Synapse-Specific Trapping of SNARE Machinery Proteins in the Anesthetized Drosophila Brain.

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 super-resolution 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.

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.

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.

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.

Using an abstract geometry in virtual reality to explore choice behaviour: visual flicker preferences in honeybees.

Closed-loop paradigms provide an effective approach for studying visual choice behaviour and attention in small animals. Different flying and walking paradigms have been developed to investigate behavioural and neuronal responses to competing stimuli in insects such as bees and flies. However, the variety of stimulus choices that can be presented over one experiment is often limited. Current choice paradigms are mostly constrained as single binary choice scenarios that are influenced by the linear structure of classical conditioning paradigms. Here, we present a novel behavioural choice paradigm that allows animals to explore a closed geometry of interconnected binary choices by repeatedly selecting among competing objects, thereby revealing stimulus preferences in an historical context. We used our novel paradigm to investigate visual flicker preferences in honeybees (Apis mellifera) and found significant preferences for 20-25 Hz flicker and avoidance of higher (50-100 Hz) and lower (2-4 Hz) flicker frequencies. Similar results were found when bees were presented with three simultaneous choices instead of two, and when they were given the chance to select previously rejected choices. Our results show that honeybees can discriminate among different flicker frequencies and that their visual preferences are persistent even under different experimental conditions. Interestingly, avoided stimuli were more attractive if they were novel, suggesting that novelty salience can override innate preferences. Our recursive virtual reality environment provides a new approach to studying visual discrimination and choice behaviour in animals.