Reverse-correlation analysis of navigation dynamics in Drosophila larva using optogenetics

Navigation strategies in Caenorhabditis elegans are differentially altered by learning

Learned olfactory-guided navigation is a powerful platform for studying how a brain generates goal-directed behaviors. However, the quantitative changes that occur in sensorimotor transformations and the underlying neural circuit substrates to generate such learning-dependent navigation is still unclear. Here we investigate learned sensorimotor processing for navigation in the nematode Caenorhabditis elegans by measuring and modeling experience-dependent odor and salt chemotaxis. We then explore the neural basis of learned odor navigation through perturbation experiments. We develop a novel statistical model to characterize how the worm employs two behavioral strategies: a biased random walk and weathervaning. We infer weights on these strategies and characterize sensorimotor kernels that govern them by fitting our model to the worm's time-varying navigation trajectories and precise sensory experiences. After olfactory learning, the fitted odor kernels reflect how appetitive and aversive trained worms up- and down-regulate both strategies, respectively. The model predicts an animal's past olfactory learning experience with  > 90% accuracy given finite observations, outperforming a classical chemotaxis metric. The model trained on natural odors further predicts the animals' learning-dependent response to optogenetically induced odor perception. Our measurements and model show that behavioral variability is altered by learning-trained worms exhibit less variable navigation than naive ones. Genetically disrupting individual interneuron classes downstream of an odor-sensing neuron reveals that learned navigation strategies are distributed in the network. Together, we present a flexible navigation algorithm that is supported by distributed neural computation in a compact brain.

Q-learning with temporal memory to navigate turbulence

We consider the problem of olfactory searches in a turbulent environment. We focus on agents that respond solely to odor stimuli, with no access to spatial perception nor prior information about the odor. We ask whether navigation to a target can be learned robustly within a sequential decision making framework. We develop a reinforcement learning algorithm using a small set of interpretable olfactory states and train it with realistic turbulent odor cues. By introducing a temporal memory, we demonstrate that two salient features of odor traces, discretized in few olfactory states, are sufficient to learn navigation in a realistic odor plume. Performance is dictated by the sparse nature of turbulent odors. An optimal memory exists which ignores blanks within the plume and activates a recovery strategy outside the plume. We obtain the best performance by letting agents learn their recovery strategy and show that it is mostly casting cross wind, similar to behavior observed in flying insects. The optimal strategy is robust to substantial changes in the odor plumes, suggesting minor parameter tuning may be sufficient to adapt to different environments.

CRASH2p: Closed-loop Two Photon Imaging in a Freely Moving Animal

Direct measurement of neural activity in freely moving animals is essential for understanding how the brain controls and represents behaviors. Genetically encoded calcium indicators report neural activity as changes in fluorescence intensity, but brain motion confounds quantitative measurement of fluorescence. Translation, rotation, and deformation of the brain and the movements of intervening scattering or auto-fluorescent tissue all alter the amount of fluorescent light captured by a microscope. Compared to single-photon approaches, two photon microscopy is less sensitive to scattering and off-target fluorescence, but more sensitive to motion, and two photon imaging has always required anchoring the microscope to the brain. We developed a closed-loop resonant axial-scanning high-speed two photon (CRASH2p) microscope for real-time 3D motion correction in unrestrained animals, without implantation of reference markers. We complemented CRASH2p with a novel scanning strategy and a multi-stage registration pipeline. We performed volumetric ratiometrically corrected functional imaging in the CNS of freely moving Drosophila larvae and discovered previously unknown neural correlates of behavior.

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.

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.

Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila

Most real-world behaviors - such as odor-guided locomotion - are performed with incomplete information. Activity in olfactory receptor neuron (ORN) classes provides information about odor identity but not the location of its source. In this study, we investigate the sensorimotor transformation that relates ORN activation to locomotion changes in Drosophila by optogenetically activating different combinations of ORN classes and measuring the resulting changes in locomotion. Three features describe this sensorimotor transformation: First, locomotion depends on both the instantaneous firing frequency (f) and its change (df); the two together serve as a short-term memory that allows the fly to adapt its motor program to sensory context automatically. Second, the mapping between (f, df) and locomotor parameters such as speed or curvature is distinct for each pattern of activated ORNs. Finally, the sensorimotor mapping changes with time after odor exposure, allowing information integration over a longer timescale.

Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience

Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience - their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem - the control of high-speed electrical activity, with great precision and ease, in the brain.

Rodent attention: Probing the mouse mind with reverse correlation

A novel approach to studying attention in mice reveals processes similar to those in humans and lays out an efficient way to explore its neuronal correlates in a genetically tractable animal model.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system's capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Temporal novelty detection and multiple timescale integration drive Drosophila orientation dynamics in temporally diverse olfactory environments

To survive, insects must effectively navigate odor plumes to their source. In natural plumes, turbulent winds break up smooth odor regions into disconnected patches, so navigators encounter brief bursts of odor interrupted by bouts of clean air. The timing of these encounters plays a critical role in navigation, determining the direction, rate, and magnitude of insects' orientation and speed dynamics. Disambiguating the specific role of odor timing from other cues, such as spatial structure, is challenging due to natural correlations between plumes' temporal and spatial features. Here, we use optogenetics to isolate temporal features of odor signals, examining how the frequency and duration of odor encounters shape the navigational decisions of freely-walking Drosophila. We find that fly angular velocity depends on signal frequency and intermittency-the fraction of time signal can be detected-but not directly on durations. Rather than switching strategies when signal statistics change, flies smoothly transition between signal regimes, by combining an odor offset response with a frequency-dependent novelty-like response. In the latter, flies are more likely to turn in response to each odor hit only when the hits are sparse. Finally, the upwind bias of individual turns relies on a filtering scheme with two distinct timescales, allowing rapid and sustained responses in a variety of signal statistics. A quantitative model incorporating these ingredients recapitulates fly orientation dynamics across a wide range of environments and shows that temporal novelty detection, when combined with odor motion detection, enhances odor plume navigation.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system’s capabilities to perform continuous observation of exploratory behavior over a duration of six hours with and without a thermal gradient present, and in a single larva for over 30 hours. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

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.

Plant optogenetics: Applications and perspectives

To understand cell biological processes, like signalling pathways, protein movements, or metabolic processes, precise tools for manipulation are desired. Optogenetics allows to control cellular processes by light and can be applied at a high temporal and spatial resolution. In the last three decades, various optogenetic applications have been developed for animal, fungal, and prokaryotic cells. However, using optogenetics in plants has been difficult due to biological and technical issues, like missing cofactors, the presence of endogenous photoreceptors, or the necessity of light for photosynthesis, which potentially activates optogenetic tools constitutively. Recently developed tools overcome these limitations, making the application of optogenetics feasible also in plants. Here, we highlight the most useful recent applications in plants and give a perspective for future optogenetic approaches in plants science.

Validation of an Optogenetic Approach to the Study of Olfactory Behavior in the T-Maze of Drosophila melanogaster Adults

Simple Summary

The fruit fly (Drosophila melanogaster) has been used as a model organism to study the olfactory system of insects thanks to the wide range of genetic tools available in this species. Among these tools, optogenetics allows the immediate alteration of the functioning of certain cells with light by the targeted expression of light receptor proteins in these cells. Thus, by successively expressing these receptors in different elements of the behavioral circuit, it is possible to evaluate their effect on the final behavior of the organism. However, the use of optogenetics to dissect the receptor elements of adult olfactory behavior presents a challenge because most odorants elicit gradual attraction or avoidance depending on their concentration, complicating the representative substitution of odor by light. In this work, we explore a dual excitation model in which the subject responds to various odorant concentrations while the olfactory receptor neurons are activated by light. The dose–response curve in these flies remains odorant concentration dependent, but with reduced sensitivity compared to olfactory stimulation alone. The existence of an effect associated with each of the two stimuli, odor and light, allows us to explore the quantitative contribution of the receptor elements to olfactory behavior also by optogenetics.

Abstract

Optogenetics enables the alteration of neural activity using genetically targeted expression of light activated proteins for studying behavioral circuits in several species including Drosophila. The main idea behind this approach is to replace the native behavioral stimulus by the light-induced electrical activation of different points of the circuit. Therefore, its effects on subsequent steps of the circuit or on the final behavior can be analyzed. However, the use of optogenetics to dissect the receptor elements of the adult olfactory behavior presents a challenge due to one additional factor: Most odorants elicit attraction or avoidance depending on their concentration; this complicates the representative replacement of odor activation of olfactory sensory neurons (OSNs) by light. Here, we explore a dual excitation model where the subject is responding to odors while the OSNs are optogenetically activated. Thereby, we can assess if and how the olfactory behavior is modified. We measure the effects of light excitation on the response to several odorant concentrations. The dose-response curve of these flies still depends on odor concentration but with reduced sensitivity compared to olfactory stimulation alone. These results are consistent with behavioral tests performed with a background odor and suggest an additive effect of light and odor excitation on OSNs.

Perceptual Weighting of V1 Spikes Revealed by Optogenetic White Noise Stimulation

During visually guided behaviors, mere hundreds of milliseconds can elapse between a sensory input and its associated behavioral response. How spikes occurring at different times are integrated to drive perception and action remains poorly understood. We delivered random trains of optogenetic stimulation (white noise) to excite inhibitory interneurons in V1 of mice of both sexes while they performed a visual detection task. We then performed a reverse correlation analysis on the optogenetic stimuli to generate a neuronal-behavioral kernel, an unbiased, temporally precise estimate of how suppression of V1 spiking at different moments around the onset of a visual stimulus affects detection of that stimulus. Electrophysiological recordings enabled us to capture the effects of optogenetic stimuli on V1 responsivity and revealed that the earliest stimulus-evoked spikes are preferentially weighted for guiding behavior. These data demonstrate that white noise optogenetic stimulation is a powerful tool for understanding how patterns of spiking in neuronal populations are decoded in generating perception and action.SIGNIFICANCE STATEMENT During visually guided actions, continuous chains of neurons connect our retinas to our motoneurons. To unravel circuit contributions to behavior, it is crucial to establish the relative functional position(s) that different neural structures occupy in processing and relaying the signals that support rapid, precise responses. To address this question, we randomly inhibited activity in mouse V1 throughout the stimulus-response cycle while the animals did many repetitions of a visual task. The period that led to impaired performance corresponded to the earliest stimulus-driven response in V1, with no effect of inhibition immediately before or during late stages of the stimulus-driven response. This approach offers experimenters a powerful method for uncovering the temporal weighting of spikes from stimulus to response.

Optogenetic and thermogenetic manipulation of defined neural circuits and behaviors in Drosophila

Neural network dynamics underlying flexible animal behaviors remain elusive. The fruit fly Drosophila melanogaster is considered an excellent model in behavioral neuroscience because of its simple neuroanatomical architecture and the availability of various genetic methods. Moreover, Drosophila larvae's transparent body allows investigators to use optical methods on freely moving animals, broadening research directions. Activating or inhibiting well-defined events in excitable cells with a fine temporal resolution using optogenetics and thermogenetics led to the association of functions of defined neural populations with specific behavioral outputs such as the induction of associative memory. Furthermore, combining optogenetics and thermogenetics with state-of-the-art approaches, including connectome mapping and machine learning-based behavioral quantification, might provide a complete view of the experience- and time-dependent variations of behavioral responses. These methodologies allow further understanding of the functional connections between neural circuits and behaviors such as chemosensory, motivational, courtship, and feeding behaviors and sleep, learning, and memory.

Most primary olfactory neurons have individually neutral effects on behavior

Animals use olfactory receptors to navigate mates, food, and danger. However, for complex olfactory systems, it is unknown what proportion of primary olfactory sensory neurons can individually drive avoidance or attraction. Similarly, the rules that govern behavioral responses to receptor combinations are unclear. We used optogenetic analysis in Drosophila to map the behavior elicited by olfactory-receptor neuron (ORN) classes: just one-fifth of ORN-types drove either avoidance or attraction. Although wind and hunger are closely linked to olfaction, neither had much effect on single-class responses. Several pooling rules have been invoked to explain how ORN types combine their behavioral influences; we activated two-way combinations and compared patterns of single- and double-ORN responses: these comparisons were inconsistent with simple pooling. We infer that the majority of primary olfactory sensory neurons have neutral behavioral effects individually, but participate in broad, odor-elicited ensembles with potent behavioral effects arising from complex interactions.

Serotonergic neurons translate taste detection into internal nutrient regulation

The nervous and endocrine systems coordinately monitor and regulate nutrient availability to maintain energy homeostasis. Sensory detection of food regulates internal nutrient availability in a manner that anticipates food intake, but sensory pathways that promote anticipatory physiological changes remain unclear. Here, we identify serotonergic (5-HT) neurons as critical mediators that transform gustatory detection by sensory neurons into the activation of insulin-producing cells and enteric neurons in Drosophila. One class of 5-HT neurons responds to gustatory detection of sugars, excites insulin-producing cells, and limits consumption, suggesting that they anticipate increased nutrient levels and prevent overconsumption. A second class of 5-HT neurons responds to gustatory detection of bitter compounds and activates enteric neurons to promote gastric motility, likely to stimulate digestion and increase circulating nutrients upon food rejection. These studies demonstrate that 5-HT neurons relay acute gustatory detection to divergent pathways for longer-term stabilization of circulating nutrients.

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.

Taste sensing and sugar detection mechanisms in Drosophila larval primary taste center

Despite the small number of gustatory sense neurons, Drosophila larvae are able to sense a wide range of chemicals. Although evidence for taste multimodality has been provided in single neurons, an overview of gustatory responses at the periphery is missing and hereby we explore whole-organ calcium imaging of the external taste center. We find that neurons can be activated by different combinations of taste modalities, including opposite hedonic valence and identify distinct temporal dynamics of response. Although sweet sensing has not been fully characterized so far in the external larval gustatory organ, we recorded responses elicited by sugar. Previous findings established that larval sugar sensing relies on the Gr43a pharyngeal receptor, but the question remains if external neurons contribute to this taste. Here, we postulate that external and internal gustation use distinct and complementary mechanisms in sugar sensing and we identify external sucrose sensing neurons.

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.

The chemosensory system of the Drosophila larva: an overview of current understanding

Animals must sense their surroundings and be able to distinguish between relevant and irrelevant cues. An enticing area of research aims to uncover the mechanisms by which animals respond to chemical signals that constitute critical sensory input. In this review, we describe the principles of a model chemosensory system: the Drosophila larva. While distinct in many ways, larval behaviour is reminiscent of the dogmatic goals of life: to reach a stage of reproductive potential. It takes into account a number of distinct and identifiable parameters to ultimately provoke or modulate appropriate behavioural output. In this light, we describe current knowledge of chemosensory anatomy, genetic components, and the processing logic of chemical cues. We outline recent advancements and summarize the hypothesized neural circuits of sensory systems. Furthermore, we note yet-unanswered questions to create a basis for further investigation of molecular and systemic mechanisms of chemosensation in Drosophila and beyond.

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.

Finding the Brain in the Nose

Olfaction is fundamentally distinct from other sensory modalities. Natural odor stimuli are complex mixtures of volatile chemicals that interact in the nose with a receptor array that, in rodents, is built from more than 1,000 unique receptors. These interactions dictate a peripheral olfactory code, which in the brain is transformed and reformatted as it is broadcast across a set of highly interconnected olfactory regions. Here we discuss the problems of characterizing peripheral population codes for olfactory stimuli, of inferring the specific functions of different higher olfactory areas given their extensive recurrence, and of ultimately understanding how odor representations are linked to perception and action. We argue that, despite the differences between olfaction and other sensory modalities, addressing these specific questions will reveal general principles underlying brain function.

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.

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.

Ionotropic Receptor-dependent cool cells control the transition of temperature preference in Drosophila larvae

Temperature sensation guides animals to avoid temperature extremes and to seek their optimal temperatures. The larval stage of Drosophila development has a dramatic effect on temperature preference. While early-stage Drosophila larvae pursue a warm temperature, late-stage larvae seek a significantly lower temperature. Previous studies suggest that this transition depends on multiple rhodopsins at the late larval stage. Here, we show that early-stage larvae, in which dorsal organ cool cells (DOCCs) are functionally blocked, exhibit similar cool preference to that of wild type late-stage larvae. The molecular thermoreceptors in DOCCs are formed by three members of the Ionotropic Receptor (IR) family, IR21a, IR93a, and IR25a. Early-stage larvae of each Ir mutant pursue a cool temperature, similar to that of wild type late-stage larvae. At the late larval stage, DOCCs express decreased IR proteins and exhibit reduced cool responses. Importantly, late-stage larvae that overexpress IR21a, IR93a, and IR25a in DOCCs exhibit similar warm preference to that of wild type early-stage larvae. These data suggest that IR21a, IR93a, and IR25a in DOCCs navigate early-stage larvae to avoid cool temperatures and the reduction of these IR proteins in DOCCs results in animals remaining in cool regions during the late larval stage. Together with previous studies, we conclude that multiple temperature-sensing systems are regulated for the transition of temperature preference in fruit fly larvae.

Animals depend on their temperature-sensing systems to avoid noxious temperature extremes and to seek optimal temperatures to survive, mate, and reproduce. Some animals pursue different optimal temperatures during development. We use fruit flies as a model to investigate how temperature-sensing systems are modulated to guide animals to distinct optimal temperatures during development. While early-stage fruit fly larvae pursue a warm temperature, late-stage larvae seek a lower temperature. Previous studies find that this transition depends on multiple rhodopsin molecules. In this study, we find an additional mechanism that also contributes to this transition. At the early larval stage, a set of cool-sensing cells express a high level of cool responsive molecules, respond strongly to low temperatures, and drive animals to avoid cool regions. At the late larval stage, these cool-sensing cells become less sensitive to low temperatures due to the decreased expression of cool responsive molecules and, thus, animals remain in cool regions. Together with previous studies, we conclude that multiple temperature-sensing systems are regulated for the transition of temperature preference in fruit fly larvae.

Optogenetics in Drosophila

The fruit fly Drosophila melanogaster, an insect 4 mm long, has served as the experimental subject in a wide range of biological research, including neuroscience. In this chapter, we briefly introduce optogenetic applications in Drosophila neuroscience research. First, we describe the development of Drosophila from egg to adult. In fly neuroscience, temperature-controlled perturbation of neural activity, sometimes called "thermogenetics," has been an invaluable tool that predates the advent of optogenetics. After briefly introducing this perturbation technique, we describe the process of generating transgenic flies that express optogenetic probes in a specific group of cells. Transgenic techniques are crucial in the application of optogenetics in Drosophila neuroscience; here we introduce the transposon P-elements, ϕC31 integrase, and CRISPR-Cas9 methods. As for cell-specific gene expression techniques, the binary expression systems utilizing Gal4-UAS, LexA-lexAop, and Q-system are described. We also present a short and basic optogenetic experiment with Drosophila larvae as a practical example. Finally, we review a few recent studies in Drosophila neuroscience that made use of optogenetics. In this overview of fly development, transgenic methods, and applications of optogenetics, we present an introductory background to optogenetics in Drosophila.

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.

Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. Here we imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. We found that navigation was stochastic and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. We find that in less predictable environments, where encounters are random in both space and time, walking flies navigate with random walks biased by encounter timing.

Controlling the behaviour of Drosophila melanogaster via smartphone optogenetics

Invertebrates such as Drosophila melanogaster have proven to be a valuable model organism for studies of the nervous system. In order to control neuronal activity, optogenetics has evolved as a powerful technique enabling non-invasive stimulation using light. This requires light sources that can deliver patterns of light with high temporal and spatial precision. Currently employed light sources for stimulation of small invertebrates, however, are either limited in spatial resolution or require sophisticated and bulky equipment. In this work, we used smartphone displays for optogenetic control of Drosophila melanogaster. We developed an open-source smartphone app that allows time-dependent display of light patterns and used this to activate and inhibit different neuronal populations in both larvae and adult flies. Characteristic behavioural responses were observed depending on the displayed colour and brightness and in agreement with the activation spectra and light sensitivity of the used channelrhodopsins. By displaying patterns of light, we constrained larval movement and were able to guide larvae on the display. Our method serves as a low-cost high-resolution testbench for optogenetic experiments using small invertebrate species and is particularly appealing to application in neuroscience teaching labs.

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.

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila

Previous work has characterized how walking Drosophila coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. Here, we demonstrate a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity that does not require real-time tracking. Instead, we activate at random, precise locations in time and space and use post hoc analysis to determine behavioral responses to specific activations. Using this method, we have characterized limb coordination and walking behavior in response to transient activation of mechanosensitive bristle neurons and sweet-sensing chemoreceptor neurons. Our findings reveal that activating these neurons has opposite effects on turning, and that activations in different limbs and body regions produce distinct behaviors.

Covert sleep-related biological processes are revealed by probabilistic analysis in Drosophila

Reduced sleep duration and disrupted sleep quality are correlated with adverse mental and physical health outcomes. Better tools for measuring the internal drives for sleep and wake in model organisms would facilitate understanding the role of sleep quality in health. We defined two conditional probabilities, P(Wake) and P(Doze), that can be calculated from recordings of Drosophila activity without disturbing the animal. We demonstrated that P(Wake) is a measure of sleep depth and that P(Doze) is a measure of sleep pressure. In parallel, we developed an automatic classifier for state-based analysis of Drosophila behavior. These analysis tools will improve our understanding of the pharmacology and neuronal regulation of behavioral drives in the Drosophila brain.

Sleep pressure and sleep depth are key regulators of wake and sleep. Current methods of measuring these parameters in Drosophila melanogaster have low temporal resolution and/or require disrupting sleep. Here we report analysis tools for high-resolution, noninvasive measurement of sleep pressure and depth from movement data. Probability of initiating activity, P(Wake), measures sleep depth while probability of ceasing activity, P(Doze), measures sleep pressure. In vivo and computational analyses show that P(Wake) and P(Doze) are largely independent and control the amount of total sleep. We also develop a Hidden Markov Model that allows visualization of distinct sleep/wake substates. These hidden states have a predictable relationship with P(Doze) and P(Wake), suggesting that the methods capture the same behaviors. Importantly, we demonstrate that both the Doze/Wake probabilities and the sleep/wake substates are tied to specific biological processes. These metrics provide greater mechanistic insight into behavior than measuring the amount of sleep alone.

Cellular Basis of Bitter-Driven Aversive Behaviors in Drosophila Larva

Feeding, a critical behavior for survival, consists of a complex series of behavioral steps. In Drosophila larvae, the initial steps of feeding are food choice, during which the quality of a potential food source is judged, and ingestion, during which the selected food source is ingested into the digestive tract. It remains unclear whether these steps employ different mechanisms of neural perception. Here, we provide insight into the two initial steps of feeding in Drosophila larva. We find that substrate choice and ingestion are determined by independent circuits at the cellular level. First, we took 22 candidate bitter compounds and examined their influence on choice preference and ingestion behavior. Interestingly, certain bitter tastants caused different responses in choice and ingestion, suggesting distinct mechanisms of perception. We further provide evidence that certain gustatory receptor neurons (GRNs) in the external terminal organ (TO) are involved in determining choice preference, and a pair of larval pharyngeal GRNs is involved in mediating both avoidance and suppression of ingestion. Our results show that feeding behavior is coordinated by a multistep regulatory process employing relatively independent neural elements. These findings are consistent with a model in which distinct sensory pathways act as modulatory circuits controlling distinct subprograms during feeding.

Olfactory Neurons and Brain Centers Directing Oviposition Decisions in Drosophila

The sense of smell influences many behaviors, yet how odors are represented in the brain remains unclear. A major challenge to studying olfaction is the lack of methods allowing activation of specific types of olfactory neurons in an ethologically relevant setting. To address this, we developed a genetic method in Drosophila called olfactogenetics in which a narrowly tuned odorant receptor, Or56a, is ectopically expressed in different olfactory neuron types. Stimulation with geosmin (the only known Or56a ligand) in an Or56a mutant background leads to specific activation of only target olfactory neuron types. We used this approach to identify olfactory sensory neurons (OSNs) that directly guide oviposition decisions. We identify 5 OSN-types (Or71a, Or47b, Or49a, Or67b, and Or7a) that, when activated alone, suppress oviposition. Projection neurons partnering with these OSNs share a region of innervation in the lateral horn, suggesting that oviposition site selection might be encoded in this brain region.

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.

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.

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.

Reverse-Correlation Analysis of the Mechanosensation Circuit and Behavior in C. elegans Reveals Temporal and Spatial Encoding

Animals must integrate the activity of multiple mechanoreceptors to navigate complex environments. In Caenorhabditis elegans, the general roles of the mechanosensory neurons have been defined, but most studies involve end-point or single-time-point measurements, and thus lack dynamic information. Here, we formulate a set of unbiased quantitative characterizations of the mechanosensory system by using reverse correlation analysis on behavior. We use a custom tracking, selective illumination, and optogenetics platform to compare two mechanosensory systems: the gentle-touch (TRNs) and harsh-touch (PVD) circuits. This method yields characteristic linear filters that allow for the prediction of behavioral responses. The resulting filters are consistent with previous findings and further provide new insights on the dynamics and spatial encoding of the systems. Our results suggest that the tiled network of the gentle-touch neurons has better resolution for spatial encoding than the harsh-touch neurons. Additionally, linear-nonlinear models can predict behavioral responses based only on sensory neuron activity. Our results capture the overall dynamics of behavior induced by the activation of sensory neurons, providing simple transformations that quantitatively characterize these systems. Furthermore, this platform can be extended to capture the behavioral dynamics induced by any neuron or other excitable cells in the animal.

An RJMCMC-Based Method for Tracking and Resolving Collisions of Drosophila Larvae

Drosophila melanogaster is an important model organism for ongoing research in neuro- and behavioral biology. Especially the locomotion analysis has become an integral part of such studies and thus elaborated automated tracking systems have been proposed in the past. However, most of these approaches share the inability to precisely segment the contours of colliding animals leading to the absence of model and motion-related features during collisions. Here, we translate the task of tracking and resolving colliding animals into a filtering problem solvable by Markov Chain Monte Carlo methods and elaborate an adequate larva model. By comparing our method with state-of-the-art approaches, we demonstrate that our algorithm produces significantly better results in a fraction of time and facilitates the analysis of animal behavior during interaction in more detail.

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.

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.

Variance adaptation in navigational decision making

Sensory systems relay information about the world to the brain, which enacts behaviors through motor outputs. To maximize information transmission, sensory systems discard redundant information through adaptation to the mean and variance of the environment. The behavioral consequences of sensory adaptation to environmental variance have been largely unexplored. Here, we study how larval fruit flies adapt sensory-motor computations underlying navigation to changes in the variance of visual and olfactory inputs. We show that variance adaptation can be characterized by rescaling of the sensory input and that for both visual and olfactory inputs, the temporal dynamics of adaptation are consistent with optimal variance estimation. In multisensory contexts, larvae adapt independently to variance in each sense, and portions of the navigational pathway encoding mixed odor and light signals are also capable of variance adaptation. Our results suggest multiplication as a mechanism for odor-light integration.

Sensorimotor pathway controlling stopping behavior during chemotaxis in the Drosophila melanogaster larva

Sensory navigation results from coordinated transitions between distinct behavioral programs. During chemotaxis in the Drosophila melanogaster larva, the detection of positive odor gradients extends runs while negative gradients promote stops and turns. This algorithm represents a foundation for the control of sensory navigation across phyla. In the present work, we identified an olfactory descending neuron, PDM-DN, which plays a pivotal role in the organization of stops and turns in response to the detection of graded changes in odor concentrations. Artificial activation of this descending neuron induces deterministic stops followed by the initiation of turning maneuvers through head casts. Using electron microscopy, we reconstructed the main pathway that connects the PDM-DN neuron to the peripheral olfactory system and to the pre-motor circuit responsible for the actuation of forward peristalsis. Our results set the stage for a detailed mechanistic analysis of the sensorimotor conversion of graded olfactory inputs into action selection to perform goal-oriented navigation.

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.

Cider vinegar rules

Experiments in wind tunnels have shed light on the rules that govern how flies respond when they detect odors.

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.