Bruno van Swinderen

During sleep, behavioral responsiveness to external stimuli is decreased. This classical definition of sleep has been applied effectively across the animal kingdom to identify this common behavioral state in a growing list of creatures, from mammals to invertebrates. Yet, it remains unclear whether decreased behavioral responsiveness during sleep is necessarily associated with decreased responsiveness in brain activity, especially in insects. Here, we performed long-term multichannel electrophysiology in tethered Drosophila melanogaster flies exposed continuously to repetitive visual stimuli. Flies were still able to sleep under these visual stimulation conditions, as determined by traditional immobility duration criteria for the field. Interestingly, we did not find any difference between responses to repetitive visual stimuli during sleep compared with wake when we recorded local field potentials (LFPs) across a transect of the fly brain from optic lobes to the central brain. However, we did find LFP responses to be altered when visual stimuli were variable and of lower probability, especially in the central brain. Central brain responses to less predictable or ‘deviant’ stimuli were lower during the deepest stage of sleep, a time of quiescence characterized by more regular proboscis extensions. This shows that the sleeping fly brain processes low-probability visual stimuli in a different way from more repeated stimuli, and presents Drosophila as a promising model for studying the potential role of sleep in regulating predictive processing.

During sleep, behavioral responsiveness to external stimuli is decreased. This classical definition of sleep has been applied effectively across the animal kingdom to identify this common behavioral state in a growing list of creatures, from mammals to invertebrates. Yet it remains unclear whether decreased behavioral responsiveness during sleep is necessarily associated with decreased responsiveness in brain activity, especially in relative latecomers to the sleep field, such as insects. Here, we perform long-term multichannel electrophysiology in tethered Drosophila melanogaster flies exposed continuously to flashing visual stimuli. Flies were still able to sleep under these visual stimulation conditions, as determined by traditional immobility duration criteria for the field. Interestingly, local field potentials (LFPs) recorded in a transect through the fly brain failed to show any difference in amplitude during sleep compared to wake when the visual stimuli were invariant. In contrast, LFP responses were lower when visual stimuli were variable and of lower probability, especially in the central brain. Central brain responses to ‘deviant’ stimuli were lowest during the deepest stage of sleep, characterized by more regular proboscis extensions. This shows that the sleeping fly brain processes low-probability visual stimuli in a different way than more repeated stimuli and presents Drosophila as a model system for studying the potential role of sleep in regulating predictive processing. SUMMARY STATEMENT: The sleeping fly brain still responds to visual stimuli. However, response amplitudes depend on stimulus history and probability, as well as recording location.

The transformation of navigational variables into coordinated motor actions is a fundamental requirement for autonomous locomotion. The circuit and control mechanisms that underlie this transformation are not well understood. Here, we combine connectomics, neuronal activity perturbations, functional imaging and electrophysiology to identify a central steering circuit in Drosophila . This steering circuit operates in both goal-directed navigation and exploratory search and controls turning during both walking and flight, by implementing a hierarchical, stepwise transformation from navigation-related signals to motor output. At the top of the hierarchy are the reciprocally connected DNa03 and LAL013 neurons. DNa03 integrates lateralized sensory and internal information to generate an effector-agnostic steering signal during goal-directed navigation. LAL013 promotes exploratory turning in response to bilateral input from ExR7 neurons of the central complex, which encode the uncertainty of the fly’s internal heading estimate. Both DNa03 and LAL013 provide input to a set of hierarchically organized descending neurons, at the top of which is DNa11. DNa11 targets leg motor circuits directly as well as indirectly through subordinate descending neurons, and its activation coordinately changes the stepping directions of all six legs to generate rapid saccadic turns. In contrast to DNa03, DNa11 shows unilateral, delayed and low pass filtered activity during a turn. The signal transformation between DNa03 and DNa11 thus marks the transition from motor planning to the execution of a walking turn. Together, our results reveal a hierarchical circuit architecture that transforms navigational variables into abstract steering representations and ultimately into motor commands, providing a general framework for flexible control of behaviour across contexts and motor systems.

General anesthetics disrupt brain network dynamics through multiple pathways, in part through postsynaptic potentiation of inhibitory ion channels as well as presynaptic inhibition of neuroexocytosis. Common clinical general anesthetic drugs, such as propofol and isoflurane, have been shown to interact and interfere with core components of the exocytic release machinery to cause impaired neurotransmitter release. Recent studies however suggest that these drugs do not affect all synapse subtypes equally. We investigated the role of the presynaptic release machinery in multiple neurotransmitter systems under isoflurane general anesthesia in the adult female Drosophila brain using live-cell superresolution microscopy and optogenetic readouts of exocytosis and neural excitability. We activated neurotransmitter-specific mushroom body output neurons and imaged presynaptic function under isoflurane anesthesia. We found that isoflurane impaired synaptic release and presynaptic protein dynamics in excitatory cholinergic synapses. In contrast, isoflurane had little to no effect on inhibitory GABAergic or glutamatergic synapses. These results present a distinct inhibitory mechanism for general anesthesia, whereby neuroexocytosis is selectively impaired at excitatory synapses, while inhibitory synapses remain functional. This suggests a presynaptic inhibitory mechanism that complements the other inhibitory effects of these drugs.

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.

How general anesthetics work remains a topic of ongoing study. A parallel field of research has sought to identify methods to reverse general anesthesia. Reversal agents could shorten patients’ recovery time and potentially reduce the risk of postoperative complications. An incomplete understanding of the mechanisms of general anesthesia has hampered the pursuit for reversal agents. Nevertheless, the search for reversal agents has furthered understanding of the mechanisms underlying general anesthesia. The study of potential reversal agents has highlighted the importance of rigorous criteria to assess recovery from general anesthesia in animal models, and has helped identify key arousal systems (e.g., cholinergic, dopaminergic, and orexinergic systems) relevant to emergence from general anesthesia. Furthermore, the effects of reversal agents have been found to be inconsistent across different general anesthetics, revealing differences in mechanisms among these drugs. The presynapse and glia probably also contribute to general anesthesia recovery alongside postsynaptic receptors. The next stage in the search for reversal agents will have to consider alternate mechanisms encompassing the tripartite synapse.

Sleep studies in Drosophila melanogaster rely mostly on behavioral read-outs to support molecular or circuit-level investigations in this model. Electrophysiology can provide an additional level of understanding in these studies to, for example, investigate changes in brain activity associated with sleep manipulations. In this protocol, we describe a procedure for performing multichannel local field potential (LFP) recordings in the fruit fly, with a flexible system that can be adapted to different experimental paradigms and situations. The approach uses electrodes containing multiple recording sites (16), allowing the acquisition of large amounts of neuronal activity data from a transect through the brain while flies are still able to sleep. The approach starts by tethering the fly, followed by positioning it on an air-supported ball. A multichannel silicon probe is then inserted laterally into the fly brain via one eye, allowing for recording of electrical signals from the retina through to the central brain. These recordings can be acquired under spontaneous conditions or in the presence of visual stimuli, and the minimal surgery promotes long-term recordings (e.g., overnight). Sleep and wake can be tracked using infrared cameras, which allow for the measurement of locomotive activity as well as microbehaviors such as proboscis extensions during sleep. The protocol has been optimized to promote subject survivability, which is an important factor when performing long-term (∼16-h) recordings. The approach described here uses specific recording probes, data acquisition devices, and analysis tools. Although it is expected that some of these items might need to be adapted to the equipment available in different laboratories, the overall aim is to provide an overview on how to record electrical activity across the brain of behaving (and sleeping) flies using this kind of approach and technology.

Sleep is likely a whole-brain phenomenon, with most of the brain probably benefiting from this state of decreased arousal. Recent advances in our understanding of some potential sleep functions, such as metabolite clearance and synaptic homeostasis, make it evident why the whole brain is likely impacted by sleep: All neurons have synapses, and all neurons produce waste metabolites. Sleep experiments in the fly Drosophila melanogaster suggest that diverse sleep functions appear to be conserved across all animals. Studies of brain activity during sleep in humans typically involve multidimensional data sets, such as those acquired by electroencephalograms (EEGs) or functional magnetic resonance imaging (fMRI), and these whole-brain read-outs often reveal important qualities of different sleep stages, such as changes in frequency dynamics or connectivity. Recently, various techniques have been developed that allow for the recording of neural activity simultaneously across multiple regions of the fly brain. These whole-brain-recording approaches will be important for better understanding sleep physiology and function, as they provide a more comprehensive view of neural dynamics during sleep and wake in a relevant model system. Here, we present a brief summary of some of the findings derived from sleep activity recording studies in sleeping Drosophila flies and discuss the value of electrophysiological versus calcium imaging techniques. Although these involve very different preparations, they both highlight the value of multidimensional data for studying sleep in this model system, like the use of both EEG and fMRI in humans.