by recording local field potentials in the Drosophila central complex, a brain structure involved in visual navigation and decision making. We found that attention selectively increased the neural gain of visual features associated with attended objects and that attention could be redirected to unattended objects by activation of a reward circuit. Attention was associated with increased beta (20- to 30-Hz) oscillations that selectively locked onto temporal features of the attended visual objects. Our results suggest a conserved function for the beta frequency range in regulating selective attention to salient visual features.

Sleep Circuits and Physiology in Non-Mammalian Systems

Research over the last 20 years has firmly established the existence of sleep states across the animal kingdom. Work in non-mammalian animal models such as nematodes, fruit flies, and zebrafish has now uncovered many evolutionarily conserved aspects of sleep physiology and regulation, including shared circuit architecture, homeostatic and circadian control elements, and principles linking sleep physiology to function. Non-mammalian sleep research is now shedding light on fundamental aspects of the genetic and neuronal circuit regulation of sleep, with direct implications for the understanding of how sleep is regulated in mammals.

Drosophila as a Model to Study the Relationship Between Sleep, Plasticity, and Memory

Humans spend nearly a third of their life sleeping, yet, despite decades of research the function of sleep still remains a mystery. Sleep has been linked with various biological systems and functions, including metabolism, immunity, the cardiovascular system, and cognitive functions. Importantly, sleep appears to be present throughout the animal kingdom suggesting that it must provide an evolutionary advantage. Among the many possible functions of sleep, the relationship between sleep, and cognition has received a lot of support. We have all experienced the negative cognitive effects associated with a night of sleep deprivation. These can include increased emotional reactivity, poor judgment, deficit in attention, impairment in learning and memory, and obviously increase in daytime sleepiness. Furthermore, many neurological diseases like Alzheimer’s disease often have a sleep disorder component. In some cases, the sleep disorder can exacerbate the progression of the neurological disease. Thus, it is clear that sleep plays an important role for many brain functions. In particular, sleep has been shown to play a positive role in the consolidation of long-term memory while sleep deprivation negatively impacts learning and memory. Importantly, sleep is a behavior that is adapted to an individual’s need and influenced by many external and internal stimuli. In addition to being an adaptive behavior, sleep can also modulate plasticity in the brain at the level of synaptic connections between neurons and neuronal plasticity influences sleep. Understanding how sleep is modulated by internal and external stimuli and how sleep can modulate memory and plasticity is a key question in neuroscience. In order to address this question, several animal models have been developed. Among them, the fruit fly Drosophila melanogaster with its unparalleled genetics has proved to be extremely valuable. In addition to sleep, Drosophila has been shown to be an excellent model to study many complex behaviors, including learning, and memory. This review describes our current knowledge of the relationship between sleep, plasticity, and memory using the fly model.

Covert sleep-related biological processes are revealed by probabilistic analysis in Drosophila

Reduced sleep duration and disrupted sleep quality are correlated with adverse mental and physical health outcomes. Better tools for measuring the internal drives for sleep and wake in model organisms would facilitate understanding the role of sleep quality in health. We defined two conditional probabilities, P(Wake) and P(Doze), that can be calculated from recordings of Drosophila activity without disturbing the animal. We demonstrated that P(Wake) is a measure of sleep depth and that P(Doze) is a measure of sleep pressure. In parallel, we developed an automatic classifier for state-based analysis of Drosophila behavior. These analysis tools will improve our understanding of the pharmacology and neuronal regulation of behavioral drives in the Drosophila brain.

Sleep pressure and sleep depth are key regulators of wake and sleep. Current methods of measuring these parameters in Drosophila melanogaster have low temporal resolution and/or require disrupting sleep. Here we report analysis tools for high-resolution, noninvasive measurement of sleep pressure and depth from movement data. Probability of initiating activity, P(Wake), measures sleep depth while probability of ceasing activity, P(Doze), measures sleep pressure. In vivo and computational analyses show that P(Wake) and P(Doze) are largely independent and control the amount of total sleep. We also develop a Hidden Markov Model that allows visualization of distinct sleep/wake substates. These hidden states have a predictable relationship with P(Doze) and P(Wake), suggesting that the methods capture the same behaviors. Importantly, we demonstrate that both the Doze/Wake probabilities and the sleep/wake substates are tied to specific biological processes. These metrics provide greater mechanistic insight into behavior than measuring the amount of sleep alone.

Drosophila insulin-like peptide 2 mediates dietary regulation of sleep intensity

Sleep is a nearly universal behavior that is regulated by diverse environmental stimuli and physiological states. A defining feature of sleep is a homeostatic rebound following deprivation, where animals compensate for lost sleep by increasing sleep duration and/or sleep depth. The fruit fly, Drosophila melanogaster, exhibits robust recovery sleep following deprivation and represents a powerful model to study neural circuits regulating sleep homeostasis. Numerous neuronal populations have been identified in modulating sleep homeostasis as well as depth, raising the possibility that the duration and quality of recovery sleep is dependent on the environmental or physiological processes that induce sleep deprivation. Here, we find that unlike most pharmacological and environmental manipulations commonly used to restrict sleep, starvation potently induces sleep loss without a subsequent rebound in sleep duration or depth. Both starvation and a sucrose-only diet result in increased sleep depth, suggesting that dietary protein is essential for normal sleep depth and homeostasis. Finally, we find that Drosophila insulin like peptide 2 (Dilp2) is acutely required for starvation-induced changes in sleep depth without regulating the duration of sleep. Flies lacking Dilp2 exhibit a compensatory sleep rebound following starvation-induced sleep deprivation, suggesting Dilp2 promotes resiliency to sleep loss. Together, these findings reveal innate resilience to starvation-induced sleep loss and identify distinct mechanisms that underlie starvation-induced changes in sleep duration and depth.

Sleep is nearly universal throughout the animal kingdom and homeostatic regulation represents a defining feature of sleep, where animals compensate for lost sleep by increasing sleep over subsequent time periods. Despite the robustness of this feature, the neural mechanisms regulating recovery from different types of sleep deprivation are not fully understood. Fruit flies provide a powerful model for investigating the genetic regulation of sleep, and like mammals, display robust recovery sleep following deprivation. Here, we find that unlike most stimuli that suppress sleep, sleep deprivation by starvation does not require a homeostatic rebound. These findings are likely due to flies engaging in deeper sleep during the period of partial sleep deprivation, suggesting a natural resilience to starvation-induced sleep loss. This unique resilience to starvation-induced sleep loss is dependent on Drosophila insulin-like peptide 2, revealing a critical role for insulin signaling in regulating interactions between diet and sleep homeostasis.

Presynaptic Active Zone Plasticity Encodes Sleep Need in Drosophila

Sleep is universal across species and essential for quality of life and health, as evidenced by the consequences of sleep loss. Sleep might homeostatically normalize synaptic gains made over wake states in order to reset information processing and storage and support learning, and sleep-associated synaptic (ultra)structural changes have been demonstrated recently. However, causal relationships between the molecular and (ultra)structural status of synapses, sleep homeostatic regulation, and learning processes have yet to be established. We show here that the status of the presynaptic active zone can directly control sleep in Drosophila. Short sleep mutants showed a brain-wide upregulation of core presynaptic scaffold proteins and release factors. Increasing the gene copy number of ELKS-family scaffold master organizer Bruchpilot (BRP) not only mimicked changes in the active zone scaffold and release proteins but importantly provoked sleep in a dosage-dependent manner, qualitatively and quantitatively reminiscent of sleep deprivation effects. Conversely, reducing the brp copy number decreased sleep in short sleep mutant backgrounds, suggesting a specific role of the active zone plasticity in homeostatic sleep regulation. Finally, elimination of BRP specifically in the sleep-promoting R2 neurons of 4xBRP animals partially restored sleep patterns and rescued learning deficits. Our results suggest that the presynaptic active zone plasticity driven by BRP operates as a sleep homeostatic actuator that also restricts periods of effective learning.

Sleep Regulates Glial Plasticity and Expression of the Engulfment Receptor Draper Following Neural Injury

Chronic sleep disturbance is associated with numerous health consequences, including neurodegenerative disease and cognitive decline [1]. Neurite damage due to apoptosis, trauma, or genetic factors is a common feature of aging, and clearance of damaged neurons is essential for maintenance of brain function. In the central nervous system, damaged neurites are cleared by Wallerian degeneration, in which activated microglia and macrophages engulf damaged neurons [2]. The fruit fly Drosophila melanogaster provides a powerful model for investigating the relationship between sleep and Wallerian degeneration [3]. Several lines of evidence suggest that glia influence sleep duration, sleep-mediated neuronal homeostasis, and clearance of toxic substances during sleep, raising the possibility that glial engulfment of damaged axons is regulated by sleep [4]. To explore this possibility, we axotomized olfactory receptor neurons and measured the effects of sleep loss or gain on the clearance of damaged neurites. Mechanical and genetic sleep deprivation impaired the clearance of damaged neurites. Conversely, treatment with the sleep-promoting drug gaboxadol accelerated clearance, while genetic induction of sleep promotes Draper expression. In sleep-deprived animals, multiple markers of glial activation were delayed, including activation of the JAK-STAT pathway, upregulation of the cell corpse engulfment receptor Draper, and innervation of the antennal lobe by glial membranes. These markers were all enhanced following genetic and pharmacological sleep induction. Taken together, these findings reveal a critical association between sleep and glial activation following neural injury, providing a platform for further investigations of the molecular mechanisms underlying sleep-dependent modulation of glial function and neurite clearance.

Alpha oscillations govern interhemispheric spike timing coordination in the honey bee brain

In 1929 Hans Berger discovered the alpha oscillations: prominent, ongoing oscillations around 10 Hz in the electroencephalogram of the human brain. These alpha oscillations are among the most widely studied brain signals, related to cognitive phenomena such as attention, memory and consciousness. However, the mechanisms by which alpha oscillations affect human cognition await demonstration. Here, we suggest the honey bee brain as an experimentally more accessible model system for investigating the functional role of alpha oscillations. We found a prominent spontaneous oscillation around 18 Hz that is reduced in amplitude upon olfactory stimulation. Similar to alpha oscillations in primates, the phase of this oscillation biased both timing of neuronal spikes and amplitude of high-frequency gamma activity (40-450 Hz). These results suggest a common role of alpha oscillations across phyla and provide an unprecedented new venue for causal studies on the relationship between neuronal spikes, brain oscillations and cognition.

Controllability of Networks of Multiple Coupled Neural Populations: An Analytical Method for Neuromodulation's Feasibility

Neuromodulation plays a vital role in the prevention and treatment of neurological and psychiatric disorders. Neuromodulation's feasibility is a long-standing issue because it provides the necessity for neuromodulation to realize the desired purpose. A controllability analysis of neural dynamics is necessary to ensure neuromodulation's feasibility. Here, we present such a theoretical method by using the concept of controllability from the control theory that neuromodulation's feasibility can be studied smoothly. Firstly, networks of multiple coupled neural populations with different topologies are established to mathematically model complicated neural dynamics. Secondly, an analytical method composed of a linearization method, the Kalman controllable rank condition and a controllability index is applied to analyze the controllability of the established network models. Finally, the relationship between network dynamics or topological characteristic parameters and controllability is studied by using the analytical method. The proposed method provides a new idea for the study of neuromodulation's feasibility, and the results are expected to guide us to better modulate neurodynamics by optimizing network dynamics and network topology.