Multilevel control of run orientation in Drosophila larval chemotaxis

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.

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.

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.

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.

The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function

It is difficult to answer important questions in neuroscience, such as: "how do neural circuits generate behaviour?," because research is limited by the complexity and inaccessibility of the mammalian nervous system. Invertebrate model organisms offer simpler networks that are easier to manipulate. As a result, much of what we know about the development of neural circuits is derived from work in crustaceans, nematode worms and arguably most of all, the fruit fly, Drosophila melanogaster. This review aims to demonstrate the utility of the Drosophila larval locomotor network as a model circuit, to those who do not usually use the fly in their work. This utility is explored first by discussion of the relatively complete connectome associated with one identified interneuron of the locomotor circuit, A27h, and relating it to similar circuits in mammals. Next, it is developed by examining its application to study two important areas of neuroscience research: critical periods of development and interindividual variability in neural circuits. In summary, this article highlights the potential to use the larval locomotor network as a "generic" model circuit, to provide insight into mammalian circuit development and function.

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.

Navigational strategies underlying temporal phototaxis in Drosophila larvae

Navigating across light gradients is essential for survival for many animals. However, we still have a poor understanding of the algorithms that underlie such behaviors. Here, we developed a novel closed-loop phototaxis assay for Drosophila larvae in which light intensity is always spatially uniform but updates depending on the location of the animal in the arena. Even though larvae can only rely on temporal cues during runs, we find that they are capable of finding preferred areas of low light intensity. Further detailed analysis of their behavior reveals that larvae turn more frequently and that heading angle changes increase when they experience brightness increments over extended periods of time. We suggest that temporal integration of brightness change during runs is an important - and so far largely unexplored - element of phototaxis.

Movements, embodiment and the emergence of decisions. Insights from insect navigation

We readily infer that animals make decisions, but what this implies is usually not clearly defined. The notion of 'decision-making' ultimately stems from human introspection, and is thus loaded with anthropomorphic assumptions. Notably, the decision is made internally, is based on information, and precedes the goal directed behaviour. Also, making a decision implies that 'something' did it, thus hints at the presence of a cognitive mind, whose existence is independent of the decision itself. This view may convey some truth, but here I take the opposite stance. Using examples from research in insect navigation, this essay highlights how apparent decisions can emerge without a brain, how actions can precede information or how sophisticated goal directed behaviours can be implemented without neural decisions. This perspective requires us to shake off the idea that behaviour is a consequence of the brain; and embrace the concept that movements arise from - as much as participate in - distributed interactions between various computational centres - including the body - that reverberate in closed-loop with the environment. From this perspective we may start to picture how a cognitive mind can be the consequence, rather than the cause, of such neural and body movements.

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.

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

Collapse

Grants

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

Collapse

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

Collapse

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.

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.

Neuroscience: An Olfactory Homunculus in the Insect Brain

Animals can follow olfactory traces to find food, detect a sexual mate, or avoid predators. A new study reveals that pheromone-specific projection neurons in the cockroach have a spatially tuned receptive field, and allow encoding spatial information of an odorant.

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.

Neural Substrates of Drosophila Larval Anemotaxis

Animals use sensory information to move toward more favorable conditions. Drosophila larvae can move up or down gradients of odors (chemotax), light (phototax), and temperature (thermotax) by modulating the probability, direction, and size of turns based on sensory input. Whether larvae can anemotax in gradients of mechanosensory cues is unknown. Further, although many of the sensory neurons that mediate taxis have been described, the central circuits are not well understood. Here, we used high-throughput, quantitative behavioral assays to demonstrate Drosophila larvae anemotax in gradients of wind speeds and to characterize the behavioral strategies involved. We found that larvae modulate the probability, direction, and size of turns to move away from higher wind speeds. This suggests that similar central decision-making mechanisms underlie taxis in somatosensory and other sensory modalities. By silencing the activity of single or very few neuron types in a behavioral screen, we found two sensory (chordotonal and multidendritic class III) and six nerve cord neuron types involved in anemotaxis. We reconstructed the identified neurons in an electron microscopy volume that spans the entire larval nervous system and found they received direct input from the mechanosensory neurons or from each other. In this way, we identified local interneurons and first- and second-order subesophageal zone (SEZ) and brain projection neurons. Finally, silencing a dopaminergic brain neuron type impairs anemotaxis. These findings suggest that anemotaxis involves both nerve cord and brain circuits. The candidate neurons and circuitry identified in our study provide a basis for future detailed mechanistic understanding of the circuit principles of anemotaxis.

Getting closer to the goal by being less capable

Understanding how systems with many semi-autonomous parts reach a desired target is a key question in biology (e.g., Drosophila larvae seeking food), engineering (e.g., driverless navigation), medicine (e.g., reliable movement for brain-damaged individuals), and socioeconomics (e.g., bottom-up goal-driven human organizations). Centralized systems perform better with better components. Here, we show, by contrast, that a decentralized entity is more efficient at reaching a target when its components are less capable. Our findings reproduce experimental results for a living organism, predict that autonomous vehicles may perform better with simpler components, offer a fresh explanation for why biological evolution jumped from decentralized to centralized design, suggest how efficient movement might be achieved despite damaged centralized function, and provide a formula predicting the optimum capability of a system's components so that it comes as close as possible to its target or goal.

Strength in diversity: functional diversity among olfactory neurons of the same type

Most animals depend upon olfaction to find food, mates, and to avoid predators. An animal's olfactory circuit helps it sense its olfactory environment and generate critical behavioral responses. The general architecture of the olfactory circuit, which is conserved across species, is made up of a few different neuronal types including first-order receptor neurons, second- and third-order neurons, and local interneurons. Each neuronal type differs in their morphology, physiology, and neurochemistry. However, several recent studies have suggested that there is intrinsic diversity even among neurons of the same type and that this diversity is important for neural function. In this review, we first examine instances of intrinsic diversity observed among individual types of olfactory neurons. Next, we review potential genetic and experience-based plasticity mechanisms that underlie this diversity. Finally, we consider the implications of intrinsic neuronal diversity for circuit function. Overall, we hope to highlight the importance of intrinsic diversity as a previously underestimated property of circuit function.

Statistical structure of locomotion and its modulation by odors

Most behaviors such as making tea are not stereotypical but have an obvious structure. However, analytical methods to objectively extract structure from non-stereotyped behaviors are immature. In this study, we analyze the locomotion of fruit flies and show that this non-stereotyped behavior is well-described by a Hierarchical Hidden Markov Model (HHMM). HHMM shows that a fly's locomotion can be decomposed into a few locomotor features, and odors modulate locomotion by altering the time a fly spends performing different locomotor features. Importantly, although all flies in our dataset use the same set of locomotor features, individual flies vary considerably in how often they employ a given locomotor feature, and how this usage is modulated by odor. This variation is so large that the behavior of individual flies is best understood as being grouped into at least three to five distinct clusters, rather than variations around an average fly.

Behavior Responses to Chemical and Optogenetic Stimuli in Drosophila Larvae

An animal’s ability to navigate an olfactory environment is critically dependent on the activities of its first-order olfactory receptor neurons (ORNs). While considerable research has focused on ORN responses to odorants, the mechanisms by which olfactory information is encoded in the activities of ORNs and translated into navigational behavior remain poorly understood. We sought to determine the contributions of most Drosophila melanogaster larval ORNs to navigational behavior. Using odorants to activate ORNs and a larval tracking assay to measure the corresponding behavioral response, we observed that larval ORN activators cluster into four groups based on the behavior responses elicited from larvae. This is significant because it provides new insights into the functional relationship between ORN activity and behavioral response. Subsequent optogenetic analyses of a subset of ORNs revealed previously undescribed properties of larval ORNs. Furthermore, our results indicated that different temporal patterns of ORN activation elicit different behavioral outputs: some ORNs respond to stimulus increments while others respond to stimulus decrements. These results suggest that the ability of ORNs to encode temporal patterns of stimulation increases the coding capacity of the olfactory circuit. Moreover, the ability of ORNs to sense stimulus increments and decrements facilitates instantaneous evaluations of concentration changes in the environment. Together, these ORN properties enable larvae to efficiently navigate a complex olfactory environment. Ultimately, knowledge of how ORN activity patterns and their weighted contributions influence odor coding may eventually reveal how peripheral information is organized and transmitted to subsequent layers of a neural circuit.

Algorithms for Olfactory Search across Species

Localizing the sources of stimuli is essential. Most organisms cannot eat, mate, or escape without knowing where the relevant stimuli originate. For many, if not most, animals, olfaction plays an essential role in search. While microorganismal chemotaxis is relatively well understood, in larger animals the algorithms and mechanisms of olfactory search remain mysterious. In this symposium, we will present recent advances in our understanding of olfactory search in flies and rodents. Despite their different sizes and behaviors, both species must solve similar problems, including meeting the challenges of turbulent airflow, sampling the environment to optimize olfactory information, and incorporating odor information into broader navigational systems.

Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

Organisms use environmental cues for directed navigation. Understanding the basic logic behind navigational decisions critically depends on the complexity of the nervous system. Due to the comparably simple organization of the nervous system of the fruit fly larva, it stands as a powerful model to study decision-making processes that underlie directed navigation. We have quantitatively measured phototaxis in response to well-defined sensory inputs. Subsequently, we have formulated a statistical stochastic model based on biased Markov chains to characterize the behavioural basis of negative phototaxis. Our experiments show that larvae make navigational decisions depending on two independent physical variables: light intensity and its spatial gradient. Furthermore, our statistical model quantifies how larvae balance two potentially-contradictory factors: minimizing exposure to light intensity and at the same time maximizing their distance to the light source. We find that the response to the light field is manifestly non-linear, and saturates above an intensity threshold. The model has been validated against our experimental biological data yielding insight into the strategy that larvae use to achieve their goal with respect to the navigational cue of light, an important piece of information for future work to study the role of the different neuronal components in larval phototaxis.

Concerted pulsatile and graded neural dynamics enables efficient chemotaxis in C. elegans

The ability of animals to effectively locate and navigate toward food sources is central for survival. Here, using C. elegans nematodes, we reveal the neural mechanism underlying efficient navigation in chemical gradients. This mechanism relies on the activity of two types of chemosensory neurons: one (AWA) coding gradients via stochastic pulsatile dynamics, and the second (AWC^ON) coding the gradients deterministically in a graded manner. The pulsatile dynamics of the AWA neuron adapts to the magnitude of the gradient derivative, allowing animals to take trajectories better oriented toward the target. The robust response of AWC^ON to negative derivatives promotes immediate turns, thus alleviating the costs incurred by erroneous turns dictated by the AWA neuron. This mechanism empowers an efficient navigation strategy that outperforms the classical biased-random walk strategy. This general mechanism thus may be applicable to other sensory modalities for efficient gradient-based navigation.

Finding one’s way to a food source along a complex gradient is central to survival for many animals. Here, the authors report that in C. elegans, the distinct response dynamics of two sensory neurons to odor gradients can support a navigation model more efficient than the biased-random walk.

Dedicated photoreceptor pathways in Drosophila larvae mediate navigation by processing either spatial or temporal cues

To integrate changing environmental cues with high spatial and temporal resolution is critical for animals to orient themselves. Drosophila larvae show an effective motor program to navigate away from light sources. How the larval visual circuit processes light stimuli to control navigational decision remains unknown. The larval visual system is composed of two sensory input channels, Rhodopsin5 (Rh5) and Rhodopsin6 (Rh6) expressing photoreceptors (PRs). We here characterize how spatial and temporal information are used to control navigation. Rh6-PRs are required to perceive temporal changes of light intensity during head casts, while Rh5-PRs are required to control behaviors that allow navigation in response to spatial cues. We characterize how distinct behaviors are modulated and identify parallel acting and converging features of the visual circuit. Functional features of the larval visual circuit highlight the principle of how early in a sensory circuit distinct behaviors may be computed by partly overlapping sensory pathways.

Reproducibility and replicability of rodent phenotyping in preclinical studies

The scientific community is increasingly concerned with the proportion of published “discoveries” that are not replicated in subsequent studies. The field of rodent behavioral phenotyping was one of the first to raise this concern, and to relate it to other methodological issues: the complex interaction between genotype and environment; the definitions of behavioral constructs; and the use of laboratory mice and rats as model species for investigating human health and disease mechanisms. In January 2015, researchers from various disciplines gathered at Tel Aviv University to discuss these issues. The general consensus was that the issue is prevalent and of concern, and should be addressed at the statistical, methodological and policy levels, but is not so severe as to call into question the validity and the usefulness of model organisms as a whole. Well-organized community efforts, coupled with improved data and metadata sharing, have a key role in identifying specific problems and promoting effective solutions. Replicability is closely related to validity, may affect generalizability and translation of findings, and has important ethical implications.

The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae

Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva – because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour–taste associative learning, as well as light/dark–electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages.

Common microbehavioral "footprint" of two distinct classes of conditioned aversion

Avoiding unfavorable situations is a vital skill and a constant task for any animal. Situations can be unfavorable because they feature something that the animal wants to escape from, or because they do not feature something that it seeks to obtain. We investigate whether the microbehavioral mechanisms by which these two classes of aversion come about are shared or distinct. We find that larval Drosophila avoid odors either previously associated with a punishment, or previously associated with the lack of a reward. These two classes of conditioned aversion are found to be strikingly alike at the microbehavioral level. In both cases larvae show more head casts when oriented toward the odor source than when oriented away, and direct fewer of their head casts toward the odor than away when oriented obliquely to it. Thus, conditioned aversion serving two qualitatively different functions—escape from a punishment or search for a reward—is implemented by the modulation of the same microbehavioral features. These features also underlie conditioned approach, albeit with opposite sign. That is, the larvae show conditioned approach toward odors previously associated with a reward, or with the lack of a punishment. In order to accomplish both these classes of conditioned approach the larvae show fewer head casts when oriented toward an odor, and direct more of their head casts toward it when they are headed obliquely. Given that the Drosophila larva is a genetically tractable model organism that is well suited to study simple circuits at the single-cell level, these analyses can guide future research into the neuronal circuits underlying conditioned approach and aversion, and the computational principles of conditioned search and escape.

Neural Circuits Underlying Fly Larval Locomotion

Locomotion is a complex motor behavior that may be expressed in different ways using a variety of strategies depending upon species and pathological or environmental conditions. Quadrupedal or bipedal walking, running, swimming, flying and gliding constitute some of the locomotor modes enabling the body, in all cases, to move from one place to another. Despite these apparent differences in modes of locomotion, both vertebrate and invertebrate species share, at least in part, comparable neural control mechanisms for locomotor rhythm and pattern generation and modulation. Significant advances have been made in recent years in studies of the genetic aspects of these control systems. Findings made specifically using Drosophila (fruit fly) models and preparations have contributed to further understanding of the key role of genes in locomotion. This review focuses on some of the main findings made in larval fruit flies while briefly summarizing the basic advantages of using this powerful animal model for studying the neural locomotor system.

Continuous lateral oscillations as a core mechanism for taxis in Drosophila larvae

Taxis behaviour in Drosophila larva is thought to consist of distinct control mechanisms triggering specific actions. Here, we support a simpler hypothesis: that taxis results from direct sensory modulation of continuous lateral oscillations of the anterior body, sparing the need for ‘action selection’. Our analysis of larvae motion reveals a rhythmic, continuous lateral oscillation of the anterior body, encompassing all head-sweeps, small or large, without breaking the oscillatory rhythm. Further, we show that an agent-model that embeds this hypothesis reproduces a surprising number of taxis signatures observed in larvae. Also, by coupling the sensory input to a neural oscillator in continuous time, we show that the mechanism is robust and biologically plausible. The mechanism provides a simple architecture for combining information across modalities, and explaining how learnt associations modulate taxis. We discuss the results in the light of larval neural circuitry and make testable predictions.

DOI:http://dx.doi.org/10.7554/eLife.15504.001

The speed-curvature power law in Drosophila larval locomotion

We report the discovery that the locomotor trajectories of Drosophila larvae follow the power-law relationship between speed and curvature previously found in the movements of human and non-human primates. Using high-resolution behavioural tracking in controlled but naturalistic sensory environments, we tested the law in maggots tracing different trajectory types, from reaching-like movements to scribbles. For most but not all flies, we found that the law holds robustly, with an exponent close to three-quarters rather than to the usual two-thirds found in almost all human situations, suggesting dynamic effects adding on purely kinematic constraints. There are different hypotheses for the origin of the law in primates, one invoking cortical computations, another viscoelastic muscle properties coupled with central pattern generators. Our findings are consistent with the latter view and demonstrate that the law is possible in animals with nervous systems orders of magnitude simpler than in primates. Scaling laws might exist because natural selection favours processes that remain behaviourally efficient across a wide range of neural and body architectures in distantly related species.

Searching for motifs in the behaviour of larval Drosophila melanogaster and Caenorhabditis elegans reveals continuity between behavioural states

We present a novel method for the unsupervised discovery of behavioural motifs in larval Drosophila melanogaster and Caenorhabditis elegans. A motif is defined as a particular sequence of postures that recurs frequently. The animal's changing posture is represented by an eigenshape time series, and we look for motifs in this time series. To find motifs, the eigenshape time series is segmented, and the segments clustered using spline regression. Unlike previous approaches, our method can classify sequences of unequal duration as the same motif. The behavioural motifs are used as the basis of a probabilistic behavioural annotator, the eigenshape annotator (ESA). Probabilistic annotation avoids rigid threshold values and allows classification uncertainty to be quantified. We apply eigenshape annotation to both larval Drosophila and C. elegans and produce a good match to hand annotation of behavioural states. However, we find many behavioural events cannot be unambiguously classified. By comparing the results with ESA of an artificial agent's behaviour, we argue that the ambiguity is due to greater continuity between behavioural states than is generally assumed for these organisms.

Differential Contributions of Olfactory Receptor Neurons in a Drosophila Olfactory Circuit

The ability of an animal to detect, discriminate, and respond to odors depends on the functions of its olfactory receptor neurons (ORNs). The extent to which each ORN, upon activation, contributes to chemotaxis is not well understood. We hypothesized that strong activation of each ORN elicits a different behavioral response in the Drosophila melanogaster larva by differentially affecting the composition of its navigational behavior. To test this hypothesis, we exposed Drosophila larvae to specific odorants to analyze the effect of individual ORN activity on chemotaxis. We used two different behavioral paradigms to analyze the chemotaxis response of larvae to odorants. When tested with five different odorants that elicit strong physiological responses from single ORNs, larval behavioral responses toward each odorant differed in the strength of attraction as well as in the composition of discrete navigational elements, such as runs and turns. Further, behavioral responses to odorants did not correlate with either the strength of odor gradients tested or the sensitivity of each ORN to its cognate odorant. Finally, we provide evidence that wild-type larvae with all ORNs intact exhibit higher behavioral variance than mutant larvae that have only a single pair of functional ORNs. We conclude that individual ORNs contribute differently to the olfactory circuit that instructs chemotactic responses. Our results, along with recent studies from other groups, suggest that ORNs are functionally nonequivalent units. These results have implications for understanding peripheral odor coding.

Generative rules of Drosophila locomotor behavior as a candidate homology across phyla

The discovery of shared behavioral processes across phyla is a significant step in the establishment of a comparative study of behavior. We use immobility as an origin and reference for the measurement of fly locomotor behavior; speed, walking direction and trunk orientation as the degrees of freedom shaping this behavior; and cocaine as the parameter inducing progressive transitions in and out of immobility. We characterize and quantify the generative rules that shape Drosophila locomotor behavior, bringing about a gradual buildup of kinematic degrees of freedom during the transition from immobility to normal behavior, and the opposite narrowing down into immobility. Transitions into immobility unfold via sequential enhancement and then elimination of translation, curvature and finally rotation. Transitions out of immobility unfold by progressive addition of these degrees of freedom in the opposite order. The same generative rules have been found in vertebrate locomotor behavior in several contexts (pharmacological manipulations, ontogeny, social interactions) involving transitions in-and-out of immobility. Recent claims for deep homology between arthropod central complex and vertebrate basal ganglia provide an opportunity to examine whether the rules we report also share common descent. Our approach prompts the discovery of behavioral homologies, contributing to the elusive problem of behavioral evolution.

Regulation of two motor patterns enables the gradual adjustment of locomotion strategy in Caenorhabditis elegans

In animal locomotion a tradeoff exists between stereotypy and flexibility: fast long-distance travelling (LDT) requires coherent regular motions, while local sampling and area-restricted search (ARS) rely on flexible movements. We report here on a posture control system in C. elegans that coordinates these needs. Using quantitative posture analysis we explain worm locomotion as a composite of two modes: regular undulations versus flexible turning. Graded reciprocal regulation of both modes allows animals to flexibly adapt their locomotion strategy under sensory stimulation along a spectrum ranging from LDT to ARS. Using genetics and functional imaging of neural activity we characterize the counteracting interneurons AVK and DVA that utilize FLP-1 and NLP-12 neuropeptides to control both motor modes. Gradual regulation of behaviors via this system is required for spatial navigation during chemotaxis. This work shows how a nervous system controls simple elementary features of posture to generate complex movements for goal-directed locomotion strategies.

DOI:http://dx.doi.org/10.7554/eLife.14116.001

Animals navigate through their environment using different strategies according to their current needs. For example, when the goal is to travel long distances, they move quickly and in an efficient way by employing regular, repetitive movements. However, when the aim is to explore the nearby area – to search for food, for example – animals move slowly and make more flexible movements. These different types of movement mostly use the same groups of muscles, and so animals must be able to alter how they control their muscles to yield these different strategies.

These movement strategies have been observed in many animal species, from worms to grazing cows, and researchers have mostly classified them into distinct behavioral states that the animals switch between. To date, the patterns of movements that underlie these strategies have not been described in detail.

The wavelike movement of the roundworm Caenorhabditis elegans has the advantage of being relatively easy to measure. By analyzing precise recordings of how the worms change posture as they move, Hums et al. now show that two main patterns of motion underlie worm movement. Regular whole-body waves (undulations) efficiently drive long-distance travel, while more complex turning motions allow the animals to flexibly change direction and so explore the local environment. Furthermore, the worms can fine-tune their movement strategy by gradually transitioning between the two patterns. This finding is opposed to the standard view, where animals switch between distinct behavioral states.

Hums et al. then studied how neuronal regulation in the C. elegans nervous system enables the worms to transition between the different movement strategies. In these experiments, neurons were manipulated and their activity was recorded. The results suggest that two classes of so called interneurons enable the worms to fine-tune their movements. Each class of these interneurons produces a signaling molecule (or neuropeptide) that counteracts the activity of the other signal; together both neuropeptides regulate the patterns of movements.

Further work is now needed to identify and investigate the downstream neurons that work together to represent the different patterns of movements in the roundworm. Future studies could also analyze whether other animals – such as swimming animals and limbed animals – use similar principles to change between distinct forms of movement and thus enact a range of behavioral strategies.

DOI:http://dx.doi.org/10.7554/eLife.14116.002

A Model of Drosophila Larva Chemotaxis

Detailed observations of larval Drosophila chemotaxis have characterised the relationship between the odour gradient and the runs, head casts and turns made by the animal. We use a computational model to test whether hypothesised sensorimotor control mechanisms are sufficient to account for larval behaviour. The model combines three mechanisms based on simple transformations of the recent history of odour intensity at the head location. The first is an increased probability of terminating runs in response to gradually decreasing concentration, the second an increased probability of terminating head casts in response to rapidly increasing concentration, and the third a biasing of run directions up concentration gradients through modulation of small head casts. We show that this model can be tuned to produce behavioural statistics comparable to those reported for the larva, and that this tuning results in similar chemotaxis performance to the larva. We demonstrate that each mechanism can enable odour approach but the combination of mechanisms is most effective, and investigate how these low-level control mechanisms relate to behavioural measures such as the preference indices used to investigate larval learning behaviour in group assays.

The larvae of the fruitfly are attracted to many odours. We use a computational model in which simulated larvae stop, start and redirect their crawling behaviour in response to their experience of changes in odour. We show that three simple rules for switching between behaviours are sufficient to produce larva-like results in a simulated agent.

Dynamical feature extraction at the sensory periphery guides chemotaxis

Behavioral strategies employed for chemotaxis have been described across phyla, but the sensorimotor basis of this phenomenon has seldom been studied in naturalistic contexts. Here, we examine how signals experienced during free olfactory behaviors are processed by first-order olfactory sensory neurons (OSNs) of the Drosophila larva. We find that OSNs can act as differentiators that transiently normalize stimulus intensity—a property potentially derived from a combination of integral feedback and feed-forward regulation of olfactory transduction. In olfactory virtual reality experiments, we report that high activity levels of the OSN suppress turning, whereas low activity levels facilitate turning. Using a generalized linear model, we explain how peripheral encoding of olfactory stimuli modulates the probability of switching from a run to a turn. Our work clarifies the link between computations carried out at the sensory periphery and action selection underlying navigation in odor gradients.

DOI:http://dx.doi.org/10.7554/eLife.06694.001

Fruit flies are attracted to the smell of rotting fruit, and use it to guide them to nearby food sources. However, this task is made more challenging by the fact that the distribution of scent or odor molecules in the air is constantly changing. Fruit flies therefore need to cope with, and exploit, this variation if they are to use odors as cues.

Odor molecules bind to receptors on the surface of nerve cells called olfactory sensory neurons, and trigger nerve impulses that travel along these cells. While many studies have investigated how fruit flies can distinguish between different odors, less is known about how animals can use variation in the strength of an odor to guide them towards its source.

Optogenetics is a technique that allows neuroscientists to control the activities of individual nerve cells, simply by shining light on to them. Because fruit fly larvae are almost transparent, optogenetics can be used on freely moving animals. Now, Schulze, Gomez-Marin et al. have used optogenetics in these larvae to trigger patterns of activity in individual olfactory sensory neurons that mimic the activity patterns elicited by real odors. These virtual realities were then used to study, in detail, some of the principles that control the sensory navigation of a larva—as it moves using a series of forward ‘runs’ and direction-changing ‘turns’.

Olfactory sensory neurons responded most strongly whenever light levels changed rapidly in strength (which simulated a rapid change in odor concentration). On the other hand, these neurons showed relatively little response to constant light levels (i.e., constant odors). This indicates that the activity of olfactory sensory neurons typically represents the rate of change in the concentration of an odor. An independent study by Kim et al. found that olfactory sensory neurons in adult fruit flies also respond in a similar way.

Schulze, Gomez-Marin et al. went on to show that the signals processed by a single type of olfactory sensory neuron could be used to predict a larva's behavior. Larvae tended to turn less when their olfactory sensory neurons were highly active. Low levels and inhibition of activity in the olfactory sensory neurons had the opposite effect; this promoted turning. It remains to be determined how this relatively simple control principle is implemented by the neural circuits that connect sensory neurons to the parts of a larva's nervous system that are involved with movement.

DOI:http://dx.doi.org/10.7554/eLife.06694.002

Computations underlying Drosophila photo-taxis, odor-taxis, and multi-sensory integration

To better understand how organisms make decisions on the basis of temporally varying multi-sensory input, we identified computations made by Drosophila larvae responding to visual and optogenetically induced fictive olfactory stimuli. We modeled the larva's navigational decision to initiate turns as the output of a Linear-Nonlinear-Poisson cascade. We used reverse-correlation to fit parameters to this model; the parameterized model predicted larvae's responses to novel stimulus patterns. For multi-modal inputs, we found that larvae linearly combine olfactory and visual signals upstream of the decision to turn. We verified this prediction by measuring larvae's responses to coordinated changes in odor and light. We studied other navigational decisions and found that larvae integrated odor and light according to the same rule in all cases. These results suggest that photo-taxis and odor-taxis are mediated by a shared computational pathway.

DOI:http://dx.doi.org/10.7554/eLife.06229.001

Living organisms can sense cues from their surroundings and respond in appropriate ways. For example, animals will often move towards the smell of food or away from potential threats, such as predators. However, it is not fully understood how an animal's nervous system is set up to allow sensory information to control how the animal navigates its environment. It is also not clear how animals ‘decide’ what to do when they receive conflicting information from different senses.

Optogenetics is a technique that allows neuroscientists to control the activities of individual nerve cells simply by shining light on to them. Fruit fly larvae have a simple but well-studied nervous system, and they are nearly transparent, so scientists can use optogenetics to activate nerve cells in freely moving larvae.

Fruit fly larvae move in a series of forward ‘runs’ and direction-changing ‘turns’ and use sensory cues to decide when to turn, how large of a turn to make, and whether to turn left or right. Gepner, Mihovilovic Skanata et al. used optogenetics to stimulate different combinations of sensory nerve cells in larvae, while tracking the larvae's movements to discover exactly what information they used to make these decisions. An independent study by Hernandez-Nunez et al. also used a similar approach.

Fruit fly larvae are attracted towards scents from rotting fruit and are repelled by light—in particular, larvae are most sensitive to blue light but cannot detect red light. Therefore, Gepner, Mihovilovic Skanata et al. could expose the larvae to blue light to activate light-sensing nerve cells as normal, and use red light to activate odor-sensing nerve cells via optogenetics. These experiments showed that larvae changed direction more often when the level of blue light was increased or when the level of red light (which simulated the detection of odors from rotting fruits) was decreased.

Analysis of the data from these experiments revealed that larvae essentially assign negative values to the blue light and positive values to the ‘odor-mimicking’ red light. The larvae then use the sum of these two values to dictate their next move. This suggests that navigation in response to both light and odors is supported by the same pathways in a larva's nervous system.

The approach of using optogenetics in combination with quantitative analysis, as used in these two independent studies, is now opening the door to a more complete understanding of the connections between the activities of sensory nerve cells and perception and behavior.

DOI:http://dx.doi.org/10.7554/eLife.06229.002

Chemosensory apparatus of Drosophila larvae

Many insects, including Drosophila melanogaster, have a rich repertoire of olfactory behavior. Combination of robust behavioral assays, physiological and molecular tools render D. melanogaster as highly suitable system for olfactory studies. The small number of neurons in the olfactory system of fruit flies, especially the number of sensory neurons in the larval stage, makes the exploration of sensory coding at all stages of its nervous system a potentially tractable goal, which is not possible in the foreseeable future in any mammalian preparation. Advances in physiological recordings, olfactory signaling and detailed analysis of behavior, can place larvae in a position to ask previously unanswerable questions.

The impact of odor-reward memory on chemotaxis in larval Drosophila

How do animals adaptively integrate innate with learned behavioral tendencies? We tackle this question using chemotaxis as a paradigm. Chemotaxis in the Drosophila larva largely results from a sequence of runs and oriented turns. Thus, the larvae minimally need to determine (i) how fast to run, (ii) when to initiate a turn, and (iii) where to direct a turn. We first report how odor-source intensities modulate these decisions to bring about higher levels of chemotactic performance for higher odor-source intensities during innate chemotaxis. We then examine whether the same modulations are responsible for alterations of chemotactic performance by learned odor “valence” (understood throughout as level of attractiveness). We find that run speed (i) is neither modulated by the innate nor by the learned valence of an odor. Turn rate (ii), however, is modulated by both: the higher the innate or learned valence of the odor, the less often larvae turn whenever heading toward the odor source, and the more often they turn when heading away. Likewise, turning direction (iii) is modulated concordantly by innate and learned valence: turning is biased more strongly toward the odor source when either innate or learned valence is high. Using numerical simulations, we show that a modulation of both turn rate and of turning direction is sufficient to account for the empirically found differences in preference scores across experimental conditions. Our results suggest that innate and learned valence organize adaptive olfactory search behavior by their summed effects on turn rate and turning direction, but not on run speed. This work should aid studies into the neural mechanisms by which memory impacts specific aspects of behavior.

A central neural pathway controlling odor tracking in Drosophila

Chemotaxis is important for the survival of most animals. How the brain translates sensory input into motor output beyond higher olfactory processing centers is largely unknown. We describe a group of excitatory neurons, termed Odd neurons, which are important for Drosophila larval chemotaxis. Odd neurons receive synaptic input from projection neurons in the calyx of the mushroom body and project axons to the central brain. Functional imaging shows that some of the Odd neurons respond to odor. Larvae in which Odd neurons are silenced are less efficient at odor tracking than controls and sample the odor space more frequently. Larvae in which the excitability of Odd neurons is increased are better at odor intensity discrimination and odor tracking. Thus, the Odd neurons represent a distinct pathway that regulates the sensitivity of the olfactory system to odor concentrations, demonstrating that efficient chemotaxis depends on processing of odor strength downstream of higher olfactory centers.

A group of segmental premotor interneurons regulates the speed of axial locomotion in Drosophila larvae

BACKGROUND

Animals control the speed of motion to meet behavioral demands. Yet, the underlying neuronal mechanisms remain poorly understood. Here we show that a class of segmentally arrayed local interneurons (period-positive median segmental interneurons, or PMSIs) regulates the speed of peristaltic locomotion in Drosophila larvae.

RESULTS

PMSIs formed glutamatergic synapses on motor neurons and, when optogenetically activated, inhibited motor activity, indicating that they are inhibitory premotor interneurons. Calcium imaging showed that PMSIs are rhythmically active during peristalsis with a short time delay in relation to motor neurons. Optogenetic silencing of these neurons elongated the duration of motor bursting and greatly reduced the speed of larval locomotion.

CONCLUSIONS

Our results suggest that PMSIs control the speed of axial locomotion by limiting, via inhibition, the duration of motor outputs in each segment. Similar mechanisms are found in the regulation of mammalian limb locomotion, suggesting that common strategies may be used to control the speed of animal movements in a diversity of species.

Immediate and punitive impact of mechanosensory disturbance on olfactory behaviour of larval Drosophila

The ability to respond to and to learn about mechanosensory disturbance is widespread among animals. Using Drosophila larvae, we describe how the frequency of mechanosensory disturbance ('buzz') affects three aspects of behaviour: free locomotion, innate olfactory preference, and potency as a punishment. We report that (i) during 2-3 seconds after buzz onset the larvae slowed down and then turned, arguably to escape this situation; this was seen for buzz frequencies of 10, 100, and 1000 Hz, (ii) innate olfactory preference was reduced when tested in the presence of the buzz; this effect was strongest for the 100 Hz frequency, (iii) after odour-buzz associative training, we observed escape from the buzz-associated odour; this effect was apparent for 10 and 100, but not for 1000 Hz. We discuss the multiple behavioural effects of mechanosensation and stress that the immediate effects on locomotion and the impact as punishment differ in their frequency-dependence. Similar dissociations between immediate, reflexive behavioural effects and reinforcement potency were previously reported for sweet, salty and bitter tastants. It should be interesting to see how these features map onto the organization of sensory, ascending pathways.

Complex and non-redundant signals from individual odor receptors that underlie chemotaxis behavior in Drosophila melanogaster larvae

The rules by which odor receptors encode odors and allow behavior are still largely unexplored. Although large data sets of electrophysiological responses of receptors to odors have been generated, few hypotheses have been tested with behavioral assays. We use a data set on odor responses of Drosophila larval odor receptors coupled with chemotaxis behavioral assays to examine rules of odor coding. Using mutants of odor receptors, we have found that odor receptors with similar electrophysiological responses to odors across concentrations play non-redundant roles in odor coding at specific odor concentrations. We have also found that high affinity receptors for odors determine behavioral response thresholds, but the rules for determining peak behavioral responses are more complex. While receptor mutants typically show loss of attraction to odors, some receptor mutants result in increased attraction at specific odor concentrations. The odor receptor mutants were rescued using transgenic expression of odor receptors, validating assignment of phenotypes to the alleles. Vapor pressures alone cannot fully explain behavior in our assay. Finally, some odors that did not elicit strong electrophysiological responses are associated with behavioral phenotypes upon examination of odor receptor mutants. This result is consistent with the role of sensory neurons in lateral inhibition via local interneurons in the antennal lobe. Taken together, our results suggest a complexity of odor coding rules even in a simple olfactory sensory system.