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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.