Controlling airborne cues to study small animal navigation

Optogenetics Neuromodulation of the Nose

Recently developed optogenetic technology, which allows high-fidelity control of neuronal activity, has been applied to investigate the neural circuits underlying sensory processing and behavior. The nasal cavity is innervated by the olfactory nerve and trigeminal nerve, which are closely related to common symptoms of rhinitis, such as impairment of smell, itching, and sneezing. The olfactory system has an amazing ability to distinguish thousands of odorant molecules at trace levels. However, there are many issues in olfactory sensing mechanisms that need to be addressed. Optogenetics offers a novel technical approach to solve this dilemma. Therefore, we review the recent advances in olfactory optogenetics to clarify the mechanisms of chemical sensing, which may help identify the mechanism of dysfunction and suggest possible treatments for impaired smell. Additionally, in rhinitis patients, alterations in the other nerve (trigeminal nerve) that innervates the nasal cavity can lead to hyperresponsiveness to various nociceptive stimuli and central sensitization, causing frequent and persistent itching and sneezing. In the last several years, the application of optogenetics in regulating nociceptive receptors, which are distributed in sensory nerve endings, and amino acid receptors, which are distributed in vital brain regions, to alleviate overreaction to nociceptive stimuli, has gained significant attention. Therefore, we focus on the progress in optogenetics and its application in neuromodulation of nociceptive stimuli and discuss the potential clinical translation for treating rhinitis in the future.

Tracking the Navigation Behavior of Drosophila Larvae in Real and Virtual Odor Gradients by Using the Raspberry Pi Virtual Reality (PiVR) System

In a closed-loop experimental paradigm, an animal experiences a modulation of its sensory input as a function of its own behavior. Tools enabling closed-loop experiments are crucial for delineating causal relationships between the activity of genetically labeled neurons and specific behavioral responses. We have recently developed an experimental platform known as "Raspberry Pi Virtual Reality" (PiVR) that is used to perform closed-loop optogenetic stimulation of neurons in unrestrained animals. PiVR is a system that operates at high temporal resolution (>30-Hz) and with low latencies. Larvae of the fruit fly Drosophila melanogaster are ideal to study the role of individual neurons in modulating behavior to aid the understanding of the neural pathways underlying various guided behaviors. Here, we introduce larval chemotaxis as an example of a navigational behavior in which an animal seeks to locate a target-in this case, the attractive source of an odor-by tracking a concentration gradient. The methodologies that we describe here combine the use of PiVR with the study of larval chemotaxis in real and virtual odor gradients, but these can also be readily adapted to other sensory modalities.

LarvaTagger: manual and automatic tagging of Drosophila larval behaviour

MOTIVATION

As more behavioural assays are carried out in large-scale experiments on Drosophila larvae, the definitions of the archetypal actions of a larva are regularly refined. In addition, video recording and tracking technologies constantly evolve. Consequently, automatic tagging tools for Drosophila larval behaviour must be retrained to learn new representations from new data. However, existing tools cannot transfer knowledge from large amounts of previously accumulated data. We introduce LarvaTagger, a piece of software that combines a pre-trained deep neural network, providing a continuous latent representation of larva actions for stereotypical behaviour identification, with a graphical user interface to manually tag the behaviour and train new automatic taggers with the updated ground truth.

RESULTS

We reproduced results from an automatic tagger with high accuracy, and we demonstrated that pre-training on large databases accelerates the training of a new tagger, achieving similar prediction accuracy using less data.

AVAILABILITY AND IMPLEMENTATION

All the code is free and open source. Docker images are also available. See gitlab.pasteur.fr/nyx/LarvaTagger.jl.

STEERING FROM THE REAR: COORDINATION OF CENTRAL PATTERN GENERATORS UNDERLYING NAVIGATION BY ASCENDING INTERNEURONS

Understanding how animals coordinate movements to achieve goals is a fundamental pursuit in neuroscience. Here we explore how neurons that reside in posterior lower-order regions of a locomotor system project to anterior higher-order regions to influence steering and navigation. We characterized the anatomy and functional role of a population of ascending interneurons in the ventral nerve cord of Drosophila larvae. Through electron microscopy reconstructions and light microscopy, we determined that the cholinergic 19f cells receive input primarily from premotor interneurons and synapse upon a diverse array of postsynaptic targets within the anterior segments including other 19f cells. Calcium imaging of 19f activity in isolated central nervous system (CNS) preparations in relation to motor neurons revealed that 19f neurons are recruited into most larval motor programmes. 19f activity lags behind motor neuron activity and as a population, the cells encode spatio-temporal patterns of locomotor activity in the larval CNS. Optogenetic manipulations of 19f cell activity in isolated CNS preparations revealed that they coordinate the activity of central pattern generators underlying exploratory headsweeps and forward locomotion in a context and location specific manner. In behaving animals, activating 19f cells suppressed exploratory headsweeps and slowed forward locomotion, while inhibition of 19f activity potentiated headsweeps, slowing forward movement. Inhibiting activity in 19f cells ultimately affected the ability of larvae to remain in the vicinity of an odor source during an olfactory navigation task. Overall, our findings provide insights into how ascending interneurons monitor motor activity and shape interactions amongst rhythm generators underlying complex navigational tasks.

Behavioral toxicological tracking analysis of Drosophila larvae exposed to polystyrene microplastics based on machine learning

Microplastics, as a pivotal concern within plastic pollution, have sparked widespread apprehension due to their ubiquitous presence. Recent research indicates that these minuscule plastic particles may exert discernible effects on the locomotor capabilities and behavior of insect larvae. This study focuses on the impact of polystyrene microplastics (PS-MPs) on the behavior of Drosophila melanogaster larvae, utilizing fruit flies as a model organism. Kinematic analysis methods were employed to assess and extrapolate the toxic effects of PS-MPs on the larvae. Drosophila larvae were exposed to varying concentrations (Control, 0.1 g/L, 1 g/L, 10 g/L, 20 g/L) of 5 μm PS-MPs during their developmental stages. The study involved calculating and evaluating parameters such as the proportion of larvae reaching the edge, distance covered, velocity, and angular velocity within a 5-min timeframe. Across different concentrations, Drosophila larvae exhibit differential degrees of impaired motor function and disrupted locomotor orientation. The proportion of larvae reaching the edge decreased, velocity significantly declined, and angular velocity exhibited a notable increase. These findings strongly suggest that when exposed to a PS-MPs environment, Drosophila larvae exhibit slower movement, increased angular rotation per unit time, leading to a reduction in the proportion of larvae reaching the edge. The altered behavior of Drosophila larvae implies potential damage of microplastics on insect larvae development and activity, consequently impacting the ecosystem and prompting heightened scrutiny regarding microplastics.

Temperature sensitivity and temperature response across development in the Drosophila larva

The surrounding thermal environment is highly important for the survival and fitness of animals, and as a result most exhibit behavioral and neural responses to temperature changes. We study signals generated by thermosensory neurons in Drosophila larvae and also the physical and sensory effects of temperature variation on locomotion and navigation. In particular we characterize how sensory neuronal and behavioral responses to temperature variation both change across the development of the larva. Looking at a wide range of non-nociceptive isotropic thermal environments, we characterize the dependence of speed, turning rate, and other behavioral components on temperature, distinguishing the physical effects of temperature from behavior changes based on sensory processing. We also characterize the strategies larvae use to modulate individual behavioral components to produce directed navigation along thermal gradients, and how these strategies change during physical development. Simulations based on modified random walks show where thermotaxis in each developmental stage fits into the larger context of possible navigation strategies. We also investigate cool sensing neurons in the larva's dorsal organ ganglion, characterizing neural response to sine-wave modulation of temperature while performing single-cell-resolution 3D imaging. We determine the sensitivity of these neurons, which produce signals in response to extremely small temperature changes. Combining thermotaxis results with neurophysiology data, we observe, across development, sensitivity to temperature change as low as a few thousandths of a °C per second, or a few hundredths of a °C in absolute temperature change.

Mechanical vibration patterns elicit behavioral transitions and habituation in crawling Drosophila larvae

How animals respond to repeatedly applied stimuli, and how animals respond to mechanical stimuli in particular, are important questions in behavioral neuroscience. We study adaptation to repeated mechanical agitation using the Drosophila larva. Vertical vibration stimuli elicit a discrete set of responses in crawling larvae: continuation, pause, turn, and reversal. Through high-throughput larva tracking, we characterize how the likelihood of each response depends on vibration intensity and on the timing of repeated vibration pulses. By examining transitions between behavioral states at the population and individual levels, we investigate how the animals habituate to the stimulus patterns. We identify time constants associated with desensitization to prolonged vibration, with re-sensitization during removal of a stimulus, and additional layers of habituation that operate in the overall response. Known memory-deficient mutants exhibit distinct behavior profiles and habituation time constants. An analogous simple electrical circuit suggests possible neural and molecular processes behind adaptive behavior.

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Specific configurations of electrical synapses filter sensory information to drive choices in behavior

Synaptic configurations in precisely wired circuits underpin how sensory information is processed by the nervous system, and the emerging animal behavior. This is best understood for chemical synapses, but far less is known about how electrical synaptic configurations modulate, in vivo and in specific neurons, sensory information processing and context-specific behaviors. We discovered that INX-1, a gap junction protein that forms electrical synapses, is required to deploy context-specific behavioral strategies during C. elegans thermotaxis behavior. INX-1 couples two bilaterally symmetric interneurons, and this configuration is required for the integration of sensory information during migration of animals across temperature gradients. In inx-1 mutants, uncoupled interneurons display increased excitability and responses to subthreshold temperature stimuli, resulting in abnormally longer run durations and context-irrelevant tracking of isotherms. Our study uncovers a conserved configuration of electrical synapses that, by increasing neuronal capacitance, enables differential processing of sensory information and the deployment of context-specific behavioral strategies.

Continuous odor profile monitoring to study olfactory navigation in small animals

Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal's sensory environment. For small model organisms like Caenorhabditis elegans and larval Drosophila melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor's adhesion, adsorption, or reemission. Here, we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.

Olfactory navigation in arthropods

Using odors to find food and mates is one of the most ancient and highly conserved behaviors. Arthropods from flies to moths to crabs use broadly similar strategies to navigate toward odor sources-such as integrating flow information with odor information, comparing odor concentration across sensors, and integrating odor information over time. Because arthropods share many homologous brain structures-antennal lobes for processing olfactory information, mechanosensors for processing flow, mushroom bodies (or hemi-ellipsoid bodies) for associative learning, and central complexes for navigation, it is likely that these closely related behaviors are mediated by conserved neural circuits. However, differences in the types of odors they seek, the physics of odor dispersal, and the physics of locomotion in water, air, and on substrates mean that these circuits must have adapted to generate a wide diversity of odor-seeking behaviors. In this review, we discuss common strategies and specializations observed in olfactory navigation behavior across arthropods, and review our current knowledge about the neural circuits subserving this behavior. We propose that a comparative study of arthropod nervous systems may provide insight into how a set of basic circuit structures has diversified to generate behavior adapted to different environments.

High-resolution analysis of individual Drosophila melanogaster larvae uncovers individual variability in locomotion and its neurogenetic modulation

Neuronally orchestrated muscular movement and locomotion are defining faculties of multicellular animals. Due to its simple brain and genetic accessibility, the larva of the fruit fly Drosophila melanogaster allows one to study these processes at tractable levels of complexity. However, although the faculty of locomotion clearly pertains to the individual, most studies of locomotion in larvae use measurements aggregated across animals, or animals tested one by one, an extravagance for larger-scale analyses. This prevents grasping the inter- and intra-individual variability in locomotion and its neurogenetic determinants. Here, we present the IMBA (individual maggot behaviour analyser) for analysing the behaviour of individual larvae within groups, reliably resolving individual identity across collisions. We use the IMBA to systematically describe the inter- and intra-individual variability in locomotion of wild-type animals, and how the variability is reduced by associative learning. We then report a novel locomotion phenotype of an adhesion GPCR mutant. We further investigated the modulation of locomotion across repeated activations of dopamine neurons in individual animals, and the transient backward locomotion induced by brief optogenetic activation of the brain-descending 'mooncrawler' neurons. In summary, the IMBA is an easy-to-use toolbox allowing an unprecedentedly rich view of the behaviour and its variability of individual larvae, with utility in multiple biomedical research contexts.

Nociception in fruit fly larvae

Nociception, the process of encoding and processing noxious or painful stimuli, allows animals to detect and avoid or escape from potentially life-threatening stimuli. Here, we provide a brief overview of recent technical developments and studies that have advanced our understanding of the Drosophila larval nociceptive circuit and demonstrated its potential as a model system to elucidate the mechanistic basis of nociception. The nervous system of a Drosophila larva contains roughly 15,000 neurons, which allows for reconstructing the connectivity among them directly by transmission electron microscopy. In addition, the availability of genetic tools for manipulating the activity of individual neurons and recent advances in computational and high-throughput behavior analysis methods have facilitated the identification of a neural circuit underlying a characteristic nocifensive behavior. We also discuss how neuromodulators may play a key role in modulating the nociceptive circuit and behavioral output. A detailed understanding of the structure and function of Drosophila larval nociceptive neural circuit could provide insights into the organization and operation of pain circuits in mammals and generate new knowledge to advance the development of treatment options for pain in humans.

Stability of olfactory behavior syndromes in the Drosophila larva

Individuals of many animal populations exhibit idiosyncratic behaviors. One measure of idiosyncratic behavior is a behavior syndrome, defined as the stability of one or more behavior traits in an individual across different situations. While behavior syndromes have been described in various animal systems, their properties and the circuit mechanisms that generate them are poorly understood. We thus have an incomplete understanding of how circuit properties influence animal behavior. Here, we characterize olfactory behavior syndromes in the Drosophila larva. We show that larvae exhibit idiosyncrasies in their olfactory behavior over short time scales. They are influenced by the larva's satiety state and odor environment. Additionally, we identified a group of antennal lobe local neurons that influence the larva's idiosyncratic behavior. These findings reveal previously unsuspected influences on idiosyncratic behavior. They further affirm the idea that idiosyncrasies are not simply statistical phenomena but manifestations of neural mechanisms. In light of these findings, we discuss more broadly the importance of idiosyncrasies to animal survival and how they might be studied.

Molecular encoding of stimulus features in a single sensory neuron type enables neuronal and behavioral plasticity

Neurons modify their transcriptomes in response to an animal’s experience. How specific experiences are transduced to modulate gene expression and precisely tune neuronal functions are not fully defined. Here, we describe the molecular profile of a thermosensory neuron pair in C. elegans experiencing different temperature stimuli. We find that distinct salient features of the temperature stimulus including its duration, magnitude of change, and absolute value are encoded in the gene expression program in this single neuron, and identify a novel transmembrane protein and a transcription factor whose specific transcriptional dynamics are essential to drive neuronal, behavioral, and developmental plasticity. Expression changes are driven by broadly expressed activity-dependent transcription factors and corresponding cis -regulatory elements that nevertheless direct neuron- and stimulus-specific gene expression programs. Our results indicate that coupling of defined stimulus characteristics to the gene regulatory logic in individual specialized neuron types can customize neuronal properties to drive precise behavioral adaptation.

Dscam1 overexpression impairs the function of the gut nervous system in Drosophila

BACKGROUND

Down syndrome (DS) patients have a 100-fold increase in the risk of Hirschsprung syndrome of the colon and rectum (HSCR), a lack of enteric neurons in the colon. The leading DS candidate gene is trisomy of the Down syndrome cell adhesion molecule (DSCAM).

RESULTS

We find that Dscam1 protein is expressed in the Drosophila enteric/stomatogastric nervous system (SNS). Axonal Dscam1 phenotypes can be rescued equally by diverse isoforms. Overexpression of Dscam1 resulted in frontal and hindgut nerve overgrowth. Expression of dominant negative Dscam1-ΔC led to a truncated frontal nerve and increased branching of the hindgut nerve. Larval locomotion is influenced by feeding state, and we found that the average speed of larvae with Dscam1 SNS expression was reduced, whereas overexpression of Dscam1-ΔC significantly increased the speed. Dscam1 overexpression reduced the efficiency of food clearance from the larval gut.

CONCLUSION

Our work demonstrates that overexpression of Dscam1 can perturb gut function in a model system.

Internal state affects local neuron function in an early sensory processing center to shape olfactory behavior in Drosophila larvae

Crawling insects, when starved, tend to have fewer head wavings and travel in straighter tracks in search of food. We used the Drosophila melanogaster larva to investigate whether this flexibility in the insect's navigation strategy arises during early olfactory processing and, if so, how. We demonstrate a critical role for Keystone-LN, an inhibitory local neuron in the antennal lobe, in implementing head-sweep behavior. Keystone-LN responds to odor stimuli, and its inhibitory output is required for a larva to successfully navigate attractive and aversive odor gradients. We show that insulin signaling in Keystone-LN likely mediates the starvation-dependent changes in head-sweep magnitude, shaping the larva's odor-guided movement. Our findings demonstrate how flexibility in an insect's navigation strategy can arise from context-dependent modulation of inhibitory neurons in an early sensory processing center. They raise new questions about modulating a circuit's inhibitory output to implement changes in a goal-directed movement.

Long-Term Observation of Locomotion of Drosophila Larvae Facilitates Feasibility of Food-Choice Assays

Animal behavior is reflected by locomotor patterns. To decipher the underlying neural circuitry locomotion has to be monitored over often longer time periods. Here a simple adaptation is described to constrain movement of third instar Drosophila larvae to a defined area and use Frustrated total internal reflection based imaging method (FIM) imaging to monitor larval movements up to 1 h. It is demonstrated that the combination of FIM imaging and long analysis periods facilitates the conduction of food choice assays and provides the means to easily quantify food preferences.

Multimodal Information Processing and Associative Learning in the Insect Brain

Simple Summary

Insect behaviors are a great indicator of evolution and provide useful information about the complexity of organisms. The realistic sensory scene of an environment is complex and replete with multisensory inputs, making the study of sensory integration that leads to behavior highly relevant. We summarize the recent findings on multimodal sensory integration and the behaviors that originate from them in our review.

Abstract

The study of sensory systems in insects has a long-spanning history of almost an entire century. Olfaction, vision, and gustation are thoroughly researched in several robust insect models and new discoveries are made every day on the more elusive thermo- and mechano-sensory systems. Few specialized senses such as hygro- and magneto-reception are also identified in some insects. In light of recent advancements in the scientific investigation of insect behavior, it is not only important to study sensory modalities individually, but also as a combination of multimodal inputs. This is of particular significance, as a combinatorial approach to study sensory behaviors mimics the real-time environment of an insect with a wide spectrum of information available to it. As a fascinating field that is recently gaining new insight, multimodal integration in insects serves as a fundamental basis to understand complex insect behaviors including, but not limited to navigation, foraging, learning, and memory. In this review, we have summarized various studies that investigated sensory integration across modalities, with emphasis on three insect models (honeybees, ants and flies), their behaviors, and the corresponding neuronal underpinnings.

The role of food odor in invertebrate foraging

Foraging for food is an integral part of animal survival. In small insects and invertebrates, multisensory information and optimized locomotion strategies are used to effectively forage in patchy and complex environments. Here, the importance of olfactory cues for effective invertebrate foraging is discussed in detail. We review how odors are used by foragers to move toward a likely food source and the recent models that describe this sensory-driven behavior. We argue that smell serves a second function by priming an organism for the efficient exploitation of food. By appraising food odors, invertebrates can establish preferences and better adapt to their ecological niches, thereby promoting survival. The smell of food pre-prepares the gastrointestinal system and primes feeding motor programs for more effective ingestion as well. Optimizing resource utilization affects longevity and reproduction as a result, leading to drastic changes in survival. We propose that models of foraging behavior should include odor priming, and illustrate this with a simple toy model based on the marginal value theorem. Lastly, we discuss the novel techniques and assays in invertebrate research that could investigate the interactions between odor sensing and food intake. Overall, the sense of smell is indispensable for efficient foraging and influences not only locomotion, but also organismal physiology, which should be reflected in behavioral modeling.

A high-throughput method to deliver targeted optogenetic stimulation to moving C. elegans populations

We present a high-throughput optogenetic illumination system capable of simultaneous closed-loop light delivery to specified targets in populations of moving Caenorhabditis elegans. The instrument addresses three technical challenges: It delivers targeted illumination to specified regions of the animal's body such as its head or tail; it automatically delivers stimuli triggered upon the animal's behavior; and it achieves high throughput by targeting many animals simultaneously. The instrument was used to optogenetically probe the animal's behavioral response to competing mechanosensory stimuli in the the anterior and posterior gentle touch receptor neurons. Responses to more than 43,418 stimulus events from a range of anterior-posterior intensity combinations were measured. The animal's probability of sprinting forward in response to a mechanosensory stimulus depended on both the anterior and posterior stimulation intensity, while the probability of reversing depended primarily on the anterior stimulation intensity. We also probed the animal's response to mechanosensory stimulation during the onset of turning, a relatively rare behavioral event, by delivering stimuli automatically when the animal began to turn. Using this closed-loop approach, over 9,700 stimulus events were delivered during turning onset at a rate of 9.2 events per worm hour, a greater than 25-fold increase in throughput compared to previous investigations. These measurements validate with greater statistical power previous findings that turning acts to gate mechanosensory evoked reversals. Compared to previous approaches, the current system offers targeted optogenetic stimulation to specific body regions or behaviors with many fold increases in throughput to better constrain quantitative models of sensorimotor processing.

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.

Circuits for integrating learned and innate valences in the insect brain

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all mushroom body (MB) output neurons (encoding learned valences) and characterized their patterns of interaction with lateral horn (LH) neurons (encoding innate valences) in Drosophila larva. The connectome revealed multiple convergence neuron types that receive convergent MB and LH inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this, we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

Switch-like and persistent memory formation in individual Drosophila larvae

Associative learning allows animals to use past experience to predict future events. The circuits underlying memory formation support immediate and sustained changes in function, often in response to a single example. Larval Drosophila is a genetic model for memory formation that can be accessed at molecular, synaptic, cellular, and circuit levels, often simultaneously, but existing behavioral assays for larval learning and memory do not address individual animals, and it has been difficult to form long-lasting memories, especially those requiring synaptic reorganization. We demonstrate a new assay for learning and memory capable of tracking the changing preferences of individual larvae. We use this assay to explore how activation of a pair of reward neurons changes the response to the innately aversive gas carbon dioxide (CO2). We confirm that when coupled to CO2 presentation in appropriate temporal sequence, optogenetic reward reduces avoidance of CO2. We find that learning is switch-like: all-or-none and quantized in two states. Memories can be extinguished by repeated unrewarded exposure to CO2 but are stabilized against extinction by repeated training or overnight consolidation. Finally, we demonstrate long-lasting protein synthesis dependent and independent memory formation.

Interspecies variation of larval locomotion kinematics in the genus Drosophila and its relation to habitat temperature

BACKGROUND

Speed and trajectory of locomotion are the characteristic traits of individual species. Locomotion kinematics may have been shaped during evolution towards increased survival in the habitats of each species. Although kinematics of locomotion is thought to be influenced by habitats, the quantitative relation between the kinematics and environmental factors has not been fully revealed. Here, we performed comparative analyses of larval locomotion in 11 Drosophila species.

RESULTS

We found that larval locomotion kinematics are divergent among the species. The diversity is not correlated to the body length but is correlated instead to the habitat temperature of the species. Phylogenetic analyses using Bayesian inference suggest that the evolutionary rate of the kinematics is diverse among phylogenetic tree branches.

CONCLUSIONS

The results of this study imply that the kinematics of larval locomotion has diverged in the evolutionary history of the genus Drosophila and evolved under the effects of the ambient temperature of habitats.

Using your nose to find your way: Ethological comparisons between human and non-human species

Olfaction is arguably the least valued among our sensory systems, and its significance for human behavior is often neglected. Spatial navigation represents no exception to the rule: humans are often characterized as purely visual navigators, a view that undermines the contribution of olfactory cues. Accordingly, research investigating whether and how humans use olfaction to navigate space is rare. In comparison, research on olfactory navigation in non-human species is abundant, and identifies behavioral strategies along with neural mechanisms characterizing the use of olfactory cues during spatial tasks. Using an ethological approach, our review draws from studies on olfactory navigation across species to describe the adaptation of strategies under the influence of selective pressure. Mammals interact with spatial environments by abstracting multisensory information into cognitive maps. We thus argue that olfactory cues, alongside inputs from other sensory modalities, play a crucial role in spatial navigation for mammalian species, including humans; that is, odors constitute one of the many building blocks in the formation of cognitive maps.

A genetically encoded tool for reconstituting synthetic modulatory neurotransmission and reconnect neural circuits in vivo

Chemogenetic and optogenetic tools have transformed the field of neuroscience by facilitating the examination and manipulation of existing circuits. Yet, the field lacks tools that enable rational rewiring of circuits via the creation or modification of synaptic relationships. Here we report the development of HySyn, a system designed to reconnect neural circuits in vivo by reconstituting synthetic modulatory neurotransmission. We demonstrate that genetically targeted expression of the two HySyn components, a Hydra-derived neuropeptide and its receptor, creates de novo neuromodulatory transmission in a mammalian neuronal tissue culture model and functionally rewires a behavioral circuit in vivo in the nematode Caenorhabditis elegans. HySyn can interface with existing optogenetic, chemogenetic and pharmacological approaches to functionally probe synaptic transmission, dissect neuropeptide signaling, or achieve targeted modulation of specific neural circuits and behaviors.

Engineering de novo synapse-like connections between neurons could enhance our understanding of neuronal circuits and how they generate behaviour. The authors present a two-component system that creates synthetic neuromodulatory connections to manipulate intracellular Ca2+ levels in in vivo neural circuits.

Synchronous and opponent thermosensors use flexible cross-inhibition to orchestrate thermal homeostasis

Body temperature homeostasis is essential and reliant upon the integration of outputs from multiple classes of cooling- and warming-responsive cells. The computations that integrate these outputs are not understood. Here, we discover a set of warming cells (WCs) and show that the outputs of these WCs combine with previously described cooling cells (CCs) in a cross-inhibition computation to drive thermal homeostasis in larval Drosophila WCs and CCs detect temperature changes using overlapping combinations of ionotropic receptors: Ir68a, Ir93a, and Ir25a for WCs and Ir21a, Ir93a, and Ir25a for CCs. WCs mediate avoidance to warming while cross-inhibiting avoidance to cooling, and CCs mediate avoidance to cooling while cross-inhibiting avoidance to warming. Ambient temperature-dependent regulation of the strength of WC- and CC-mediated cross-inhibition keeps larvae near their homeostatic set point. Using neurophysiology, quantitative behavioral analysis, and connectomics, we demonstrate how flexible integration between warming and cooling pathways can orchestrate homeostatic thermoregulation.

Associative learning in larval and adult Drosophila is impaired by the dopamine-synthesis inhibitor 3-Iodo-L-tyrosine

Across the animal kingdom, dopamine plays a crucial role in conferring reinforcement signals that teach animals about the causal structure of the world. In the fruit fly Drosophila melanogaster, dopaminergic reinforcement has largely been studied using genetics, whereas pharmacological approaches have received less attention. Here, we apply the dopamine-synthesis inhibitor 3-Iodo-L-tyrosine (3IY), which causes acute systemic inhibition of dopamine signaling, and investigate its effects on Pavlovian conditioning. We find that 3IY feeding impairs sugar-reward learning in larvae while leaving task-relevant behavioral faculties intact, and that additional feeding of a precursor of dopamine (L-3,4-dihydroxyphenylalanine, L-DOPA), rescues this impairment. Concerning a different developmental stage and for the aversive valence domain. Moreover, we demonstrate that punishment learning by activating the dopaminergic neuron PPL1-γ1pedc in adult flies is also impaired by 3IY feeding, and can likewise be rescued by L-DOPA. Our findings exemplify the advantages of using a pharmacological approach in combination with the genetic techniques available in D. melanogaster to manipulate neuronal and behavioral function.

Summary: We surveyed the effects of a dopamine-synthesis inhibitor on associative learning in larval and adult Drosophila. This approach can supplement genetic tools in investigating the conserved reinforcing function of dopamine.

Resolving Colliding Larvae by Fitting ASM to Random Walker-Based Pre-Segmentations

Drosophila melanogaster is an important model organism for research in neuro- and behavioral biology. Automated studies of their locomotion are crucial to link sensory input and neural processing to motor output which has led to numerous vision-based tracking systems. However, most of these approaches share the inability to segment the contours of colliding animals causing identity losses, appearing and disappearing animals, and the absence of posture and motion related measurements during the time of the collision. We present a novel collision resolution algorithm enabling an accurate contour segmentation of multiple touching Drosophila larvae. Our algorithm utilizes an adapted active shape model (ASM) to learn a low dimensional posture space which is fitted to random-walker generated pre-segmentations. We evaluate our collision resolution algorithm using three publicly available datasets and compare it with the current state-of-the-art methods. In addition, we introduce a refined dataset enabling a segmentation evaluation on the level of pixel accuracy. The results demonstrate that our approach outperforms the state-of-the-art approaches in both accuracy and computational time. We will incorporate this algorithm into our widely used tracking program to improve the statistical strength of the behavioral quantification and allow marker-free studies of interacting Drosophila larvae.

Aversive teaching signals from individual dopamine neurons in larval Drosophila show qualitative differences in their temporal "fingerprint"

Dopamine serves many functions, and dopamine neurons are correspondingly diverse. We use a combination of optogenetics, behavioral experiments, and high-resolution video-tracking to probe for the functional capacities of two single, identified dopamine neurons in larval Drosophila. The DAN-f1 and the DAN-d1 neuron were recently found to carry aversive teaching signals during Pavlovian olfactory learning. We enquire into a fundamental feature of these teaching signals, namely their temporal "fingerprint". That is, receiving punishment feels bad, whereas being relieved from it feels good, and animals and humans alike learn with opposite valence about the occurrence and the termination of punishment (the same principle applies in the appetitive domain, with opposite sign). We find that DAN-f1 but not DAN-d1 can mediate such timing-dependent valence reversal: presenting an odor before DAN-f1 activation leads to learned avoidance of the odor (punishment memory), whereas presenting the odor upon termination of DAN-f1 activation leads to learned approach (relief memory). In contrast, DAN-d1 confers punishment memory only. These effects are further characterized in terms of the impact of the duration of optogenetic activation, the temporal stability of the memories thus established, and the specific microbehavioral patterns of locomotion through which they are expressed. Together with recent findings in the appetitive domain and from adult Drosophila, our results suggest that heterogeneity in the temporal fingerprint of teaching signals might be a more general principle of reinforcement processing through dopamine neurons.

Volatile Organic Compound Chamber: A Novel Technology for Microbiological Volatile Interaction Assays

The interest in the study of microbiological interactions mediated by volatile organic compounds (VOCs) has steadily increased in the last few years. Nevertheless, most assays still rely on the use of non-specific materials. We present a new tool, the volatile organic compound chamber (VOC chamber), specifically designed to perform these experiments. The novel devices were tested using four Trichoderma strains against Fusarium oxysporum and Rhizoctonia solani. We demonstrate that VOC chambers provide higher sensitivity and selectivity between treatments and higher homogeneity of results than the traditional method. VOC chambers are also able to test both vented and non-vented conditions. We prove that ventilation plays a very important role regarding volatile interactions, up to the point that some growth-inhibitory effects observed in closed environments switch to promoting ones when tested in vented conditions. This promoting activity seems to be related to the accumulation of squalene by T. harzianum. The VOC chambers proved to be an easy, homogeneous, flexible, and repeatable method, able to better select microorganisms with high biocontrol activity and to guide the future identification of new bioactive VOCs and their role in microbial interactions.

Anatomy and Neural Pathways Modulating Distinct Locomotor Behaviors in Drosophila Larva

The control of movements is a fundamental feature shared by all animals. At the most basic level, simple movements are generated by coordinated neural activity and muscle contraction patterns that are controlled by the central nervous system. How behavioral responses to various sensory inputs are processed and integrated by the downstream neural network to produce flexible and adaptive behaviors remains an intense area of investigation in many laboratories. Due to recent advances in experimental techniques, many fundamental neural pathways underlying animal movements have now been elucidated. For example, while the role of motor neurons in locomotion has been studied in great detail, the roles of interneurons in animal movements in both basic and noxious environments have only recently been realized. However, the genetic and transmitter identities of many of these interneurons remains unclear. In this review, we provide an overview of the underlying circuitry and neural pathways required by Drosophila larvae to produce successful movements. By improving our understanding of locomotor circuitry in model systems such as Drosophila, we will have a better understanding of how neural circuits in organisms with different bodies and brains lead to distinct locomotion types at the organism level. The understanding of genetic and physiological components of these movements types also provides directions to understand movements in higher organisms.

Internal state configures olfactory behavior and early sensory processing in Drosophila larvae

Animals exhibit different behavioral responses to the same sensory cue depending on their internal state at a given moment. How and where in the brain are sensory inputs combined with state information to select an appropriate behavior? Here, we investigate how food deprivation affects olfactory behavior in Drosophila larvae. We find that certain odors repel well-fed animals but attract food-deprived animals and that feeding state flexibly alters neural processing in the first olfactory center, the antennal lobe. Hunger differentially modulates two output pathways required for opposing behavioral responses. Upon food deprivation, attraction-mediating uniglomerular projection neurons show elevated odor-evoked activity, whereas an aversion-mediating multiglomerular projection neuron receives odor-evoked inhibition. The switch between these two pathways is regulated by the lone serotonergic neuron in the antennal lobe, CSD. Our findings demonstrate how flexible behaviors can arise from state-dependent circuit dynamics in an early sensory processing center.

Useful road maps: studying Drosophila larva's central nervous system with the help of connectomics

The larva of Drosophila melanogaster is emerging as a powerful model system for comprehensive brain-wide understanding of the circuit implementation of neural computations. With an unprecedented amount of tools in hand, including synaptic-resolution connectomics, whole-brain imaging, and genetic tools for selective targeting of single neuron types, it is possible to dissect which circuits and computations are at work behind behaviors that have an interesting level of complexity. Here we present some of the recent advances regarding multisensory integration, learning, and action selection in Drosophila larva.

Feeding state functionally reconfigures a sensory circuit to drive thermosensory behavioral plasticity

Internal state alters sensory behaviors to optimize survival strategies. The neuronal mechanisms underlying hunger-dependent behavioral plasticity are not fully characterized. Here we show that feeding state alters C. elegans thermotaxis behavior by engaging a modulatory circuit whose activity gates the output of the core thermotaxis network. Feeding state does not alter the activity of the core thermotaxis circuit comprised of AFD thermosensory and AIY interneurons. Instead, prolonged food deprivation potentiates temperature responses in the AWC sensory neurons, which inhibit the postsynaptic AIA interneurons to override and disrupt AFD-driven thermotaxis behavior. Acute inhibition and activation of AWC and AIA, respectively, restores negative thermotaxis in starved animals. We find that state-dependent modulation of AWC-AIA temperature responses requires INS-1 insulin-like peptide signaling from the gut and DAF-16/FOXO function in AWC. Our results describe a mechanism by which functional reconfiguration of a sensory network via gut-brain signaling drives state-dependent behavioral flexibility.

Mini-brain computations converting dynamic olfactory inputs into orientation behavior

The neural logic underlying the conversion of non-stationary (dynamic) olfactory inputs into odor-search behaviors has been difficult to crack due to the distributed nature of the olfactory code - food odors typically co-activate multiple olfactory sensory neurons. In the Drosophila larva, the activity of a single olfactory sensory neuron is sufficient to direct accurate reorientation maneuvers in odor gradients (chemotaxis). In this reduced sensory system, a descending pathway essential for larval chemotaxis has been delineated from the peripheral olfactory system down to the premotor system. Here, I review how anatomical and functional inspections of this pathway have advanced our understanding of the neural mechanisms that convert behaviorally relevant sensory signals into orientation responses.

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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Mechanism underlying starvation-dependent modulation of olfactory behavior in Drosophila larva

Starvation enhances olfactory sensitivity that encourage animals to search for food. The molecular mechanisms that enable sensory neurons to remain flexible and adapt to a particular internal state remain poorly understood. Here, we study the roles of GABA and insulin signaling in starvation-dependent modulation of olfactory sensory neuron (OSN) function in the Drosophila larva. We show that GABAB-receptor and insulin-receptor play important roles during OSN modulation. Using an OSN-specific gene expression analysis, we explore downstream targets of insulin signaling in OSNs. Our results suggest that insulin and GABA signaling pathways interact within OSNs and modulate OSN function by impacting olfactory information processing. We further show that manipulating these signaling pathways specifically in the OSNs impact larval feeding behavior and its body weight. These results challenge the prevailing model of OSN modulation and highlight opportunities to better understand OSN modulation mechanisms and their relationship to animal physiology.

Circadian and Genetic Modulation of Visually-Guided Navigation in Drosophila Larvae

Organisms possess an endogenous molecular clock which enables them to adapt to environmental rhythms and to synchronize their metabolism and behavior accordingly. Circadian rhythms govern daily oscillations in numerous physiological processes, and the underlying molecular components have been extensively described from fruit flies to mammals. Drosophila larvae have relatively simple nervous system compared to their adult counterparts, yet they both share a homologous molecular clock with mammals, governed by interlocking transcriptional feedback loops with highly conserved constituents. Larvae exhibit a robust light avoidance behavior, presumably enabling them to avoid predators and desiccation, and DNA-damage by exposure to ultraviolet light, hence are crucial for survival. Circadian rhythm has been shown to alter light-dark preference, however it remains unclear how distinct behavioral strategies are modulated by circadian time. To address this question, we investigate the larval visual navigation at different time-points of the day employing a computer-based tracking system, which allows detailed evaluation of distinct navigation strategies. Our results show that due to circadian modulation specific to light information processing, larvae avoid light most efficiently at dawn, and a functioning clock mechanism at both molecular and neuro-signaling level is necessary to conduct this modulation.

Studying neural circuits of decision-making in Drosophila larva

To study neural circuits underlying decisions, the model organism used for that purpose has to be simple enough to be able to dissect the circuitry neuron by neuron across the nervous system and in the same time complex enough to be able to perform different types of decisions. Here, I lay out the case: (1) that Drosophila larva is an advantageous model system that balances well these two requirements and (2) the insights gained from this model, assuming that circuit principles may be shared across species, can be used to advance our knowledge of neural circuit implementation of decision-making in general, including in more complex brains.

MicroRNAs Regulate Multiple Aspects of Locomotor Behavior in Drosophila

Locomotion is an ancient and fundamental output of the nervous system required for animals to perform many other complex behaviors. Although the formation of motor circuits is known to be under developmental control of transcriptional mechanisms that define the fates and connectivity of the many neurons, glia and muscle constituents of these circuits, relatively little is known about the role of post-transcriptional regulation of locomotor behavior. MicroRNAs have emerged as a potentially rich source of modulators for neural development and function. In order to define the microRNAs required for normal locomotion in Drosophila melanogaster, we utilized a set of transgenic Gal4-dependent competitive inhibitors (microRNA sponges, or miR-SPs) to functionally assess ca. 140 high-confidence Drosophila microRNAs using automated quantitative movement tracking systems followed by multiparametric analysis. Using ubiquitous expression of miR-SP constructs, we identified a large number of microRNAs that modulate aspects of normal baseline adult locomotion. Addition of temperature-dependent Gal80 to identify microRNAs that act during adulthood revealed that the majority of these microRNAs play developmental roles. Comparison of ubiquitous and neural-specific miR-SP expression suggests that most of these microRNAs function within the nervous system. Parallel analyses of spontaneous locomotion in adults and in larvae also reveal that very few of the microRNAs required in the adult overlap with those that control the behavior of larval motor circuits. These screens suggest that a rich regulatory landscape underlies the formation and function of motor circuits and that many of these mechanisms are stage and/or parameter-specific.

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.

Controlling and measuring dynamic odorant stimuli in the laboratory

Animals experience complex odorant stimuli that vary widely in composition, intensity and temporal properties. However, stimuli used to study olfaction in the laboratory are much simpler. This mismatch arises from the challenges in measuring and controlling them precisely and accurately. Even simple pulses can have diverse kinetics that depend on their molecular identity. Here, we introduce a model that describes how stimulus kinetics depend on the molecular identity of the odorant and the geometry of the delivery system. We describe methods to deliver dynamic odorant stimuli of several types, including broadly distributed stimuli that reproduce some of the statistics of naturalistic plumes, in a reproducible and precise manner. Finally, we introduce a method to calibrate a photo-ionization detector to any odorant it can detect, using no additional components. Our approaches are affordable and flexible and can be used to advance our understanding of how olfactory neurons encode real-world odor signals.

Modulations of microbehaviour by associative memory strength in Drosophila larvae

Finding food is a vital skill and a constant task for any animal, and associative learning of food-predicting cues gives an advantage in this daily struggle. The strength of the associations between cues and food depends on a number of parameters, such as the salience of the cue, the strength of the food reward and the number of joint cue-food experiences. We investigate what impact the strength of an associative odour-sugar memory has on the microbehaviour of Drosophila melanogaster larvae. We find that larvae form stronger memories with increasing concentrations of sugar or odour, and that these stronger memories manifest themselves in stronger modulations of two aspects of larval microbehaviour, the rate and the direction of lateral reorientation manoeuvres (so-called head casts). These two modulations of larval behaviour are found to be correlated to each other in every experiment performed, which is in line with a model that assumes that both modulations are controlled by a common motor output. Given that the Drosophila larva is a genetically tractable model organism that is well suited to the study of simple circuits at the single-cell level, these analyses can guide future research into the neuronal circuits underlying the translation of associative memories of different strength into behaviour, and may help to understand how these processes are organised in more complex systems.

Computational Neuroethology: A Call to Action

The brain is worthy of study because it is in charge of behavior. A flurry of recent technical advances in measuring and quantifying naturalistic behaviors provide an important opportunity for advancing brain science. However, the problem of understanding unrestrained behavior in the context of neural recordings and manipulations remains unsolved, and developing approaches to addressing this challenge is critical. Here we discuss considerations in computational neuroethology-the science of quantifying naturalistic behaviors for understanding the brain-and propose strategies to evaluate progress. We point to open questions that require resolution and call upon the broader systems neuroscience community to further develop and leverage measures of naturalistic, unrestrained behavior, which will enable us to more effectively probe the richness and complexity of the brain.

Muscarinic acetylcholine receptor signaling generates OFF selectivity in a simple visual circuit

ON and OFF selectivity in visual processing is encoded by parallel pathways that respond to either light increments or decrements. Despite lacking the anatomical features to support split channels, Drosophila larvae effectively perform visually-guided behaviors. To understand principles guiding visual computation in this simple circuit, we focus on investigating the physiological properties and behavioral relevance of larval visual interneurons. We find that the ON vs. OFF discrimination in the larval visual circuit emerges through light-elicited cholinergic signaling that depolarizes a cholinergic interneuron (cha-lOLP) and hyperpolarizes a glutamatergic interneuron (glu-lOLP). Genetic studies further indicate that muscarinic acetylcholine receptor (mAchR)/Gαo signaling produces the sign-inversion required for OFF detection in glu-lOLP, the disruption of which strongly impacts both physiological responses of downstream projection neurons and dark-induced pausing behavior. Together, our studies identify the molecular and circuit mechanisms underlying ON vs. OFF discrimination in the Drosophila larval visual system.

Drosophila larvae are able to perform visually-guided behaviours yet the molecular and circuit mechanisms for discriminating changes in light intensity are not known. Here, the authors report that ON versus OFF discrimination results from opposing cholinergic and glutamatergic mechanisms.

Modelling the mechanics of exploration in larval Drosophila

The Drosophila larva executes a stereotypical exploratory routine that appears to consist of stochastic alternation between straight peristaltic crawling and reorientation events through lateral bending. We present a model of larval mechanics for axial and transverse motion over a planar substrate, and use it to develop a simple, reflexive neuromuscular model from physical principles. The mechanical model represents the midline of the larva as a set of point masses which interact with each other via damped translational and torsional springs, and with the environment via sliding friction forces. The neuromuscular model consists of: 1. segmentally localised reflexes that amplify axial compression in order to counteract frictive energy losses, and 2. long-range mutual inhibition between reflexes in distant segments, enabling overall motion of the model larva relative to its substrate. In the absence of damping and driving, the mechanical model produces axial travelling waves, lateral oscillations, and unpredictable, chaotic deformations. The neuromuscular model counteracts friction to recover these motion patterns, giving rise to forward and backward peristalsis in addition to turning. Our model produces spontaneous exploration, even though the nervous system has no intrinsic pattern generating or decision making ability, and neither senses nor drives bending motions. Ultimately, our model suggests a novel view of larval exploration as a deterministic superdiffusion process which is mechanistically grounded in the chaotic mechanics of the body. We discuss how this may provide new interpretations for existing observations at the level of tissue-scale activity patterns and neural circuitry, and provide some experimental predictions that would test the extent to which the mechanisms we present translate to the real larva.

We investigate the relationship between brain, body and environment in the exploratory behaviour of fruitfly larva. A larva crawls forward by propagating a wave of compression through its segmented body, and changes its crawling direction by bending to one side or the other. We show first that a purely mechanical model of the larva’s body can produce travelling compression waves, sideways bending, and unpredictable, chaotic motions. For this body to locomote through its environment, it is necessary to add a neuromuscular system to counteract the loss of energy due to friction, and to limit the simultaneous compression of segments. These simple additions allow our model larva to generate life-like forward and backward crawling as well as spontaneous turns, which occur without any direct sensing or control of reorientation. The unpredictability inherent in the larva’s physics causes the model to explore its environment, despite the lack of any neural mechanism for rhythm generation or for deciding when to switch from crawling to turning. Our model thus demonstrates how understanding body mechanics can generate and simplify neurobiological hypotheses as to how behaviour arises.

A Neuromechanical Model of Larval Chemotaxis

Larval Drosophila move up attractive chemical gradients, and down aversive ones. Although their movement is often characterized as a series of runs and directed turns, it can also be modeled as a continuous modulation of turning extent by the detected change in stimulus intensity as the animal moves through the gradient. We show that a neuromechanical model of peristaltic crawling and spontaneous bending in the larva can be adapted to produce taxis behavior by the simple addition of a local segmental reflex to modulate transverse viscosity (or "bendiness") proportionally to the intensity change detected in the head. Altering the gain produces weaker or stronger, negative or positive taxis, with behavioral statistics that qualitatively match the larva.

High-throughput mechanotransduction in Drosophila embryos with mesofluidics

Developing embryos create complexity by expressing genes to coordinate movement which generates mechanical force. An emerging theory is that mechanical force can also serve as an input signal to regulate developmental gene expression. Experimental methods to apply mechanical stimulation to whole embryos have been limited, mainly to aspiration, indentation, or moving a coverslip; these approaches stimulate only a few embryos at a time and require manual alignment. A powerful approach for automation is microfluidic devices, which can precisely manipulate hundreds of samples. However, using microfluidics to apply mechanical stimulation has been limited to small cellular systems, with fewer applications for larger scale whole embryos. We developed a mesofluidic device that applies the precision and automation of microfluidics to the Drosophila embryo: high-throughput automatic alignment, immobilization, compression, real-time imaging, and recovery of hundreds of live embryos. We then use twist:eGFP embryos to show that the mechanical induction of twist depends on the dose and duration of compression. This device allows us to quantify responses to compression, map the distribution of ectopic twist, and measure embryo stiffness. For building mesofluidic devices, we describe modifications on ultra-thick photolithography, derive an analytical model that predicts the deflection of sidewalls, and discuss parametric calibration. This "mesomechanics" approach combines the high-throughput automation and precision of microfluidics with the biological relevance of live embryos to examine mechanotransduction. These analytical models facilitate the design of future devices to process multicellular organisms such as larvae, organoids, and mesoscale tissue samples.