Insect
insect
Brain circuits for spatial navigation
In this webinar on spatial navigation circuits, three researchers—Ann Hermundstad, Ila Fiete, and Barbara Webb—discussed how diverse species solve navigation problems using specialized yet evolutionarily conserved brain structures. Hermundstad illustrated the fruit fly’s central complex, focusing on how hardwired circuit motifs (e.g., sinusoidal steering curves) enable rapid, flexible learning of goal-directed navigation. This framework combines internal heading representations with modifiable goal signals, leveraging activity-dependent plasticity to adapt to new environments. Fiete explored the mammalian head-direction system, demonstrating how population recordings reveal a one-dimensional ring attractor underlying continuous integration of angular velocity. She showed that key theoretical predictions—low-dimensional manifold structure, isometry, uniform stability—are experimentally validated, underscoring parallels to insect circuits. Finally, Webb described honeybee navigation, featuring path integration, vector memories, route optimization, and the famous waggle dance. She proposed that allocentric velocity signals and vector manipulation within the central complex can encode and transmit distances and directions, enabling both sophisticated foraging and inter-bee communication via dance-based cues.
Spatial matching tasks for insect minds: relational similarity in bumblebees
Understanding what makes human unique is a fundamental research drive for comparative psychologists. Cognitive abilities such as theory of mind, cooperation or mental time travel have been considered uniquely human. Despite empirical evidence showing that animals other than humans are able (to some extent) of these cognitive achievements, findings are still heavily contested. In this context, being able to abstract relations of similarity has also been considered one of the hallmarks of human cognition. While previous research has shown that other animals (e.g., primates) can attend to relational similarity, less is known about what invertebrates can do. In this talk, I will present a series of spatial matching tasks that previously were used with children and great apes and that I adapted for use with wild-caught bumblebees. The findings from these studies suggest striking similarities between vertebrates and invertebrates in their abilities to attend to relational similarity.
Central place foraging: how insects anchor spatial information
Many insect species maintain a nest around which their foraging behaviour is centered, and can use path integration to maintain an accurate estimate of their distance and direction (a vector) to their nest. Some species, such as bees and ants, can also store the vector information for multiple salient locations in the world, such as food sources, in a common coordinate system. They can also use remembered views of the terrain around salient locations or along travelled routes to guide return. Recent modelling of these abilities shows convergence on a small set of algorithms and assumptions that appear sufficient to account for a wide range of behavioural data, and which can be mapped to specific insect brain circuits. Notably, this does not include any significant topological knowledge: the insect does not need to recover the information (implicit in their vector memory) about the relationships between salient places; nor to maintain any connectedness or ordering information between view memories; nor to form any associations between views and vectors. However, there remains some experimental evidence not fully explained by these algorithms that may point towards the existence of a more complex or integrated mental map in insects.
Neural circuits for vector processing in the insect brain
Several species of insects have been observed to perform accurate path integration, constantly updating a vector memory of their location relative to a starting position, which they can use to take a direct return path. Foraging insects such as bees and ants are also able to store and recall the vectors to return to food locations, and to take novel shortcuts between these locations. Other insects, such as dung beetles, are observed to integrate multimodal directional cues in a manner well described by vector addition. All these processes appear to be functions of the Central Complex, a highly conserved and strongly structured circuit in the insect brain. Modelling this circuit, at the single neuron level, suggests it has general capabilities for vector encoding, vector memory, vector addition and vector rotation that can support a wide range of directed and navigational behaviours.
Setting network states via the dynamics of action potential generation
To understand neural computation and the dynamics in the brain, we usually focus on the connectivity among neurons. In contrast, the properties of single neurons are often thought to be negligible, at least as far as the activity of networks is concerned. In this talk, I will contradict this notion and demonstrate how the biophysics of action-potential generation can have a decisive impact on network behaviour. Our recent theoretical work shows that, among regularly firing neurons, the somewhat unattended homoclinic type (characterized by a spike onset via a saddle homoclinic orbit bifurcation) particularly stands out: First, spikes of this type foster specific network states - synchronization in inhibitory and splayed-out/frustrated states in excitatory networks. Second, homoclinic spikes can easily be induced by changes in a variety of physiological parameters (like temperature, extracellular potassium, or dendritic morphology). As a consequence, such parameter changes can even induce switches in network states, solely based on a modification of cellular voltage dynamics. I will provide first experimental evidence and discuss functional consequences of homoclinic spikes for the design of efficient pattern-generating motor circuits in insects as well as for mammalian pathologies like febrile seizures. Our analysis predicts an interesting role for homoclinic action potentials as an integral part of brain dynamics in both health and disease.
What the fly’s eye tells the fly’s brain…and beyond
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.
Social immunity in ants: disease defense of the colony
Social insects fight disease as a collective. Their colonies are protected against disease by the combination of the individual immune defenses of all colony members and their jointly performed nest- and colony-hygiene. This social immunity is achieved by cooperative behaviors to reduce pathogen load of the colony and to prevent transmission along the social interaction networks of colony members. Individual and social immunity interact: performance of sanitary care can affect future disease susceptibility, yet also vice versa, individuals differing in susceptibility adjust their sanitary care performance to their individual risk of infection. I present the integrated approach we use to understand how colony protection arises from the individual and collective actions of colony members and how it affects pathogen communities and hence disease ecology.
Sensing in Insect Wings
Ali Weber (University of Washington, USA) uses the the hawkmoth as a model system, to investigate how information from a small number of mechanoreceptors on the wings are used in flight control. She employs a combination of experimental and computational techniques to study how these sensors respond during flight and how one might optimally array a set of these sensors to best provide feedback during flight.
Dynamic spatial processing in insect vision
How does the visual system of insects function in vastly different light intensities, process separate parts of the visual field in parallel, and cope with eye sizes that differ between individuals? This talk will give you the answers we receive from our unique(ly adorable) model system: hawkmoths.
A Flash of Darkness within Dusk: Crossover inhibition in the mouse retina
To survive in the wild small rodents evolved specialized retinas. To escape predators, looming shadows need to be detected with speed and precision. To evade starvation, small seeds, grass, nuts and insects need to also be detected quickly. Some of these succulent seeds and insects may be camouflaged offering only low contrast targets.Moreover, these challenging tasks need to be accomplished continuously at dusk, night, dawn and daytime. Crossover inhibition is thought to be involved in enhancing contrast detectionin the microcircuits of the inner plexiform layer of the mammalian retina. The AII amacrine cells are narrow field cells that play a key role in crossover inhibition. Our lab studies the synaptic physiology that regulates glycine release from AII amacrine cellsin mouse retina. These interneurons receive excitation from rod and conebipolar cells and transmit excitation to ON-type bipolar cell terminals via gap junctions. They also transmit inhibition via multiple glycinergic synapses onto OFF bipolar cell terminals.AII amacrine cells are thus a central hub of synaptic information processing that cross links the ON and the OFF pathways. What are the functions of crossover inhibition? How does it enhance contrast detection at different ambient light levels? How is the dynamicrange, frequency response and synaptic gain of glycine release modulated by luminance levels and circadian rhythms? How is synaptic gain changed by different extracellular neuromodulators, like dopamine, and by intracellular messengers like cAMP, phosphateand Ca2+ ions from Ca2+ channels and Ca2+ stores? My talk will try to answer some of these questions and will pose additional ones. It will end with further hypothesis and speculations on the multiple roles of crossover inhibition.
Opponent processing in the expanded retinal mosaic of Nymphalid butterflies
In many butterflies, the ancestral trichromatic insect colour vision, based on UV-, blue- and green-sensitive photoreceptors, is extended with red-sensitive cells. Physiological evidence for red receptors has been missing in nymphalid butterflies, although some species can discriminate red hues well. In eight species from genera Archaeoprepona, Argynnis, Charaxes, Danaus, Melitaea, Morpho, Heliconius and Speyeria, we found a novel class of green-sensitive photoreceptors that have hyperpolarizing responses to stimulation with red light. These green-positive, red-negative (G+R–) cells are allocated to positions R1/2, normally occupied by UV and blue-sensitive cells. Spectral sensitivity, polarization sensitivity and temporal dynamics suggest that the red opponent units (R–) are the basal photoreceptors R9, interacting with R1/2 in the same ommatidia via direct inhibitory synapses. We found the G+R– cells exclusively in butterflies with red-shining ommatidia, which contain longitudinal screening pigments. The implementation of the red colour channel with R9 is different from pierid and papilionid butterflies, where cells R5–8 are the red receptors. The nymphalid red-green opponent channel and the potential for tetrachromacy seem to have been switched on several times during evolution, balancing between the cost of neural processing and the value of extended colour information.
NMC4 Short Talk: The complete connectome of an insect brain
Brains must integrate complex sensory information and compare to past events to generate appropriate behavioral responses. The neural circuit basis of these computations is unclear and the underlying structure unknown. Here, we mapped the comprehensive synaptic wiring diagram of the fruit fly larva brain, which contains 3,013 neurons and 544K synaptic sites. It is the most complete insect connectome to date: 1) Both brain hemispheres are reconstructed, allowing investigation of neural pathways that include contralateral axons, which we found in 37% of brain neurons. 2) All sensory neurons and descending neurons are reconstructed, allowing one to follow signals in an uninterrupted chain—from the sensory periphery, through the brain, to motor neurons in the nerve cord. We developed novel computational tools, allowing us to cluster the brain and investigate how information flows through it. We discovered that feedforward pathways from sensory to descending neurons are multilayered and highly multimodal. Robust feedback was observed at almost all levels of the brain, including descending neurons. We investigated how the brain hemispheres communicate with each other and the nerve cord, leading to identification of novel circuit motifs. This work provides the complete blueprint of a brain and a strong foundation to study the structure-function relationship of neural circuits.
NMC4 Short Talk: Maggot brain, mirror image? A statistical analysis of bilateral symmetry in an insect brain connectome
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.
Target detection in the natural world
Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons that have a limited bandwidth to encode almost impossibly large input ranges. Importantly, natural scenes are not random, and peripheral visual systems have therefore evolved to reduce the predictable redundancy. The vertebrate visual cortex is also optimally tuned to the spatial statistics of natural scenes, but much less is known about how the insect brain responds to these. We are redressing this deficiency using several techniques. Olga Dyakova uses exquisite image manipulation to give natural images unnatural image statistics, or vice versa. Marissa Holden then uses these images as stimuli in electrophysiological recordings of neurons in the fly optic lobes, to see how the brain codes for the statistics typically encountered in natural scenes, and Olga Dyakova measures the behavioral optomotor response on our trackball set-up.
Physical Computation in Insect Swarms
Our world is full of living creatures that must share information to survive and reproduce. As humans, we easily forget how hard it is to communicate within natural environments. So how do organisms solve this challenge, using only natural resources? Ideas from computer science, physics and mathematics, such as energetic cost, compression, and detectability, define universal criteria that almost all communication systems must meet. We use insect swarms as a model system for identifying how organisms harness the dynamics of communication signals, perform spatiotemporal integration of these signals, and propagate those signals to neighboring organisms. In this talk I will focus on two types of communication in insect swarms: visual communication, in which fireflies communicate over long distances using light signals, and chemical communication, in which bees serve as signal amplifiers to propagate pheromone-based information about the queen’s location.
Collective Construction in Natural and Artificial Swarms
Natural systems provide both puzzles to unravel and demonstrations of what's possible. The natural world is full of complex systems of dynamically interchangeable, individually unreliable components that produce effective and reliable outcomes at the group level. A complementary goal to understanding the operation of such systems is that of being able to engineer artifacts that work in a similar way. One notable type of collective behavior is collective construction, epitomized by mound-building termites, which build towering, intricate mounds through the joint activity of millions of independent and limited insects. The artificial counterpart would be swarms of robots designed to build human-relevant structures. I will discuss work on both aspects of the problem, including studies of cues that individual termite workers use to help direct their actions and coordinate colony activity, and development of robot systems that build user-specified structures despite limited information and unpredictable variability in the process. These examples illustrate principles used by the insects and show how they can be applied in systems we create.
Predator-prey interactions: the avian visual sensory perspective
My research interests are centered on animal ecology, and more specifically include the following areas: visual ecology, behavioral ecology, and conservation biology, as well as the interactions between them. My research is question-driven. I answer my questions in a comprehensive manner, using a combination of empirical, theoretical, and comparative approaches. My model species are usually birds, but I have also worked with fish, mammals, amphibians, and insects. I was fortunate to enrich my education by attending Universities in different parts of the world. I did my undergraduate, specialized in ecology and biodiversity, at the "Universidad Nacional de Cordoba", Argentina. My Ph.D. was in animal ecology and conservation biology at the "Universidad Complutense de Madrid", Spain. My two post-docs were focused on behavioral ecology; the first one at University of Oxford (United Kingdom), and the second one at University of Minnesota (USA). I was an Assistant Professor at California State University Long Beach for almost six years. I am now a Full Professor of Biological Sciences at Purdue University.
Neural circuits that support robust and flexible navigation in dynamic naturalistic environments
Tracking heading within an environment is a fundamental requirement for flexible, goal-directed navigation. In insects, a head-direction representation that guides the animal’s movements is maintained in a conserved brain region called the central complex. Two-photon calcium imaging of genetically targeted neural populations in the central complex of tethered fruit flies behaving in virtual reality (VR) environments has shown that the head-direction representation is updated based on self-motion cues and external sensory information, such as visual features and wind direction. Thus far, the head direction representation has mainly been studied in VR settings that only give flies control of the angular rotation of simple sensory cues. How the fly’s head direction circuitry enables the animal to navigate in dynamic, immersive and naturalistic environments is largely unexplored. I have developed a novel setup that permits imaging in complex VR environments that also accommodate flies’ translational movements. I have previously demonstrated that flies perform visually-guided navigation in such an immersive VR setting, and also that they learn to associate aversive optogenetically-generated heat stimuli with specific visual landmarks. A stable head direction representation is likely necessary to support such behaviors, but the underlying neural mechanisms are unclear. Based on a connectomic analysis of the central complex, I identified likely circuit mechanisms for prioritizing and combining different sensory cues to generate a stable head direction representation in complex, multimodal environments. I am now testing these predictions using calcium imaging in genetically targeted cell types in flies performing 2D navigation in immersive VR.
Internal structure of honey bee swarms for mechanical stability and division of labor
The western honey bee (Apis mellifera) is a domesticated pollinator famous for living in highly social colonies. In the spring, thousands of worker bees and a queen fly from their hive in search of a new home. They self-assemble into a swarm that hangs from a tree branch for several days. We reconstruct the non-isotropic arrangement of worker bees inside swarms made up of 3000 - 8000 bees using x-ray computed tomography. Some bees are stationary and hang from the attachment board or link their bodies into hanging chains to support the swarm structure. The remaining bees use the chains as pathways to walk around the swarm, potentially to feed the queen or communicate with one another. The top layers of bees bear more weight per bee than the remainder of the swarm, suggesting that bees are optimizing for additional factors besides weight distribution. Despite not having a clear leader, honey bees are able to organize into a swarm that protects the queen and remains stable until scout bees locate a new hive.
Communicating (Neuro)Science
In recent years, communicating one’s research to audiences outside of academia has grown in importance and time commitment for many researchers. Science Slams or University Open Days reliably draw large crowds, and the potential of social media to amplify any message has made it possible to reach interested recipients without the traditional press as a middleman. In this presentation, I will provide insights into science communication from my perspective as a neuroscience researcher, who enjoys spreading the word about how amazing insect brains are. We will have a look at the What?, Why? and How? of science communication. What do we generally mean by the term, and what forms can it take? Why should – or must – we engage in it? And how can we best achieve our aims with it? I will provide an overview of the current communication landscape, some food for (critical) thought, and many practical tips that help me when preparing to share my science with a wider audience.
Evolution of vision - The regular route and shortcuts
Eyes abound in the animal kingdom. Some are large as basketballs and others are just fractions of a millimetre. Eyes also come in many different types, such as the compound eyes of insects, the mirror eyes of scallopsor our own camera-like eyes. Common to all animal eyes is that they serve the same fundamental role of collecting external information for guidingthe animal’s behaviour. But behaviours vary tremendously across the animal kingdom, and it turns outthis is the key to understand how eyes evolved. The lecture will take a tour from the first animals that could only sense the presence of light, to those that saw the first crude image of the world and finally to animals that use acute vision for interacting with otheranimals. Amazingly, all these stages of eye evolution still exist in animals living today, and this is how we can unravel the evolution of behaviours that has been the driving force behind eye evolution
Neural mechanisms of navigation behavior
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.
The 2021 Annual Bioengineering Lecture + Bioinspired Guidance, Navigation and Control Symposium
Join the Department of Bioengineering on the 26th May at 9:00am for The 2021 Annual Bioengineering Lecture + Bioinspired Guidance, Navigation and Control Symposium. This year’s lecture speaker will be distinguished bioengineer and neuroscientist Professor Mandyam V. Srinivasan AM FRS, from the University of Queensland. Professor Srinivasan studies visual systems, particularly those of bees and birds. His research has revealed how flying insects negotiate narrow gaps, regulate the height and speed of flight, estimate distance flown, and orchestrate smooth landings. Apart from enhancing fundamental knowledge, these findings are leading to novel, biologically inspired approaches to the design of guidance systems for unmanned aerial vehicles with applications in the areas of surveillance, security and planetary exploration. Following Professor Srinivasan’s lecture will be the Bioinspired GNC Mini Symposium with guest speakers from Google Deepmind, Imperial College London, the University of Würzburg and the University of Konstanz giving talks on their research into autonomous robot navigation, neural mechanisms of compass orientation in insects and computational approaches to motor control.
Neural codes in early sensory areas maximize fitness
It has generally been presumed that sensory information encoded by a nervous system should be as accurate as its biological limitations allow. However, perhaps counter intuitively, accurate representations of sensory signals do not necessarily maximize the organism’s chances of survival. We show that neural codes that maximize reward expectation—and not accurate sensory representations—account for retinal responses in insects, and retinotopically-specific adaptive codes in humans. Thus, our results provide evidence that fitness-maximizing rules imposed by the environment are applied at the earliest stages of sensory processing.
Stereo vision in humans and insects
Stereopsis – deriving information about distance by comparing views from two eyes – is widespread in vertebrates but so far known in only class of invertebrates, the praying mantids. Understanding stereopsis which has evolved independently in such a different nervous system promises to shed light on the constraints governing any stereo system. Behavioral experiments indicate that insect stereopsis is functionally very different from that studied in vertebrates. Vertebrate stereopsis depends on matching up the pattern of contrast in the two eyes; it works in static scenes, and may have evolved in order to break camouflage rather than to detect distances. Insect stereopsis matches up regions of the image where the luminance is changing; it is insensitive to the detailed pattern of contrast and operates to detect the distance to a moving target. Work from my lab has revealed a network of neurons within the mantis brain which are tuned to binocular disparity, including some that project to early visual areas. This is in contrast to previous theories which postulated that disparity was computed only at a single, late stage, where visual information is passed down to motor neurons. Thus, despite their very different properties, the underlying neural mechanisms supporting vertebrate and insect stereopsis may be computationally more similar than has been assumed.
The collective behavior of the clonal raider ant: computations, patterns, and naturalistic behavior
Colonies of ants and other eusocial insects are superorganisms, which perform sophisticated cognitive-like functions at the level of the group. In my talk I will review our efforts to establish the clonal raider ant Ooceraea biroi as a lab model system for the systematic study of the principles underlying collective information processing in ant colonies. I will use results from two separate projects to demonstrate the potential of this model system: In the first, we analyze the foraging behavior of the species, known as group raiding: a swift offensive response of a colony to the detection of a potential prey by a scout. By using automated behavioral tracking and detailed analysis we show that this behavior is closely related to the army ant mass raid, an iconic collective behavior in which hundreds of thousands of ants spontaneously leave the nest to go hunting, and that the evolutionary transition between the two can be explained by a change in colony size alone. In the second project, we study the emergence of a collective sensory response threshold in a colony. The sensory threshold is a fundamental computational primitive, observed across many biological systems. By carefully controlling the sensory environment and the social structure of the colonies we were able to show that it also appear in a collective context, and that it emerges out of a balance between excitatory and inhibitory interactions between ants. Furthermore, by using a mathematical model we predict that these two interactions can be mapped into known mechanisms of communication in ants. Finally, I will discuss the opportunities for understanding collective behavior that are opening up by the development of methods for neuroimaging and neurocontrol of our ants.
The neuroecological context of group living
Dr. Sean O'Donnell is a Professor of Biodiversity Earth & Environmental Science at Drexel University, USA. His neuroscience research focuses on how brain structure plasticity & evolution are affected by social behavior, mainly using insects as models. He is also interested in tropical ecology & thermal physiology. He conducts field research & teaches field courses in Central & South America, as well as in the Negev Desert in Israel.
Vision for escape and pursuit
We want to understand how the visual system detects and tracks salient stimuli in the environment to initiate and guide specific behaviors (i.e., visual neuroethology). Predator avoidance and prey capture are central selection pressures of animal evolution. Mice use vision to detect aerial predators and hunt insects. I will discuss studies from my group that identify specific circuits and pathways in the early visual system (i.e., the retina and its subcortical targets) mediating predator avoidance and prey capture in mice. Our results highlight the importance of subcellular visual processing in the retina and the alignment of viewing strategies with region- and cell-type-specific retinal ganglion cell projection patterns to the brain.
An Adaptive-Gravity Model for Insect Swarms: Miniature Star-Clusters Buzzing Above Your Heads in the Park
Modelling the neural mechanisms of navigation in insects
Toward an understanding of the impact of prenatal exposure to environmental contaminants on brain development
The risks of in utero and early exposure to environmental contaminants, such as heavy metals and persistent organic pollutants, on child neurodevelopment is now established, however our understanding of how these contaminants alter the human brain is very limited. To address this issue, more effort must be made to integrate brain imaging tools with epidemiological studies. In this seminar, I will be presenting EEG and MRI data collected in birth-cohort studies where impairments of cognitive and sensory functions were observed in association with prenatal exposure to mercury, lead, PCB or organophosphate insecticides. Results obtained in children and adolescents suggest that each pollutant might affect different levels of brain processing and that frontal regions are particularly vulnerable.
Stereo vision and prey detection in the praying mantis
Praying mantises are the only insects known to have stereo vision. We used a comparative approach to determine how the mechanisms underlying stereopsis in mantises differ from those underlying primate stereo vision. By testing mantises with virtual 3D targets we showed that mantis stereopsis enables prey capture in complex scenes but the mechanisms underlying it differ from those underlying primate stereopsis. My talk will further discuss how stereopsis combines with second-order motion perception to enable the detection of camouflaged prey by mantises. The talk will highlight the benefits of a comparative approach towards understanding visual cognition.
Collective Ecophysiology and Physics of Social Insects
Collective behavior of organisms creates environmental micro-niches that buffer them from environmental fluctuations e.g., temperature, humidity, mechanical perturbations, etc., thus coupling organismal physiology, environmental physics, and population ecology. This talk will focus on a combination of biological experiments, theory, and computation to understand how a collective of bees can integrate physical and behavioral cues to attain a non-equilibrium steady state that allows them to resist and respond to environmental fluctuations of forces and flows. We analyze how bee clusters change their shape and connectivity and gain stability by spread-eagling themselves in response to mechanical perturbations. Similarly, we study how bees in a colony respond to environmental thermal perturbations by deploying a fanning strategy at the entrance that they use to create a forced ventilation stream that allows the bees to collectively maintain a constant hive temperature. When combined with quantitative analysis and computations in both systems, we integrate the sensing of the environmental cues (acceleration, temperature, flow) and convert them to behavioral outputs that allow the swarms to achieve a dynamic homeostasis.
Blood is thicker than water
According to Hamilton’s inclusive fitness hypothesis, kinship is an organizing principle of social behavior. Behavioral evidence supporting this hypothesis includes the ability to recognize kin and the adjustment of behavior based on kin preference with respect to altruism, attachment and care for offspring in insect societies. Despite the fundamental importance of kinship behavior, the underlying neural mechanisms are poorly understood. We repeated behavioral experiments by Hepper on behavioral preference of rats for their kin. Consistent with Hepper’s work, we find a developmental time course for kinship behavior, where rats prefer sibling interactions at young ages and express non-sibling preferences at older ages. In probing the brain areas responsible for this behavior, we find that aspiration lesions of the lateral septum but not control lesions of cingulate cortices eliminate the behavioral preference in young animals for their siblings and in older rats for non-siblings. We then presented awake and anaesthetized rats with odors and calls of age- and status-matched kin (siblings and mothers) and non-kin (non-siblings and non-mothers) conspecifics, while performing in vivo juxta-cellular and whole-cell patch-clamp recordings in the lateral septum. We find multisensory (olfactory and auditory) neuronal responses, whereby neurons typically responded preferentially but not exclusively to individual social stimuli. Non-kin-odor responsive neurons were found dorsally, while kin-odor responsive neurons were located in ventrally in the lateral septum. To our knowledge such an ordered representation of response preferences according to kinship has not been previously observed and we refer this organization as nepotopy. Nepotopy could be instrumental in reading out kinship from preferential but not exclusive responses and in the generation of differential behavior according to kinship. Thus, our results are consistent with a role of the lateral septum in organizing mammalian kinship behavior.
An evolutionarily conserved hindwing circuit mediates Drosophila flight control
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.
The complexity of the ordinary – neural control of locomotion
Today, considerable information is available on the organization and operation of the neural networks that generate the motor output for animal locomotion, such as swimming, walking, or flying. In recent years, the question of which neural mechanisms are responsible for task-specific and flexible adaptations of locomotor patterns has gained increased attention in the field of motor control. I will report on advances we made with respect to this topic for walking in insects, i.e. the leg muscle control system of phasmids and fruit flies. I will present insights into the neural basis of speed control, heading, walking direction, and the role of ground contact in insect walking, both for local control and intersegmental coordination. For these changes in motor activity modifications in the processing of sensory feedback signals play a pivotal role, for instance for movement and load signals in heading and curve walking or for movement signals that contribute to intersegmental coordination. Our recent findings prompt future investigations that aim to elucidate the mechanisms by which descending and intersegmental signals interact with local networks in the generation of motor flexibility during walking in animals.
Who can turn faster? Comparison of the head direction circuit of two species
Ants, bees and other insects have the ability to return to their nest or hive using a navigation strategy known as path integration. Similarly, fruit flies employ path integration to return to a previously visited food source. An important component of path integration is the ability of the insect to keep track of its heading relative to salient visual cues. A highly conserved brain region known as the central complex has been identified as being of key importance for the computations required for an insect to keep track of its heading. However, the similarities or differences of the underlying heading tracking circuit between species are not well understood. We sought to address this shortcoming by using reverse engineering techniques to derive the effective underlying neural circuits of two evolutionary distant species, the fruit fly and the locust. Our analysis revealed that regardless of the anatomical differences between the two species the essential circuit structure has not changed. Both effective neural circuits have the structural topology of a ring attractor with an eight-fold radial symmetry (Fig. 1). However, despite the strong similarities between the two ring attractors, there remain differences. Using computational modelling we found that two apparently small anatomical differences have significant functional effect on the ability of the two circuits to track fast rotational movements and to maintain a stable heading signal. In particular, the fruit fly circuit responds faster to abrupt heading changes of the animal while the locust circuit maintains a heading signal that is more robust to inhomogeneities in cell membrane properties and synaptic weights. We suggest that the effects of these differences are consistent with the behavioural ecology of the two species. On the one hand, the faster response of the ring attractor circuit in the fruit fly accommodates the fast body saccades that fruit flies are known to perform. On the other hand, the locust is a migratory species, so its behaviour demands maintenance of a defined heading for a long period of time. Our results highlight that even seemingly small differences in the distribution of dendritic fibres can have a significant effect on the dynamics of the effective ring attractor circuit with consequences for the behavioural capabilities of each species. These differences, emerging from morphologically distinct single neurons highlight the importance of a comparative approach to neuroscience.
How Do Bees See the World? A (Normative) Deep Reinforcement Learning Model for Insect Navigation
Bernstein Conference 2024
An insect vision-based flight control model with a plastic efference copy
COSYNE 2022
An insect vision-based flight control model with a plastic efference copy
COSYNE 2022
Multiple stimulus features are encoded by single mechanosensory neurons in insect wings
COSYNE 2022
Multiple stimulus features are encoded by single mechanosensory neurons in insect wings
COSYNE 2022
Path integration in insects as an optimized circuit
COSYNE 2023