The Nature versus Nurture debate has generally been considered from the lens of genome versus experience dichotomy and has dominated our thinking about behavioral individuality and personality traits. In contrast, the role of nonheritable noise during brain development in behavioral variation is understudied. Using the Drosophila melanogaster visual system, I will discuss our efforts to dissect how individuality in circuit wiring emerges during development, and how that helps generate individual behavioral variation.

A Research Assistant post is available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge. Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. Successful candidates will join a team based in Zoology with 16 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis).

A postdoctoral position is available immediately in the lab of Dr. Paul Shaw in the Neuroscience Department at Washington University School of Medicine in St. Louis to study the molecular and cellular bases for sleep regulation, plasticity and memory consolidation in the fruit fly Drosophila melanogaster. Successful candidates will have the opportunity to learn and apply molecular, genetic, physiological, and behavioral tools to study mechanisms by which sleep might influence plasticity. Qualified applicants are expected to hold a recent doctoral degree in the biological sciences, or in related disciplines. Prior experience in working with flies and broad understanding of genetic principles are highly preferred. Highly competitive salary and benefits are available and will commensurate with experience. Washington University School of Medicine offers a highly collaborative, top-notch training and research environment in neuroscience and the biomedical sciences. Wash U’s community is a very active and highly regarded neuroscience community, and is an excellent training environment for postdoctoral fellows. Interested candidates should email their curriculum vitae, a letter of interest outlining experience and research goals, and the names and contact information of at least three references to shawp@wustl.edu EOE Washington University is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status.

My lab will investigate neural mechanisms of motor control in Drosophila by combining neurophysiology, behavior, engineering, genetics, and quantitative analysis.

A Research Assistant post is available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge. Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. A background in neurobiology or a strong quantitative preparation (e.g. in bioinformatics/computer science) will be helpful. Successful candidates will join a team based in Zoology with 15 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis).

A Research Assistant post is available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge. Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. A background in neurobiology or a strong quantitative preparation (e.g. in bioinformatics/computer science) will be helpful. Successful candidates will join a team based in Zoology with 15 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis). Candidates will report to a team leader based in Zoology and will be mentored by an experienced post-doc. There will be opportunities to contribute to training new team members as the group expands and to general project management, as well as to participate in public engagement activities.

A Research Assistant post is available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge. Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. A background in neurobiology or a strong quantitative preparation (e.g. in bioinformatics/computer science) will be helpful. Successful candidates will join a team based in Zoology with 15 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis). Candidates will need to be highly motivated and develop a good understanding of the nature of the data and the scientific aims of the project. This will be critical to setting priorities as the project develops. Close teamwork and a collaborative spirit will be essential, but team members will have increasing opportunities for scientific independence as their expertise develops. Candidates will report to a team leader based in Zoology and will be mentored by an experienced post-doc. There will be opportunities to contribute to training new team members as the group expands and to general project management, as well as to participate in public engagement activities. Candidates will report to a team leader based in Zoology and will be mentored by an experienced post-doc. There will be opportunities to contribute to training new team members as the group expands and to general project management, as well as to participate in public engagement activities.

Two Research Assistant posts are available in the Drosophila Connectomics Group directed by Greg Jefferis and Matthias Landgraf in the Department of Zoology at the University of Cambridge. Applicants will work with electron-microscopy image data, annotate and proof-read automatically segmented reconstructions of neurons and their connectivity, develop open source tools for data analysis/processing and perform neuron morphology, graph/circuit analyses etc. to obtain biological insight. A background in neurobiology or a strong quantitative preparation (e.g. in bioinformatics/computer science) will be helpful. Successful candidates will join a team based in Zoology with 16 team members, carrying out data processing and computational analysis of neuronal reconstruction data. They will interact closely with a similar team in the US as well as experimental groups in Oxford (Scott Waddell) and Cambridge (Greg Jefferis). Candidates will need to be highly motivated and develop a good understanding of the nature of the data and the scientific aims of the project. This will be critical to setting priorities as the project develops. Close teamwork and a collaborative spirit will be essential, but team members will have increasing opportunities for scientific independence as their expertise develops. Candidates will report to a team leader based in Zoology and will be mentored by an experienced post-doc. There will be opportunities to contribute to training new team members as the group expands and to general project management, as well as to participate in public engagement activities.

A NIH-funded postdoctoral position is available in the Barnard Neurobiology Lab. Our lab is in the Department of Neuroscience & Behavior at Barnard College, a liberal arts college in Manhattan affiliated with Columbia University. Imaging facilities are available at Columbia’s Zuckerman Institute which is a few blocks away. The position is fully funded for at least four years. Ideally the position would start in the summer of 2021, but the start date is flexible. We are looking for a highly motivated and accomplished scientist interested in studying circadian timekeeping and sleep in Drosophila. The research project will involve the following techniques: - Genetic manipulation of neural networks supporting timekeeping and entrainment - Behavioral analysis of clock controlled behavioral outputs - Live-imaging and immunohistochemical analysis of clock neurons Desired qualifications: The candidate should have a Ph.D. in Biology, Neuroscience, Biochemistry, or a related field. Experience with live-imaging, immunohistochemistry, or Drosophila neurobiology is desired. However, all candidates with a track record of scientific accomplishment and a strong interest in circadian biology in any species are encouraged to apply. Please submit a CV and a cover letter explaining your research and career goals. Please also include the names and contact information for three professional references. contact: mfernand@barnard.edu Application Link: https://jobs.sciencecareers.org/job/547743/postdoctoral-research-fellow/

All animal locomotion is rhythmic,whether it is achieved through undulatory movement of the whole body or the coordination of articulated limbs. Neurobiologists have long studied locomotor circuits that produce rhythmic activity with non-rhythmic input, also called central pattern generators (CPGs). However, the cellular and microcircuit implementation of a walking CPG has not been described for any limbed animal. New comprehensive connectomes of the fruit fly ventral nerve cord (VNC) provide an opportunity to study rhythmogenic walking circuits at a synaptic scale.We use a data-driven network modeling approach to identify and characterize a putative walking CPG in the Drosophila leg motor system.

Through recent advances in microscopy, we now have an unprecedented view of the brain and body of the fruit fly Drosophila melanogaster. We now know the connectivity at single neuron resolution across the whole brain. How do we translate these new measurements into a deeper understanding of how the brain processes sensory information and produces behavior? I will describe two computational efforts to model the brain and the body of the fruit fly. First, I will describe a new modeling method which makes highly accurate predictions of neural activity in the fly visual system as measured in the living brain, using only measurements of its connectivity from a dead brain [1], joint work with Jakob Macke. Second, I will describe a whole body physics simulation of the fruit fly which can accurately reproduce its locomotion behaviors, both flight and walking [2], joint work with Google DeepMind.

We are interested in the biology of macrophages, which represent the first line of defense against pathogens. In Drosophila, the embryonic hemocytes arise from the mesoderm whereas glial cells arise from multipotent precursors in the neurogenic region. These cell types represent, respectively, the macrophages located outside and within the nervous system (similar to vertebrate microglia). Thus, despite their different origin, hemocytes and glia display common functions. In addition, both cell types express the Glide/Gcm transcription factor, which plays an evolutionarily conserved role as an anti-inflammatory factor. Moreover, embryonic hemocytes play an evolutionarily conserved and fundamental role in development. The ability to migrate and to contact different tissues/organs most likely allow macrophages to function as signaling hubs. The function of macrophages beyond the recognition of the non-self calls for revisiting the biology of these heterogeneous and plastic cells in physiological and pathological conditions across evolution.

The adult intestine is a major barrier epithelium and coordinator of multi-organ functions. Stem cells constantly repair the intestinal epithelium by adjusting their proliferation and differentiation to tissue intrinsic as well as micro- and macro-environmental signals. How these signals integrate to control intestinal and whole-body homeostasis is largely unknown. Addressing this gap in knowledge is central to an improved understanding of intestinal pathophysiology and its systemic consequences. Combining Drosophila and mammalian model systems my laboratory has discovered fundamental mechanisms driving intestinal regeneration and tumourigenesis and outlined complex inter-organ signaling regulating health and disease. During my talk, I will discuss inter-related areas of research from my lab, including:1- Interactions between the intestine and its microenvironment influencing intestinal regeneration and tumourigenesis. 2- Long-range signals from the intestine impacting whole-body in health and disease.

Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits, involving a comparison of the signals from neighboring photoreceptors over time. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Much progress has been made in recent years in the fruit fly Drosophila melanogaster by genetically targeting individual neuron types to block, activate or record from them. Our results obtained this way demonstrate that the local direction of motion is computed in two parallel ON and OFF pathways. Within each pathway, a retinotopic array of four direction-selective T4 (ON) and T5 (OFF) cells represents the four Cartesian components of local motion vectors (leftward, rightward, upward, downward). Since none of the presynaptic neurons is directionally selective, direction selectivity first emerges within T4 and T5 cells. Our present research focuses on the cellular and biophysical mechanisms by which the direction of image motion is computed in these neurons.

Programmed axon death is a widespread and completely preventable mechanism in injury and disease. Mouse and Drosophila studies define a molecular pathway involving activation of SARM1 NA Dase and its prevention by NAD synthesising enzyme NMNAT2 . Loss of axonal NMNAT2 causes its substrate, NMN , to accumulate and activate SARM1 , driving loss of NAD and changes in ATP , ROS and calcium. Animal models caused by genetic mutation, toxins, viruses or metabolic defects can be alleviated by blocking programmed axon death, for example models of CMT1B , chemotherapy-induced peripheral neuropathy (CIPN), rabies and diabetic peripheral neuropathy (DPN). The perinatal lethality of NMNAT2 null mice is completely rescued, restoring a normal, healthy lifespan. Animal models lack the genetic and environmental diversity present in human populations and this is problematic for modelling gene-environment combinations, for example in CIPN and DPN , and identifying rare, pathogenic mutations. Instead, by testing human gene variants in WGS datasets for loss- and gain-of-function, we identified enrichment of rare SARM1 gain-of-function variants in sporadic ALS , despite previous negative findings in SOD1 transgenic mice. We have shown in mice that heterozygous SARM1 loss-of-function is protective from a range of axonal stresses and that naturally-occurring SARM1 loss-of-function alleles are present in human populations. This enables new approaches to identify disorders where blocking SARM1 may be therapeutically useful, and the existence of two dominant negative human variants in healthy adults is some of the best evidence available that drugs blocking SARM1 are likely to be safe. Further loss- and gain-of-function variants in SARM1 and NMNAT2 are being identified and used to extend and strengthen the evidence of association with neurological disorders. We aim to identify diseases, and specific patients, in whom SARM1 -blocking drugs are most likely to be effective.

Gut-derived signals regulate metabolism, appetite, and behaviors important for mental health. We have performed a large-scale multidimensional screen to identify gut hormones and nutrient-sensing mechanisms in the intestine that regulate metabolism and behavior in the fruit fly Drosophila. We identified several gut hormones that affect fecundity, stress responses, metabolism, feeding, and sleep behaviors, many of which seem to act sex-specifically. We show that in response to nutrient intake, the enteroendocrine cells (EECs) of the adult Drosophila midgut release hormones that act via inter-organ relays to coordinate metabolism and feeding decisions. These findings suggest that crosstalk between the gut and other tissues regulates food choice according to metabolic needs, providing insight into how that intestine processes nutritional inputs and into the gut-derived signals that relay information regulating nutrient-specific hungers to maintain metabolic homeostasis.

Drosophila olfactory sensory hairs ("sensilla") typically house two olfactory receptor neurons (ORNs) which can laterally inhibit each other via electrical ("ephaptic") coupling. ORN pairing is highly stereotyped and genetically determined. Thus, olfactory signals arriving in the Antennal Lobe (AL) have been pre-processed by a fixed and shallow network at the periphery. To uncover the functional significance of this organization, we developed a nonlinear phenomenological model of asymmetrically coupled ORNs responding to odor mixture stimuli. We derived an analytical solution to the ORNs’ dynamics, which shows that the peripheral network can extract the valence of specific odor mixtures via transient amplification. Our model predicts that for efficient read-out of the amplified valence signal there must exist specific patterns of downstream connectivity that reflect the organization at the periphery. Analysis of AL→Lateral Horn (LH) fly connectomic data reveals evidence directly supporting this prediction. We further studied the effect of ephaptic coupling on olfactory processing in the AL→Mushroom Body (MB) pathway. We show that stereotyped ephaptic interactions between ORNs lead to a clustered odor representation of glomerular responses. Such clustering in the AL is an essential assumption of theoretical studies on odor recognition in the MB. Together our work shows that preprocessing of olfactory stimuli by a fixed and shallow network increases sensitivity to specific odor mixtures, and aids in the learning of novel olfactory stimuli. Work led by Palka Puri, in collaboration with Chih-Ying Su and Shiuan-Tze Wu.

Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Our results obtained in the fruit fly Drosophila demonstrate that the local direction of motion is computed in two parallel ON and OFF pathways. Within each pathway, a retinotopic array of four direction-selective T4 (ON) and T5 (OFF) cells represents the four Cartesian components of local motion vectors (leftward, rightward, upward, downward). Since none of the presynaptic neurons is directionally selective, direction selectivity first emerges within T4 and T5 cells. Our present research focuses on the cellular and biophysical mechanisms by which the direction of image motion is computed in these neurons.

It is critical for all animals to make appropriate, but also flexible, foraging decisions, especially when facing starvation. Sensing olfactory information is essential to evaluate food quality before ingestion. Previously, we found that <i>Drosophila</i> larvae switch their response to certain odors from aversion to attraction when food deprived. The neural mechanism underlying this switch in behavior involves serotonergic modulation and reconfiguration of odor processing in the early olfactory sensory system. We now investigate if a change in hunger state also influences other behavioral decisions. Since it had been shown that fly larvae can perform cannibalism, we investigate the effect of food deprivation on feeding on dead conspecifics. We find that fed fly larvae rarely use dead conspecifics as a food source. However, food deprivation largely enhances this behavior. We will now also investigate the underlying neural mechanisms that mediate this enhancement and compare it to the already described mechanism for a switch in olfactory choice behavior. Generally, this flexibility in foraging behavior enables the larva to explore a broader range of stimuli and to expand their feeding choices to overcome starvation.

Chronic exercise is a powerful intervention that lowers the incidence of most age-related diseases while promoting healthy metabolism in humans. However, illness, injury or age prevent many humans from consistently exercising. Thus, identification of molecular targets that can mimic the benefits of exercise would be a valuable tool to improve health outcomes of humans with neurodegenerative or mitochondrial diseases, or those with enforced sedentary lifestyles. Using a novel exercise platform for Drosophila, we have identified octopaminergic neurons as a key subset of neurons that are critical for the exercise response, and shown that periodic daily stimulation of these neurons can induce a systemic exercise response in sedentary flies. Octopamine is released into circulation where it signals through various octopamine receptors in target tissues and induces gene expression changes similar to exercise. In particular, we have identified several key molecules that respond to octopamine in skeletal muscle, including the mTOR modulator Sestrin, the PGC-1α homolog Spargel, and the FNDC5/Irisin homolog Iditarod. We are currently testing these molecules as potential therapies for multiple diseases that reduce mobility, including the PolyQ disease SCA2 and the mitochondrial disease Barth syndrome.

Efficient navigation requires animals to track their position, velocity and heading direction (HD). Some animals’ behavior suggests that they also track uncertainties about these navigational variables, and make strategic use of these uncertainties, in line with a Bayesian computation. Ring-attractor networks have been proposed to estimate and track these navigational variables, for instance in the HD system of the fruit fly Drosophila. However, such networks are not designed to incorporate a notion of uncertainty, and therefore seem unsuited to implement dynamic Bayesian inference. Here, we close this gap by showing that specifically tuned ring-attractor networks can track both a HD estimate and its associated uncertainty, thereby approximating a circular Kalman filter. We identified the network motifs required to integrate angular velocity observations, e.g., through self-initiated turns, and absolute HD observations, e.g., visual landmark inputs, according to their respective reliabilities, and show that these network motifs are present in the connectome of the Drosophila HD system. Specifically, our network encodes uncertainty in the amplitude of a localized bump of neural activity, thereby generalizing standard ring attractor models. In contrast to such standard attractors, however, proper Bayesian inference requires the network dynamics to operate in a regime away from the attractor state. More generally, we show that near-Bayesian integration is inherent in generic ring attractor networks, and that their amplitude dynamics can account for close-to-optimal reliability weighting of external evidence for a wide range of network parameters. This only holds, however, if their connection strengths allow the network to sufficiently deviate from the attractor state. Overall, our work offers a novel interpretation of ring attractor networks as implementing dynamic Bayesian integrators. We further provide a principled theoretical foundation for the suggestion that the Drosophila HD system may implement Bayesian HD tracking via ring attractor dynamics.

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

Fly Escape Behaviors: Flexible and Modular We have identified a set of escape maneuvers performed by a fly when confronted by a looming object. These escape responses can be divided into distinct behavioral modules. Some of the modules are very stereotyped, as when the fly rapidly extends its middle legs to jump off the ground. Other modules are more complex and require the fly to combine information about both the location of the threat and its own body posture. In response to an approaching object, a fly chooses some varying subset of these behaviors to perform. We would like to understand the neural process by which a fly chooses when to perform a given escape behavior. Beyond an appealing set of behaviors, this system has two other distinct advantages for probing neural circuitry. First, the fly will perform escape behaviors even when tethered such that its head is fixed and neural activity can be imaged or monitored using electrophysiology. Second, using Drosophila as an experimental animal makes available a rich suite of genetic tools to activate, silence, or image small numbers of cells potentially involved in the behaviors. Neural Circuits for Escape Until recently, visually induced escape responses have been considered a hardwired reflex in Drosophila. White-eyed flies with deficient visual pigment will perform a stereotyped middle-leg jump in response to a light-off stimulus, and this reflexive response is known to be coordinated by the well-studied giant fiber (GF) pathway. The GFs are a pair of electrically connected, large-diameter interneurons that traverse the cervical connective. A single GF spike results in a stereotyped pattern of muscle potentials on both sides of the body that extends the fly's middle pair of legs and starts the flight motor. Recently, we have found that a fly escaping a looming object displays many more behaviors than just leg extension. Most of these behaviors could not possibly be coordinated by the known anatomy of the GF pathway. Response to a looming threat thus appears to involve activation of numerous different neural pathways, which the fly may decide if and when to employ. Our goal is to identify the descending pathways involved in coordinating these escape behaviors as well as the central brain circuits, if any, that govern their activation. Automated Single-Fly Screening We have developed a new kind of high-throughput genetic screen to automatically capture fly escape sequences and quantify individual behaviors. We use this system to perform a high-throughput genetic silencing screen to identify cell types of interest. Automation permits analysis at the level of individual fly movements, while retaining the capacity to screen through thousands of GAL4 promoter lines. Single-fly behavioral analysis is essential to detect more subtle changes in behavior during the silencing screen, and thus to identify more specific components of the contributing circuits than previously possible when screening populations of flies. Our goal is to identify candidate neurons involved in coordination and choice of escape behaviors. Measuring Neural Activity During Behavior We use whole-cell patch-clamp electrophysiology to determine the functional roles of any identified candidate neurons. Flies perform escape behaviors even when their head and thorax are immobilized for physiological recording. This allows us to link a neuron's responses directly to an action.

Early in development the nervous system is constructed with far too many neurons that make an excessive number of synaptic connections.  Later, a wave of neuronal remodeling radically reshapes nervous system wiring and cell numbers through the selective elimination of excess synapses, axons and dendrites, and even whole neurons.  This remodeling is widespread across the nervous system, extensive in terms of how much individual brain regions can change (e.g. in some cases 50% of neurons integrated into a brain circuit are eliminated), and thought to be essential for optimizing nervous system function.  Perturbations of neuronal remodeling are thought to underlie devastating neurodevelopmental disorders including autism spectrum disorder, schizophrenia, and epilepsy.  This seminar will discuss our efforts to use the relatively simple nervous system of Drosophila to understand the mechanistic basis by which cells, or parts of cells, are specified for removal and eliminated from the nervous system.

Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does genetically encoded brain wiring deal with this apparent contradiction? Brain wiring is a developmental growth process that is not only characterized by precision, but also flexibility and robustness. As in any other growth process, cellular interactions are restricted in space and time. Correspondingly, molecular and cellular interactions are restricted to those that 'get to see' each other during development. This seminar will explore the question how neurons decide when and where to make synapses using the Drosophila visual system as a model. New findings reveal that pattern formation during growth and the kinetics of live neuronal interactions restrict synapse formation and partner choice for neurons that are not otherwise prevented from making incorrect synapses in this system. For example, cell biological mechanisms like autophagy as well as developmental temperature restrict inappropriate partner choice through a process of kinetic exclusion that critically contributes to wiring specificity. The seminar will explore these and other neuronal strategies when and where to make synapses during developmental growth that contribute to precise, flexible and robust outcomes in brain wiring.

I am working on color vision in Drosophila, identifying behaviors that involve color vision and understanding the neural circuits supporting them (Longden 2016). I have a long-term interest in understanding how neural computations operate reliably under changing circumstances, be they external changes in the sensory context, or internal changes of state such as hunger and locomotion. On internal state-modulation of sensory processing, I have shown how hunger alters visual motion processing in blowflies (Longden et al. 2014), and identified a role for octopamine in modulating motion vision during locomotion (Longden and Krapp 2009, 2010). On responses to external cues, I have shown how one kind of uncertainty in the motion of the visual scene is resolved by the fly (Saleem, Longden et al. 2012), and I have identified novel cells for processing translation-induced optic flow (Longden et al. 2017). I like working with colleagues who use different model systems, to get at principles of neural operation that might apply in many species (Ding et al. 2016, Dyakova et al. 2015). I like work motivated by computational principles - my background is computational neuroscience, with a PhD on models of memory formation in the hippocampus (Longden and Willshaw, 2007).

Neuroscientists have many questions about connectomes that revolve around the ability to compare networks. For example, comparing connectomes could help explain how neural wiring is related to individual differences, genetics, disease, development, or learning. One such question is that of bilateral symmetry: are the left and right sides of a connectome the same? Here, we investigate the bilateral symmetry of a recently presented connectome of an insect brain, the Drosophila larva. We approach this question from the perspective of two-sample testing for networks. First, we show how this question of “sameness” can be framed as a variety of different statistical hypotheses, each with different assumptions. Then, we describe test procedures for each of these hypotheses. We show how these different test procedures perform on both the observed connectome as well as a suite of synthetic perturbations to the connectome. We also point out that these tests require careful attention to parameter alignment and differences in network density in order to provide biologically meaningful results. Taken together, these results provide the first statistical characterization of bilateral symmetry for an entire brain at the single-neuron level, while also giving practical recommendations for future comparisons of connectome networks.

Neuronal computations are matched to optimally encode the sensory information that is available and relevant for the animal. However, the physical distribution of sensory information is often shaped by the animal’s own behavior. One prominent example is the encoding of optic flow fields that are generated during self-motion of the animal and will therefore depend on the type of locomotion. How evolution has matched computational resources to the behavioral constraints of an animal is not known. Here we use in vivo two photon imaging to record from a population of >3.500 local-direction selective cells. Our data show that the local direction-selective T4/T5 neurons in Drosophila form a population code that is matched to represent optic flow fields generated during translational and rotational self-motion of the fly. This coding principle for optic flow is reminiscent to the population code of local direction-selective ganglion cells in the mouse retina, where four direction-selective ganglion cells encode four different axes of self-motion encountered during walking (Sabbah et al., 2017). However, in flies we find six different subtypes of T4 and T5 cells that, at the population level, represent six axes of self-motion of the fly. The four uniformly tuned T4/T5 subtypes described previously represent a local snapshot (Maisak et al. 2013). The encoding of six types of optic flow in the fly as compared to four types of optic flow in mice might be matched to the high degrees of freedom encountered during flight. Thus, a population code for optic flow appears to be a general coding principle of visual systems, resulting from convergent evolution, but matching the individual ethological constraints of the animal.

Animals exhibit extraordinary variation in their behavior, yet little is known about the neural mechanisms that generate this diversity. My lab has been taking advantage of the rapid diversification of male courtship behaviors in Drosophila to glean insight into how evolution shapes the nervous system to generate species-specific behaviors. By translating neurogenetic tools from D. melanogaster to closely related Drosophila species, we have begun to directly compare the homologous neural circuits and pinpoint sites of adaptive change. Across species, P1 neurons serve as a conserved node in regulating male courtship: these neurons are selectively activated by the sensory cues indicative of an appropriate mate and their activation triggers enduring courtship displays. We have been examining how different sensory pathways converge onto P1 neurons to regulate a male’s state of arousal, honing his pursuit of a prospective partner. Moreover, by performing cross-species comparison of these circuits, we have begun to gain insight into how reweighting of sensory inputs to P1 neurons underlies species-specific mate recognition. Our results suggest how variation at flexible nodes within the nervous system can serve as a substrate for behavioral evolution, shedding light on the types of changes that are possible and preferable within brain circuits.

The ability to keep track of one’s location in space is a critical behavior for animals navigating to and from a salient location, and its computational basis is now beginning to be unraveled. Here, we tracked flies in a ring-shaped channel as they executed bouts of search triggered by optogenetic activation of sugar receptors. Unlike experiments in open field arenas, which produce highly tortuous search trajectories, our geometrically constrained paradigm enabled us to monitor flies’ decisions to move toward or away from the fictive food. Our results suggest that flies use path integration to remember the location of a food site even after it has disappeared, and flies can remember the location of a former food site even after walking around the arena one or more times. To determine the behavioral algorithms underlying Drosophila search, we developed multiple state transition models and found that flies likely accomplish path integration by combining odometry and compass navigation to keep track of their position relative to the fictive food. Our results indicate that whereas flies re-zero their path integrator at food when only one feeding site is present, they adjust their path integrator to a central location between sites when experiencing food at two or more locations. Together, this work provides a simple experimental paradigm and theoretical framework to advance investigations of the neural basis of path integration.

The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising and this typically evokes prediction error signatures in animal brains. In humans such mismatched expectations are often associated with an emotional response as well. Appropriate emotional responses are understood to be important for memory consolidation, suggesting that valence cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolishing error detection and surprise entirely is probably also maladaptive, as this might undermine the very mechanism that brains use to become better prediction machines. This paradoxical view of brain functions as an ongoing tug-of-war between prediction and surprise suggests a compelling new way to study and understand the evolution of consciousness in animals. I will present approaches to studying attention and prediction in the tiny brain of the fruit fly, Drosophila melanogaster. I will discuss how an ‘active’ sleep stage (termed rapid eye movement – REM – sleep in mammals) may have evolved in the first animal brains as a mechanism for optimizing prediction in motile creatures confronted with constantly changing environments. A role for REM sleep in emotional regulation could thus be better understood as an ancient sleep function that evolved alongside selective attention to maintain an adaptive balance between prediction and surprise. This view of active sleep has some interesting implications for the evolution of subjective awareness and consciousness.

We seek to determine how circadian rhythms and sleep are integrated with physiological processes to provide optimal fitness and health. Using initially a Drosophila model, and more recently also mammalian models, we have found that aspects of the blood brain barrier (BBB) are controlled by the circadian clock. BBB properties are also influenced by sleep:wake state in Drosophila, and, in fact, appear to be contribute to functions of sleep. This and other work, which implicates sleep in the regulation of metabolic processes, is providing insights into sleep function

How does the brain decode the meaning of sound signals, such as music and courtship songs? We believe that the fruit fly Drosophila melanogaster is an ideal model for answering this question, as it offers a comprehensive range of tools and assays which allow us to dissect the mechanisms underlying sound perception and evaluation in the brain. During the courtship behavior, male fruit flies emit “courtship songs” by vibrating their wings. Interestingly, the fly song has a species-specific rhythm, which indeed increases the female’s receptivity for copulation as well as male’s courtship behavior itself. How song signals, especially the species-specific sound rhythm, are evaluated in the fly brain? To tackle this question, we are exploring the features of the fly auditory system systematically. In this lecture, I will talk about our recent findings on the neural basis for song evaluation in fruit flies.

Animals produce behavior by responding to a mixture of cues that arise both externally (sensory) and internally (neural dynamics and states). These cues are continuously produced and can be combined in different ways depending on the needs of the animal. However, the integration of these external and internal cues remains difficult to understand in natural behaviors. To address this gap, we have developed an unsupervised method to identify internal states from behavioral data, and have applied it to the study of a dynamic social interaction. During courtship, Drosophila melanogaster males pattern their songs using cues from their partner. This sensory-driven behavior dynamically modulates courtship directed at their partner. We use our unsupervised method to identify how the animal integrates sensory information into distinct underlying states. We then use this to identify the role of courtship neurons in either integrating incoming information or directing the production of the song, roles that were previously hidden. Our results reveal how animals compose behavior from previously unidentified internal states, a necessary step for quantitative descriptions of animal behavior that link environmental cues, internal needs, neuronal activity, and motor outputs.

The regions of the insect brain devoted to spatial navigation are beautifully orderly, with a remarkably precise pattern of synaptic connections. Thus, we can learn much about the neural mechanisms of spatial navigation by targeting identifiable neurons in these networks for in vivo patch clamp recording and calcium imaging. Our lab has recently discovered that the "compass system" in the Drosophila brain is anchored to not only visual landmarks, but also the prevailing wind direction. Moreover, we found that the compass system can re-learn the relationship between these external sensory cues and internal self-motion cues, via rapid associative synaptic plasticity. Postsynaptic to compass neurons, we found neurons that conjunctively encode heading direction and body-centric translational velocity. We then showed how this representation of travel velocity is transformed from body- to world-centric coordinates at the subsequent layer of the network, two synapses downstream from compass neurons. By integrating this world-centric vector-velocity representation over time, it should be possible for the brain to form a stored representation of the body's path through the environment.

We seek to understand the control of behavior – by animals, their brains, and their neurons. Reiser and his team are focused on the fly visual system, using modern methods from the Drosophila toolkit to understand how visual pathways are involved in specific behaviors. Due to the recent connectomics explosion, they now study the brain-wide networks organizing visual information for behavior control. The team combines explorations of visually guided behaviors with functional investigations of specific cell types throughout the fly brain. The Reiser lab actively develops and disseminates new methods and instruments enabling increasingly precise quantification of animal behavior.

Claude Desplan is a Silver Professor of Biology and Neuroscience at NYU. He was born in Algeria and was trained at Ecole Normale Supérieure St. Cloud, France. He received his DSc at INSERM in Paris in 1983 and joined Pat O’Farrell at UCSF as a postdoc. There he demonstrated that the homeodomain, a conserved signature of many developmental genes, is a DNA binding motif. Currently, Dr. Desplan works at NYU where he investigates the generation of neural diversity using the Drosophila visual system.

Drosophila can learn to associate odours with reward or punishment and the resulting memories direct odour-specific approach or avoidance behaviours. Recent progress has revealed a straightforward model for learning in which reinforcing dopaminergic neurons assign valence to odour representations in the neural ensemble of the mushroom bodies. Dopamine directed synaptic depression alters the route of odour-driven activity through the mushroom body output network. This circuit configuration and influence of internal state guide the expression of appropriate behaviour. Importantly, learned behaviour is flexible and can be updated as the fly accumulates additional experience. Our latest studies demonstrate that well-informed behaviour is guided by combining parallel conflicting and complementary memories of opposite valence.

The development and maintenance of many tissues are fueled by stem cells. Many studies have addressed how intrinsic factors and local signals from neighboring niche cells maintain stem cell identity and proliferative potential. In contrast, it is poorly understood how stem cell activity is controlled by systemic, tissue-extrinsic signals in response to environmental cues and changes in physiological status. Our laboratory has been focusing on female germline stem cells (fGSCs) in the fruit fly Drosophila melanogaster as a model system and studying neuroendocrine control of fGSC increase. The increase of fGSCs is induced by mating stimuli. We have previously reported that mating-induced fGSC increase is regulated by the ovarian steroid hormone and the enteroendocrine peptide hormone [Ameku & Niwa, PLOS Genetics 2016; Ameku et al. PLOS Biology 2018]. In this presentation, we report our recent finding showing a neuronal mechanism of mating-induced fGSC increase. We first found that the ovarian somatic cell-specific RNAi for Oamb, a G protein-coupled receptor for the neurotransmitter octopamine, failed to induce fGSC proliferation after mating. Both ex vivo and in vivo experiments revealed that octopamine and Oamb positively regulated mating-induced fGSC increase via intracellular Ca 2+ signaling. We also found that a small subset of octopaminergic neurons directly projected to the ovary, and neuronal activity of these neurons was required for mating-induced fGSC increase. This study provides a mechanism describing how the neuronal system controls stem cell behavior through stem cell niche signaling [Yoshinari et al. eLife 2020]. Here I will also present our recent data showing how the neuroendocrine system couples fGSC behavior to multiple environmental cues, such as mating and nutrition.

My research at the interface of neurobiology, biomechanics, and behavior seeks to understand how the timing precision of sensory input structures locomotor output. My lab studies the flight behavior of the fruit fly, Drosophila melanogaster, combining powerful genetic tools available for labeling and manipulating neural circuits with cutting-edge imaging in awake, behaving animals. This work has the potential to fundamentally reshape understanding of the evolution of insect flight, as well as highlight the tremendous importance of timing in the context of locomotion. Timing is crucial to the nervous system. The ability to rapidly detect and process subtle disturbances in the environment determines whether an animal can attain its next meal or successfully navigate complex, unpredictable terrain. While previous work on various animals has made tremendous strides uncovering the specialized neural circuits used to resolve timing differences with sub-microsecond resolution, it has focused on the detection of timing differences in sensory systems. Understanding of how the timing of motor output is structured by precise sensory input remains poor. My research focuses on an organ unique to fruit flies, called the haltere, that serves as a bridge for detecting and acting on subtle timing differences, helping flies execute rapid maneuvers. Understanding how this relatively simple insect canperform such impressive aerial feats demands an integrative approach that combines physics, muscle mechanics, neuroscience, and behavior. This unique, powerful approach will reveal the general principles that govern sensorimotor processing.

Behavior varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical underpinnings of this individuality, though previous work implicates sensory periphery. Drosophila olfaction presents an ideal model to study the biological basis of behavioral individuality, because while the neural circuit underlying olfactory behavior is well-described and highly stereotyped, persistent idiosyncrasy in behavior, neural coding, and neural wiring have also been described. Projection neurons (PNs), which relay odor signals sensed by olfactory receptor neurons (ORNs) to deeper brain structures, exhibit variable calcium responses to identical odor stimuli across individuals, but how these idiosyncrasies relate to individual behavioral responses remains unknown. Here, using paired behavior and two-photon imaging measurements, we show that idiosyncratic calcium dynamics in both ORNs and PNs predict individual preferences for an aversive monomolecular odorant versus air, suggesting that variation at the periphery of the olfactory system determines individual preference for an odor’s presence. In contrast, PN, but not ORN, calcium responses predict individual preferences in a two-odor choice assay. Furthermore, paired behavior and immunohistochemistry measurements reveal that variation in ORN presynaptic density also predicts two-odor preference, suggesting this site is a locus of individuality where microscale circuit variation gives rise to idiosyncrasy in behavior. Our results demonstrate how a neural circuit may vary functionally and structurally to produce variable behavior among individuals.

To function properly, the nervous system consumes vast amounts of energy, which is mostly provided by carbohydrate metabolism. Neurons are very sensitive to changes in the extracellular fluid surrounding them, which necessitated shielding of the nervous system from fluctuating solute concentrations in circulation. This is achieved by the blood-brain barrier (BBB) that prevents paracellular diffusion of solutes into the nervous system. This in turn also means that all nutrients that are needed e.g. for sufficient energy supply need to be transported over the BBB. We use Drosophila as a model system to better understand the metabolic homeostasis in the central nervous system. Glial cells play essential roles in both nutrient uptake and neural energy metabolism. Carbohydrate transport over the glial BBB is well-regulated and can be adapted to changes in carbohydrate availability. Furthermore, Drosophila glial cell are highly glycolytic cells that support the rather oxidative metabolism of neurons. Upon perturbations of carbohydrate metabolism, the glial cells prove to be metabolically very flexible and able to adapt to changing circumstances. I will summarize what we know about carbohydrate transport at the Drosophila BBB and about the metabolic coupling between neurons and glial cells. Our data shows that many basic features of neural metabolism are well conserved between the fly and mammals.

Internal organs constantly exchange signals, and can respond with striking anatomical and functional transformations, even in fully developed organisms. We are exploring the mechanisms that drive and sustain such plasticity using the intestine and its neurons as experimental systems. I will present some of our recent work, which has characterised the enteric nervous system of Drosophila, and has explored its physiological plasticity as well as that of the intestine itself. This work has uncovered unexpected sexual dimorphisms, intestinal contributions to reproductive success and metabolic crosstalk between the gut and the brain. Interestingly, this crosstalk appears to be spatially constrained by the three dimensional arrangement of viscera, revealing a previously unrecognised layer of inter-organ signalling regulation. I may also describe our attempts to explore how broadly applicable our findings may be using mammalian systems.

In the last decades, the post-transcriptional control of gene expression has become an area of intense investigation, delineating a complex scenario where several factors (e.g. RNA-binding proteins, coding and non-coding RNAs) orchestrate the fate of a given transcript. An intriguing hypothesis suggests that loss of RNA homeostasis is a central feature of many pathological states, including eye diseases. Since the elav (embryonic lethal, abnormal visual system) gene discovery in the Drosophila melanogaster, the mammalian ELAV-like family has confirmed its leading role in controlling the RNA metabolism (from splicing to translation) of genes with a key function in many physio-pathological contexts. Some relevant findings suggest the involvement of the HuR/ELAV-like1 member and its potential as a therapeutic target in age-related ocular pathologies.

Animals exhibit extraordinary variation in their behaviour, yet little is known about the neural mechanisms that generate this diversity. My lab has been taking advantage of the rapid diversification of male courtship behaviours in Drosophila to gain insight into how evolution shapes the nervous system to generate species-specific behaviours. By translating neurogenetic tools from D. melanogaster to closely related Drosophila species, we have begun to directly compare the homologous neural circuits and pinpoint sites of adaptive change. Across species, P1 interneurons serve as a conserved and key node in regulating male courtship: these neurons are selectively activated by the sensory cues carried by an appropriate mate and their activation triggers enduring courtship displays. We have been examining how different sensory pathways converge onto P1 neurons to regulate a male’s state of arousal, honing his pursuit of a prospective partner. Moreover, by performing cross-species comparison of these circuits, we have begun to gain insight into how reweighting of sensory inputs to P1 neurons underlies species-specific mate recognition. Our results suggest how variation at flexible nodes within the nervous system can serve as a substrate for behavioural evolution, shedding light on the types of changes that are possible and preferable within brain circuits.

behaviour varies even among genetically identical animals raised in the same environment. However, little is known about the circuit or anatomical underpinnings of this individuality, though previous work implicates sensory periphery. Drosophila olfaction presents an ideal model to study the biological basis of behavioural individuality, because while the neural circuit underlying olfactory behaviour is well-described and highly stereotyped, persistent idiosyncrasy in behaviour, neural coding, and neural wiring have also been described. Projection neurons (PNs), which relay odor signals sensed by olfactory receptor neurons (ORNs) to deeper brain structures, exhibit variable calcium responses to identical odor stimuli across individuals, but how these idiosyncrasies relate to individual behavioural responses remains unknown. Here, using paired behaviour and two-photon imaging measurements, we show that idiosyncratic calcium dynamics in both ORNs and PNs predict individual preferences for an aversive monomolecular odorant versus air, suggesting that variation at the periphery of the olfactory system determines individual preference for an odor’s presence. In contrast, PN, but not ORN, calcium responses predict individual preferences in a two-odor choice assay. Furthermore, paired behaviour and immunohistochemistry measurements reveal that variation in ORN presynaptic density also predicts two-odor preference, suggesting this site is a locus of individuality where microscale circuit variation gives rise to idiosyncrasy in behaviour. Our results demonstrate how a neural circuit may vary functionally and structurally to produce variable behaviour among individuals.