Visually Guided Behavior and Optogenetically Induced Learning in Head-Fixed Flies Exploring a Virtual Landscape

AFD Thermosensory Neurons Mediate Tactile-Dependent Locomotion Modulation in C. elegans

Sensory neurons drive animal behaviors by detecting environmental stimuli and relaying information to downstream circuits. Beyond their primary roles in sensing, these neurons often form additional synaptic connections outside their main sensory modality, suggesting broader contributions to behavior modulation. Here, we uncover an unexpected role for the thermosensory neuron AFD in coupling tactile experience to locomotion modulation in Caenorhabditis elegans. We show that while AFD employs cGMP signaling for both thermotaxis and tactile-dependent modulation, the specific molecular components of the cGMP pathway differ between these two processes. Interestingly, disrupting the dendritic sensory apparatus of AFD, which is essential for thermotaxis, does not impair tactile-based locomotion modulation, indicating that AFD can mediate tactile-dependent behavior independently of its thermosensory apparatus. In contrast, ablating the AFD neuron eliminates tactile-dependent modulation, pointing to an essential role for AFD itself, rather than its sensory dendritic endings. Further, we find tactile-dependent modulation requires the AIB interneuron, which connects AFD to touch circuits via electrical synapses. Removing innexins expressed in AFD and AIB abolishes this modulation, while re-establishing AFD-AIB connections with engineered electrical synapses restores it. Collectively, these findings uncover a previously unrecognized function of AFD beyond thermosensation, highlighting its influence on context-dependent neuroplasticity and behavioral modulation through broader circuit connectivity.

Driver lines for studying associative learning in Drosophila

The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, investigation of many cell types upstream and downstream of the MB has been hindered due to lack of specific driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified a sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.

Overlap and divergence of neural circuits mediating distinct behavioral responses to sugar

How do neural circuits coordinate multiple behavioral responses to a single sensory cue? Here, we investigate how sweet taste drives appetitive behaviors in Drosophila, including feeding, locomotor suppression, spatial preference, and associative learning. We find that neural circuits mediating different innate responses to sugar are partially overlapping and diverge at the second and third layers. Connectomic analyses reveal distinct subcircuits that mediate different behaviors. Connectome-based simulations of neuronal activity predict that second-order sugar neurons act synergistically to promote downstream activity and that bitter input overrides the sugar circuit through multiple pathways acting at third- and fourth-order neurons. Consistent with the latter prediction, optogenetic experiments suggest that bitter input inhibits third- and fourth-order sugar neurons to override the sugar pathway, whereas hunger and diet act earlier in the circuit to modulate behavior. Together, these studies provide insight into how circuits are organized to drive diverse behavioral responses to a single stimulus.

Connectomic reconstruction predicts visual features used for navigation

Many animals use visual information to navigate1-4, but how such information is encoded and integrated by the navigation system remains incompletely understood. In Drosophila melanogaster, EPG neurons in the central complex compute the heading direction5 by integrating visual input from ER neurons6-12, which are part of the anterior visual pathway (AVP)10,13-16. Here we densely reconstruct all neurons in the AVP using electron-microscopy data17. The AVP comprises four neuropils, sequentially linked by three major classes of neurons: MeTu neurons10,14,15, which connect the medulla in the optic lobe to the small unit of the anterior optic tubercle (AOTUsu) in the central brain; TuBu neurons9,16, which connect the AOTUsu to the bulb neuropil; and ER neurons6-12, which connect the bulb to the EPG neurons. On the basis of morphologies, connectivity between neural classes and the locations of synapses, we identify distinct information channels that originate from four types of MeTu neurons, and we further divide these into ten subtypes according to the presynaptic connections in the medulla and the postsynaptic connections in the AOTUsu. Using the connectivity of the entire AVP and the dendritic fields of the MeTu neurons in the optic lobes, we infer potential visual features and the visual area from which any ER neuron receives input. We confirm some of these predictions physiologically. These results provide a strong foundation for understanding how distinct sensory features can be extracted and transformed across multiple processing stages to construct higher-order cognitive representations.

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

Exploration-exploitation trade-off is regulated by metabolic state and taste value in Drosophila

Similar to other animals, the fly, Drosophila melanogaster, changes its foraging strategy from exploration to exploitation upon encountering a nutrient-rich food source. However, the impact of metabolic state or taste/nutrient value on exploration vs. exploitation decisions in flies is poorly understood. Here, we developed a one-source foraging assay that uses automated video tracking coupled with high-resolution measurements of food ingestion to investigate the behavioral variables flies use when foraging for food with different taste/caloric values and when in different metabolic states. We found that flies alter their foraging and ingestive behaviors based on their hunger state and the concentration of the sucrose solution. Interestingly, sugar-blind flies did not transition from exploration to exploitation upon finding a high-concentration sucrose solution, suggesting that taste sensory input, as opposed to post-ingestive nutrient feedback, plays a crucial role in determining the foraging decisions of flies. Using a Generalized Linear Model (GLM), we showed that hunger state and sugar volume ingested, but not the nutrient or taste value of the food, influence flies' radial distance to the food source, a strong indicator of exploitation. Our behavioral paradigm and theoretical framework offer a promising avenue for investigating the neural mechanisms underlying state and value-based foraging decisions in flies, setting the stage for systematically identifying the neuronal circuits that drive these behaviors.

HisCl1 regulates gustatory habituation in sweet taste neurons and mediates sugar ingestion in Drosophila

Similar to other animals, the fly, Drosophila melanogaster, reduces its responsiveness to tastants with repeated exposure, a phenomenon called gustatory habituation. Previous studies have focused on the circuit basis of gustatory habituation in the fly chemosensory system1,2. However, gustatory neurons reduce their firing rate during repeated stimulation3, suggesting that cell-autonomous mechanisms also contribute to habituation. Here, we used deep learning-based pose estimation and optogenetic stimulation to demonstrate that continuous activation of sweet taste neurons causes gustatory habituation in flies. We conducted a transgenic RNAi screen to identify genes involved in this process and found that knocking down Histamine-gated chloride channel subunit 1 (HisCl1) in the sweet taste neurons significantly reduced gustatory habituation. Anatomical analysis showed that HisCl1 is expressed in the sweet taste neurons of various chemosensory organs. Using single sensilla electrophysiology, we showed that sweet taste neurons reduced their firing rate with prolonged exposure to sucrose. Knocking down HisCl1 in sweet taste neurons suppressed gustatory habituation by reducing the spike frequency adaptation observed in these neurons during high-concentration sucrose stimulation. Finally, we showed that flies lacking HisCl1 in sweet taste neurons increased their consumption of high-concentration sucrose solution at their first meal bout compared to control flies. Together, our results demonstrate that HisCl1 tunes spike frequency adaptation in sweet taste neurons and contributes to gustatory habituation and food intake regulation in flies. Since HisCl1 is highly conserved across many dipteran and hymenopteran species, our findings open a new direction in studying insect gustatory habituation.

Temporal effects of sugar intake on fly local search and honey bee dance behaviour

Honey bees communicate flight navigational information of profitable food to nestmates via their dance, a small-scale walking pattern, inside the nest. Hungry flies and honey bee foragers exhibit a sugar-elicited search involving path integration that bears a resemblance to dance behaviour. This study aimed to investigate the temporal dynamics of the initiation of sugar-elicited search and dance behaviour, using a comparative approach. Passive displacement experiments showed that feeding and the initiation of search could be spatially and temporally dissociated. Sugar intake increased the probability of initiating a search but the actual onset of walking triggers the path integration system to guide the search. When prevented from walking after feeding, flies and bees maintained their motivation for a path integration-based search for a duration of 3 min. In flies, turning and associated characters were significantly reduced during this period but remained higher than in flies without sugar stimulus. These results suggest that sugar elicits two independent behavioural responses: path integration and increased turning, with the initiation and duration of path integration system being temporally restricted. Honey bee dance experiments demonstrated that the motivation of foragers to initiate dance persisted for 15 min, while the number of circuits declined after 3 min following sugar ingestion. Based on these findings, we propose that food intake during foraging increases the probability to initiate locomotor behaviours involving the path integration system in both flies and honey bees, and this ancestral connection might have been co-opted and elaborated during the evolution of dance communication by honey bees.

A perspective on neuroethology: what the past teaches us about the future of neuroethology

For 100 years, the Journal of Comparative Physiology-A has significantly supported research in the field of neuroethology. The celebration of the journal's centennial is a great time point to appreciate the recent progress in neuroethology and to discuss possible avenues of the field. Animal behavior is the main source of inspiration for neuroethologists. This is illustrated by the huge diversity of investigated behaviors and species. To explain behavior at a mechanistic level, neuroethologists combine neuroscientific approaches with sophisticated behavioral analysis. The rapid technological progress in neuroscience makes neuroethology a highly dynamic and exciting field of research. To summarize the recent scientific progress in neuroethology, I went through all abstracts of the last six International Congresses for Neuroethology (ICNs 2010-2022) and categorized them based on the sensory modalities, experimental model species, and research topics. This highlights the diversity of neuroethology and gives us a perspective on the field's scientific future. At the end, I highlight three research topics that may, among others, influence the future of neuroethology. I hope that sharing my roots may inspire other scientists to follow neuroethological approaches.

Reward expectations direct learning and drive operant matching in Drosophila

Foraging animals must use decision-making strategies that dynamically adapt to the changing availability of rewards in the environment. A wide diversity of animals do this by distributing their choices in proportion to the rewards received from each option, Herrnstein's operant matching law. Theoretical work suggests an elegant mechanistic explanation for this ubiquitous behavior, as operant matching follows automatically from simple synaptic plasticity rules acting within behaviorally relevant neural circuits. However, no past work has mapped operant matching onto plasticity mechanisms in the brain, leaving the biological relevance of the theory unclear. Here, we discovered operant matching in Drosophila and showed that it requires synaptic plasticity that acts in the mushroom body and incorporates the expectation of reward. We began by developing a dynamic foraging paradigm to measure choices from individual flies as they learn to associate odor cues with probabilistic rewards. We then built a model of the fly mushroom body to explain each fly's sequential choice behavior using a family of biologically realistic synaptic plasticity rules. As predicted by past theoretical work, we found that synaptic plasticity rules could explain fly matching behavior by incorporating stimulus expectations, reward expectations, or both. However, by optogenetically bypassing the representation of reward expectation, we abolished matching behavior and showed that the plasticity rule must specifically incorporate reward expectations. Altogether, these results reveal the first synapse-level mechanisms of operant matching and provide compelling evidence for the role of reward expectation signals in the fly brain.

Displacement experiments provide evidence for path integration in Drosophila

Like many other animals, insects are capable of returning to previously visited locations using path integration, which is a memory of travelled direction and distance. Recent studies suggest that Drosophila can also use path integration to return to a food reward. However, the existing experimental evidence for path integration in Drosophila has a potential confound: pheromones deposited at the site of reward might enable flies to find previously rewarding locations even without memory. Here, we show that pheromones can indeed cause naïve flies to accumulate where previous flies had been rewarded in a navigation task. Therefore, we designed an experiment to determine if flies can use path integration memory despite potential pheromonal cues by displacing the flies shortly after an optogenetic reward. We found that rewarded flies returned to the location predicted by a memory-based model. Several analyses are consistent with path integration as the mechanism by which flies returned to the reward. We conclude that although pheromones are often important in fly navigation and must be carefully controlled for in future experiments, Drosophila may indeed be capable of performing path integration.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

The influence of stimulus history on directional coding in the monarch butterfly brain

The central complex is a brain region in the insect brain that houses a neural network specialized to encode directional information. Directional coding has traditionally been investigated with compass cues that revolve in full rotations and at constant angular velocities around the insect's head. However, these stimulus conditions do not fully simulate an insect's sensory perception of compass cues during navigation. In nature, an insect flight is characterized by abrupt changes in moving direction as well as constant changes in velocity. The influence of such varying cue dynamics on compass coding remains unclear. We performed long-term tetrode recordings from the brain of monarch butterflies to study how central complex neurons respond to different stimulus velocities and directions. As these butterflies derive directional information from the sun during migration, we measured the neural response to a virtual sun. The virtual sun was either presented as a spot that appeared at random angular positions or was rotated around the butterfly at different angular velocities and directions. By specifically manipulating the stimulus velocity and trajectory, we dissociated the influence of angular velocity and direction on compass coding. While the angular velocity substantially affected the tuning directedness, the stimulus trajectory influenced the shape of the angular tuning curve. Taken together, our results suggest that the central complex flexibly adjusts its directional coding to the current stimulus dynamics ensuring a precise compass even under highly demanding conditions such as during rapid flight maneuvers.

Naturalistic neuroscience and virtual reality

Virtual reality (VR) is one of the techniques that became particularly popular in neuroscience over the past few decades. VR experiments feature a closed-loop between sensory stimulation and behavior. Participants interact with the stimuli and not just passively perceive them. Several senses can be stimulated at once, large-scale environments can be simulated as well as social interactions. All of this makes VR experiences more natural than those in traditional lab paradigms. Compared to the situation in field research, a VR simulation is highly controllable and reproducible, as required of a laboratory technique used in the search for neural correlates of perception and behavior. VR is therefore considered a middle ground between ecological validity and experimental control. In this review, I explore the potential of VR in eliciting naturalistic perception and behavior in humans and non-human animals. In this context, I give an overview of recent virtual reality approaches used in neuroscientific research.

A place learning assay for tethered walking Drosophila

BACKGROUND

Drosophila shows a range of visually guided memory and learning behaviors, including place learning. Investigating the dynamics of neural circuits underlying such behaviors requires learning assays in tethered animals, compatible with in vivo imaging experiments.

NEW METHOD

Here, we introduce an assay for place learning for tethered walking flies. A cylindrical arena is rotated and translated in real time around the fly in concert with the rotational and translational walking activity measured with an air supported ball, resulting in a mechanical virtual reality (VR).

RESULTS

Navigation together with heat-based operant conditioning allows flies to learn the location of a cool spot with respect to a visual landmark. Flies optimize the time and distance required to find the cool spot over a similar number of trials as observed in assays with freely moving flies. Additionally, a fraction of flies remembers the location of the cool spot also after the conditioning heat is removed.

COMPARISON WITH EXISTING METHODS

Learning tasks have been implemented in tethered flying as well as walking flies. Mechanically translating and rotating an arena in concert with the fly's walking activity enables navigation in a three dimensional environment.

CONCLUSION

In the developed mechanical VR flies can learn to remember the location of a cool place within an otherwise hot environment with respect to a visual landmark. Implementing place learning in a tethered walking configuration is a precondition for investigating the underlying circuit dynamics using functional imaging.

High-throughput automated methods for classical and operant conditioning of Drosophila larvae

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

Excessive energy expenditure due to acute physical restraint disrupts Drosophila motivational feeding response

To study the behavior of Drosophila, it is often necessary to restrain and mount individual flies. This requires removal from food, additional handling, anesthesia, and physical restraint. We find a strong positive correlation between the length of time flies are mounted and their subsequent reflexive feeding response, where one hour of mounting is the approximate motivational equivalent to ten hours of fasting. In an attempt to explain this correlation, we rule out anesthesia side-effects, handling, additional fasting, and desiccation. We use respirometric and metabolic techniques coupled with behavioral video scoring to assess energy expenditure in mounted and free flies. We isolate a specific behavior capable of exerting large amounts of energy in mounted flies and identify it as an attempt to escape from restraint. We present a model where physical restraint leads to elevated activity and subsequent faster nutrient storage depletion among mounted flies. This ultimately further accelerates starvation and thus increases reflexive feeding response. In addition, we show that the consequences of the physical restraint profoundly alter aerobic activity, energy depletion, taste, and feeding behavior, and suggest that careful consideration is given to the time-sensitive nature of these highly significant effects when conducting behavioral, physiological or imaging experiments that require immobilization.

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.

Classification and genetic targeting of cell types in the primary taste and premotor center of the adult Drosophila brain

Neural circuits carry out complex computations that allow animals to evaluate food, select mates, move toward attractive stimuli, and move away from threats. In insects, the subesophageal zone (SEZ) is a brain region that receives gustatory, pheromonal, and mechanosensory inputs and contributes to the control of diverse behaviors, including feeding, grooming, and locomotion. Despite its importance in sensorimotor transformations, the study of SEZ circuits has been hindered by limited knowledge of the underlying diversity of SEZ neurons. Here, we generate a collection of split-GAL4 lines that provides precise genetic targeting of 138 different SEZ cell types in adult Drosophila melanogaster, comprising approximately one third of all SEZ neurons. We characterize the single-cell anatomy of these neurons and find that they cluster by morphology into six supergroups that organize the SEZ into discrete anatomical domains. We find that the majority of local SEZ interneurons are not classically polarized, suggesting rich local processing, whereas SEZ projection neurons tend to be classically polarized, conveying information to a limited number of higher brain regions. This study provides insight into the anatomical organization of the SEZ and generates resources that will facilitate further study of SEZ neurons and their contributions to sensory processing and behavior.

The Panopticon-Assessing the Effect of Starvation on Prolonged Fly Activity and Place Preference

Animal behaviours are demonstrably governed by sensory stimulation, previous experience and internal states like hunger. With increasing hunger, priorities shift towards foraging and feeding. During foraging, flies are known to employ efficient path integration strategies. However, general long-term activity patterns for both hungry and satiated flies in conditions of foraging remain to be better understood. Similarly, little is known about how permanent contact chemosensory stimulation affects locomotion. To address these questions, we have developed a novel, simplistic fly activity tracking setup—the Panopticon. Using a 3D-printed Petri dish inset, our assay allows recording of walking behaviour, of several flies in parallel, with all arena surfaces covered by a uniform substrate layer. We tested two constellations of providing food: (i) in single patches and (ii) omnipresent within the substrate layer. Fly tracking is done with FIJI, further assessment, analysis and presentation is done with a custom-built MATLAB analysis framework. We find that starvation history leads to a long-lasting reduction in locomotion, as well as a delayed place preference for food patches which seems to be not driven by immediate hunger motivation.

Expanding evolutionary neuroscience: insights from comparing variation in behavior

Neuroscientists have long studied species with convenient biological features to discover how behavior emerges from conserved molecular, neural, and circuit level processes. With the advent of new tools, from viral vectors and gene editing to automated behavioral analyses, there has been a recent wave of interest in developing new, "nontraditional" model species. Here, we advocate for a complementary approach to model species development, that is, model clade development, as a way to integrate an evolutionary comparative approach with neurobiological and behavioral experiments. Capitalizing on natural behavioral variation in and investing in experimental tools for model clades will be a valuable strategy for the next generation of neuroscience discovery.

Systems Neuroscience of Natural Behaviors in Rodents

Animals evolved in complex environments, producing a wide range of behaviors, including navigation, foraging, prey capture, and conspecific interactions, which vary over timescales ranging from milliseconds to days. Historically, these behaviors have been the focus of study for ecology and ethology, while systems neuroscience has largely focused on short timescale behaviors that can be repeated thousands of times and occur in highly artificial environments. Thanks to recent advances in machine learning, miniaturization, and computation, it is newly possible to study freely moving animals in more natural conditions while applying systems techniques: performing temporally specific perturbations, modeling behavioral strategies, and recording from large numbers of neurons while animals are freely moving. The authors of this review are a group of scientists with deep appreciation for the common aims of systems neuroscience, ecology, and ethology. We believe it is an extremely exciting time to be a neuroscientist, as we have an opportunity to grow as a field, to embrace interdisciplinary, open, collaborative research to provide new insights and allow researchers to link knowledge across disciplines, species, and scales. Here we discuss the origins of ethology, ecology, and systems neuroscience in the context of our own work and highlight how combining approaches across these fields has provided fresh insights into our research. We hope this review facilitates some of these interactions and alliances and helps us all do even better science, together.

Thermoresponsive motor behavior is mediated by ring neuron circuits in the central complex of Drosophila

Insects are ectothermal animals that are constrained in their survival and reproduction by external temperature fluctuations which require either active avoidance of or movement towards a given heat source. In Drosophila, different thermoreceptors and neurons have been identified that mediate temperature sensation to maintain the animal’s thermal preference. However, less is known how thermosensory information is integrated to gate thermoresponsive motor behavior. Here we use transsynaptic tracing together with calcium imaging, electrophysiology and thermogenetic manipulations in freely moving Drosophila exposed to elevated temperature and identify different functions of ellipsoid body ring neurons, R1-R4, in thermoresponsive motor behavior. Our results show that warming of the external surroundings elicits calcium influx specifically in R2-R4 but not in R1, which evokes threshold-dependent neural activity in the outer layer ring neurons. In contrast to R2, R3 and R4d neurons, thermogenetic inactivation of R4m and R1 neurons expressing the temperature-sensitive mutant allele of dynamin, shibire^TS, results in impaired thermoresponsive motor behavior at elevated 31 °C. trans-Tango mediated transsynaptic tracing together with physiological and behavioral analyses indicate that integrated sensory information of warming is registered by neural activity of R4m as input layer of the ellipsoid body ring neuropil and relayed on to R1 output neurons that gate an adaptive motor response. Together these findings imply that segregated activities of central complex ring neurons mediate sensory-motor transformation of external temperature changes and gate thermoresponsive motor behavior in Drosophila.

What gaze direction can tell us about cognitive processes in invertebrates

Most visually guided animals shift their gaze using body movements, eye movements, or both to gather information selectively from their environments. Psychological studies of eye movements have advanced our understanding of perceptual and cognitive processes that mediate visual attention in humans and other vertebrates. However, much less is known about how these processes operate in other organisms, particularly invertebrates. We here make the case that studies of invertebrate cognition can benefit by adding precise measures of gaze direction. To accomplish this, we briefly review the human visual attention literature and outline four research themes and several experimental paradigms that could be extended to invertebrates. We briefly review selected studies where the measurement of gaze direction in invertebrates has provided new insights, and we suggest future areas of exploration.

Using virtual worlds to understand insect navigation for bio-inspired systems

Insects perform a wide array of intricate behaviors over large spatial and temporal scales in complex natural environments. A mechanistic understanding of insect cognition has direct implications on how brains integrate multimodal information and can inspire bio-based solutions for autonomous robots. Virtual Reality (VR) offers an opportunity assess insect neuroethology while presenting complex, yet controlled, stimuli. Here, we discuss the use of insects as inspiration for artificial systems, recent advances in different VR technologies, current knowledge gaps, and the potential for application of insect VR research to bio-inspired robots. Finally, we advocate the need to diversify our model organisms, behavioral paradigms, and embrace the complexity of the natural world. This will help us to uncover the proximate and ultimate basis of brain and behavior and extract general principles for common challenging problems.

Quantifying behavior to understand the brain

Over the past years, numerous methods have emerged to automate the quantification of animal behavior at a resolution not previously imaginable. This has opened up a new field of computational ethology and will, in the near future, make it possible to quantify in near completeness what an animal is doing as it navigates its environment. The importance of improving the techniques with which we characterize behavior is reflected in the emerging recognition that understanding behavior is an essential (or even prerequisite) step to pursuing neuroscience questions. The use of these methods, however, is not limited to studying behavior in the wild or in strictly ethological settings. Modern tools for behavioral quantification can be applied to the full gamut of approaches that have historically been used to link brain to behavior, from psychophysics to cognitive tasks, augmenting those measurements with rich descriptions of how animals navigate those tasks. Here we review recent technical advances in quantifying behavior, particularly in methods for tracking animal motion and characterizing the structure of those dynamics. We discuss open challenges that remain for behavioral quantification and highlight promising future directions, with a strong emphasis on emerging approaches in deep learning, the core technology that has enabled the markedly rapid pace of progress of this field. We then discuss how quantitative descriptions of behavior can be leveraged to connect brain activity with animal movements, with the ultimate goal of resolving the relationship between neural circuits, cognitive processes and behavior.

Multi-regional circuits underlying visually guided decision-making in Drosophila

Visually guided decision-making requires integration of information from distributed brain areas, necessitating a brain-wide approach to examine its neural mechanisms. New tools in Drosophila melanogaster enable circuits spanning the brain to be charted with single cell-type resolution. Here, we highlight recent advances uncovering the computations and circuits that transform and integrate visual information across the brain to make behavioral choices. Visual information flows from the optic lobes to three primary central brain regions: a sensorimotor mapping area and two 'higher' centers for memory or spatial orientation. Rapid decision-making during predator evasion emerges from the spike timing dynamics in parallel sensorimotor cascades. Goal-directed decisions may occur through memory, navigation and valence processing in the central complex and mushroom bodies.

Experience- and Context-Dependent Modulation of the Invertebrate Compass System

How are head direction signals computed and maintained in neural circuits? In this issue of Neuron, Shiozaki et al. (2020) expand our understanding of the fly "compass" network, revealing context- and experience-dependent changes in the multiplexed encoding of head direction and steering maneuvers.

PiVR: An affordable and versatile closed-loop platform to study unrestrained sensorimotor behavior

Tools enabling closed-loop experiments are crucial to delineate causal relationships between the activity of genetically labeled neurons and specific behaviors. We developed the Raspberry Pi Virtual Reality (PiVR) system to conduct closed-loop optogenetic stimulation of neural functions in unrestrained animals. PiVR is an experimental platform that operates at high temporal resolution (70 Hz) with low latencies (<30 milliseconds), while being affordable ( Collapse

Key Words Collapse

MESH Headings

• Animals
• Behavior, Animal/physiology
• Chemotaxis
• Drosophila melanogaster/physiology
• Larva/physiology
• Light
• Locomotion
• Male
• Neurons/physiology
• Odorants
• Optogenetics
• Sensation/physiology
• Sensorimotor Cortex/physiology
• Software
• Taste/physiology
• Virtual Reality
• Zebrafish

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Grants

• R01 NS113048 NINDS NIH HHS
• R25 GM067110 NIGMS NIH HHS
• National Science Foundation
• National Institute of Health
• Gordon and Betty Moore Foundation

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Affiliation(s)

David Tadres Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

Matthieu Louis Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America

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Collaborators Collapse

Cataglyphis meets Drosophila

In Cataglyphis and Drosophila - in desert ants and fruit flies - research on visually guided behavior took different paths. While work in Cataglyphis started in the field and covered the animal's wide navigational repertoire, in Drosophila the initial focus was on a particular kind of visual control behavior scrutinized within the confines of the laboratory arena, before research concentrated on more advanced behaviors. In recent times, these multi-pronged approaches in flies and ants increasingly converge, both conceptually and methodologically, and thus lay the ground for combined neuroethological efforts. In spite of the obvious differences in the behavioral repertoire of these two groups of insects, likely commonalities in the navigational processes and underlying neuronal circuitries are increasingly coming to the fore.

Mechanisms Underlying the Neural Computation of Head Direction

Many animals use an internal sense of direction to guide their movements through the world. Neurons selective to head direction are thought to support this directional sense and have been found in a diverse range of species, from insects to primates, highlighting their evolutionary importance. Across species, most head-direction networks share four key properties: a unique representation of direction at all times, persistent activity in the absence of movement, integration of angular velocity to update the representation, and the use of directional cues to correct drift. The dynamics of theorized network structures called ring attractors elegantly account for these properties, but their relationship to brain circuits is unclear. Here, we review experiments in rodents and flies that offer insights into potential neural implementations of ring attractor networks. We suggest that a theory-guided search across model systems for biological mechanisms that enable such dynamics would uncover general principles underlying head-direction circuit function.

Multisensory control of navigation in the fruit fly

Spatial navigation is influenced by cues from nearly every sensory modality and thus provides an excellent model for understanding how different sensory streams are integrated to drive behavior. Here we review recent work on multisensory control of navigation in the model organism Drosophila melanogaster, which allows for detailed circuit dissection. We identify four modes of integration that have been described in the literature-suppression, gating, summation, and association-and describe regions of the larval and adult brain that have been implicated in sensory integration. Finally we discuss what circuit architectures might support these different forms of integration. We argue that Drosophila is an excellent model to discover these circuit and biophysical motifs.

Nutrient homeostasis - translating internal states to behavior

Behavioral neuroscience aims to describe a causal relationship between neuronal processes and behavior. Animals' ever-changing physiological needs alter their internal states. Internal states then alter neuronal processes to adapt the behavior of the animal enabling it to meet its needs. Here, we describe nutrient-specific appetites as an attractive framework to study how internal states shape complex neuronal processes and resulting behavioral outcomes. Understanding how neurons detect nutrient states and how these are integrated at the level of neuronal circuits will provide a multilevel description of the mechanisms underlying complex feeding and foraging decisions.

An arbitrary-spectrum spatial visual stimulator for vision research

Visual neuroscientists require accurate control of visual stimulation. However, few stimulator solutions simultaneously offer high spatio-temporal resolution and free control over the spectra of the light sources, because they rely on off-the-shelf technology developed for human trichromatic vision. Importantly, consumer displays fail to drive UV-shifted short wavelength-sensitive photoreceptors, which strongly contribute to visual behaviour in many animals, including mice, zebrafish and fruit flies. Moreover, many non-mammalian species feature more than three spectral photoreceptor types. Here, we present a flexible, spatial visual stimulator with up to six arbitrary spectrum chromatic channels. It combines a standard digital light processing engine with open source hard- and software that can be easily adapted to the experimentalist's needs. We demonstrate the capability of this general visual stimulator experimentally in the in vitro mouse retinal whole-mount and the in vivo zebrafish. With this work, we intend to start a community effort of sharing and developing a common stimulator design for vision research.

Random Walk Revisited: Quantification and Comparative Analysis of Drosophila Walking Trajectories

Walking trajectory is frequently measured to assess animal behavior. Air-supported spherical treadmills have been developed for real-time monitoring of animal walking trajectories. However, current systems for mice mainly employ computer mouse microcameras (chip-on-board sensors) to monitor ball motion, and these detectors exhibit technical issues with focus and rotation scale. In addition, computational methods to analyze and quantify the “random walk” of organisms are under-developed. In this work, we overcame the hurdle of frame-to-signal translation to develop a treadmill system with camera-based detection. Moreover, we generated a package of mathematical methods to quantify distinct aspects of Drosophila walking trajectories. By extracting and quantifying certain features of walking dynamics with high temporal resolution, we found that depending on their internal state, flies employ different walking strategies to approach environmental cues. This camera-based treadmill system and method package may also be applicable to monitor the walking trajectories of other diverse animal species.

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A camera-mode treadmill system was built to track Drosophila walking trajectories

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Four key features were identified to describe walking strategies

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Ball rotation is indispensable for full characterization of trajectories

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Fed and starved control flies show no obvious differences in their random walk

Learning a Spatial Task by Trial and Error in Drosophila

The ability to use memory to return to specific locations for foraging is advantageous for survival. Although recent reports have demonstrated that the fruit flies Drosophila melanogaster are capable of visual cue-driven place learning and idiothetic path integration [1-4], the depth and flexibility of Drosophila's ability to solve spatial tasks and the underlying neural substrate and genetic basis have not been extensively explored. Here, we show that Drosophila can remember a reward-baited location through reinforcement learning and do so quickly and without requiring vision. After gaining genetic access to neurons (through 0273-GAL4) with properties reminiscent of the vertebrate medial forebrain bundle (MFB) and developing a high-throughput closed-loop stimulation system, we found that both sighted and blind flies can learn-by trial and error-to repeatedly return to an unmarked location (in a rectangularly shaped arena) where a brief stimulation of the 0273-GAL4 neurons was available for each visit. We found that optogenetic stimulation of these neurons enabled learning by employing both a cholinergic pathway that promoted self-stimulation and a dopaminergic pathway that likely promoted association of relevant cues with reward. Lastly, inhibiting activities of specific neurons time-locked with stimulation of 0273-GAL4 neurons showed that mushroom bodies (MB) and central complex (CX) both play a role in promoting learning of our task. Our work uncovered new depth in flies' ability to learn a spatial task and established an assay with a level of throughput that permits a systematic genetic interrogation of flies' ability to learn spatial tasks.

Spatial Cognition: Allowing Natural Behaviours to Flourish in the Lab

Understanding the computational basis of spatial cognition requires observations of natural behaviour and the underlying neural circuits, which are difficult to do simultaneously: however, recent studies show how we might achieve this, combining rich virtual reality set-ups and the use of optogenetics in freely moving animals.

Diverse Food-Sensing Neurons Trigger Idiothetic Local Search in Drosophila

Foraging animals may benefit from remembering the location of a newly discovered food patch while continuing to explore nearby [1, 2]. For example, after encountering a drop of yeast or sugar, hungry flies often perform a local search [3, 4]. That is, rather than remaining on the food or simply walking away, flies execute a series of exploratory excursions during which they repeatedly depart and return to the resource. Fruit flies, Drosophila melanogaster, can perform this food-centered search behavior in the absence of external landmarks, instead relying on internal (idiothetic) cues [5]. This path-integration behavior may represent a deeply conserved navigational capacity in insects [6, 7], but its underlying neural basis remains unknown. Here, we used optogenetic activation to screen candidate cell classes and found that local searches can be initiated by diverse sensory neurons. Optogenetically induced searches resemble those triggered by actual food, are modulated by starvation state, and exhibit key features of path integration. Flies perform tightly centered searches around the fictive food site, even within a constrained maze, and they can return to the fictive food site after long excursions. Together, these results suggest that flies enact local searches in response to a wide variety of food-associated cues and that these sensory pathways may converge upon a common neural system for navigation. Using a virtual reality system, we demonstrate that local searches can be optogenetically induced in tethered flies walking on a spherical treadmill, laying the groundwork for future studies to image the brain during path integration. VIDEO ABSTRACT.