Insect Brain Research Articles

Stochastic and Arbitrarily Generated Input Patterns to the Mushroom Bodies Can Serve as Conditioned Stimuli in Drosophila.

Single neurons in the brains of insects often have individual genetic identities and can be unambiguously identified between animals. The overall neuronal connectivity is also genetically determined and hard-wired to a large degree. Experience-dependent structural and functional plasticity is believed to be superimposed onto this more-or-less fixed connectome. However, in Drosophila melanogaster, it has been shown that the connectivity between the olfactory projection neurons (OPNs) and Kenyon cells, the intrinsic neurons of the mushroom body, is highly stochastic and idiosyncratic between individuals. Ensembles of distinctly and sparsely activated Kenyon cells represent information about the identity of the olfactory input, and behavioral relevance can be assigned to this representation in the course of associative olfactory learning. Previously, we showed that in the absence of any direct sensory input, artificially and stochastically activated groups of Kenyon cells could be trained to encode aversive cues when their activation coincided with aversive stimuli. Here, we have tested the hypothesis that the mushroom body can learn any stochastic neuronal input pattern as behaviorally relevant, independent of its exact origin. We show that fruit flies can learn thermogenetically generated, stochastic activity patterns of OPNs as conditioned stimuli, irrespective of glomerular identity, the innate valence that the projection neurons carry, or inter-hemispheric symmetry.

A dynamical model exploring sensory integration in the insect central complex substructures

It is imperative that an animal has the ability to contextually integrate received sensory information to formulate appropriate behavioral responses. Determining a body heading based on a multitude of ego-motion cues and visual landmarks is an example of such a task that requires this context dependent integration. The work presented here simulates a sensory integrator in the insect brain called the central complex (CX). Based on the architecture of the CX, we assembled a dynamical neural simulation of two structures called the protocerebral bridge (PB) and the ellipsoid body (EB). Using non-spiking neuronal dynamics, our simulation was able to recreate in vivo neuronal behavior such as correlating body rotation direction and speed to activity bumps within the EB as well as updating the believed heading with quick secondary system updates. With this model, we performed sensitivity analysis of certain neuronal parameters as a possible means to control multi-system gains during sensory integration. We found that modulation of synapses in the memory network and EB inhibition are two possible mechanisms in which a sensory system could affect the memory stability and gain of another input, respectively. This model serves as an exploration in network design for integrating simultaneous idiothetic and allothetic cues in the task of body tracking and determining contextually dependent behavioral outputs.

Analysis of Synaptic Microcircuits in the Mushroom Bodies of the Honeybee.

Mushroom bodies (MBs) are multisensory integration centers in the insect brain involved in learning and memory formation. In the honeybee, the main sensory input region (calyx) of MBs is comparatively large and receives input from mainly olfactory and visual senses, but also from gustatory/tactile modalities. Behavioral plasticity following differential brood care, changes in sensory exposure or the formation of associative long-term memory (LTM) was shown to be associated with structural plasticity in synaptic microcircuits (microglomeruli) within olfactory and visual compartments of the MB calyx. In the same line, physiological studies have demonstrated that MB-calyx microcircuits change response properties after associative learning. The aim of this review is to provide an update and synthesis of recent research on the plasticity of microcircuits in the MB calyx of the honeybee, specifically looking at the synaptic connectivity between sensory projection neurons (PNs) and MB intrinsic neurons (Kenyon cells). We focus on the honeybee as a favorable experimental insect for studying neuronal mechanisms underlying complex social behavior, but also compare it with other insect species for certain aspects. This review concludes by highlighting open questions and promising routes for future research aimed at understanding the causal relationships between neuronal and behavioral plasticity in this charismatic social insect.

Social Facilitation of Long-Lasting Memory is Mediated by CO <sub>2</sub> in Drosophila

How social interactions influences cognition is a fundamental question, yet rarely addressed at the neurobiological level. It is well established that the presence of conspecifics affects learning and memory performance, but the neural basis for the influence of the social context has received little attention. In the fruitfly Drosophila melanogaster, the presence of conspecifics improves retrieval of a long-lasting olfactory memory. Here, we demonstrate that this memory is composite and involves two independent neural pathways. One is based on the expression of individual memory and depends on the α’β’ lobes outputs of the Mushroom Bodies (MBs), the memory center in the insect brain. The other one relies on the expression of group memory and requires a distinct sub-part of the MBs, the αβ lobes outputs. We show that such social facilitation increases with group size and is triggered by the CO2 released by group members. Among the known neurons carrying CO2 information in the brain, we establish that the bilateral Ventral Projection Neuron (biVPN), which projects onto the MBs, is necessary for social facilitation. Moreover, we demonstrate that this CO2-dependent memory engages a serotoninergic pathway involving the Dorsal-Paired Median neurons (DPM), which reveals a new role for this pair of serotonergic neurons. Overall, we identify both the sensorial cue and the neural circuit (biVPN>αβ>DPM>αβ) governing social facilitation of memory. This study provides the first demonstration that being in a group recruits the expression of a cryptic memory and that variations in CO2 concentration can affect cognitive processes in insects.

Vertical Lobes of the Mushroom Bodies are Essential for View-Based Navigation in Australian Bull Ants

For many animals, visual landmarks provide information about their location in space and the direction to a goal. Insects acquire this visual information through a series of well-choreographed walks or flights of learning carried out prior to leaving home. Views acquired during learning walks are sufficient for pinpointing goals both when in their vicinity and when animals are at locations they have not visited previously. It is presumed that animals returning home match the memorised views to their current view for successful view-based navigation. While view-based navigation strategies have been incorporated in a wide variety of navigation models used in robotics, we still know very little about how view-based navigation is performed by the insect brain. We investigated the role of the mushroom bodies in view-based navigation in a visually oriented Australian bull ant Myrmecia midas. We targeted the mushroom body vertical lobes (VL) because they are innervated by the visual input regions of the mushroom body and are known to be involved in learning and memory. To ensure that ants in our experiments could navigate using only visual landmarks, we captured experienced foragers close to their nest when they were returning home. For our treatment group, we selectively inhibited neural activity in the VL of the mushroom bodies using the anesthetic procaine and compared their behaviour with three groups: untreated control, VL saline injected, and off-target (antennal lobe) procaine injected groups. Ants were then released at their familiar foraging tree, their subsequent paths were filmed, and their final destinations were determined. While all groups exhibited similar walking speeds, we found significant differences in their orientation and the ability of ants to successfully return home. Untreated control and off-target procaine injected ants were well directed and the most successful at returning home. Animals with procaine-inactivated VL had tortuous paths with multiple loops and were unable to find their nest. We analysed their walking speed relative to gaze direction and found that untreated animals accelerated when their gaze was directed toward home. This behaviour was eliminated by anaesthetizing the VL. Our data show that a simple and effective view-based navigation strategy – accelerate whenever a homeward view is in the frontal visual field – is mediated by the VL of the ant brain. We therefore provide neurobiological evidence that view-based navigation requires functional mushroom bodies.

Route-following ants respond to alterations of the view sequence.

Ants can navigate by comparing the currently perceived view with memorised views along a familiar foraging route. Models regarding route-following suggest that the views are stored and recalled independently of the sequence in which they occur. Hence, the ant only needs to evaluate the instantaneous familiarity of the current view to obtain a heading direction. This study investigates whether ant homing behaviour is influenced by alterations in the sequence of views experienced along a familiar route, using the frequency of stop-and-scan behaviour as an indicator of the ant's navigational uncertainty. Ants were trained to forage between their nest and a feeder which they exited through a short channel before proceeding along the homeward route. In tests, ants were collected before entering the nest and released again in the channel, which was placed either in its original location or halfway along the route. Ants exiting the familiar channel in the middle of the route would thus experience familiar views in a novel sequence. Results show that ants exiting the channel scan significantly more when they find themselves in the middle of the route, compared with when emerging at the expected location near the feeder. This behaviour suggests that previously encountered views influence the recognition of current views, even when these views are highly familiar, revealing a sequence component to route memory. How information about view sequences could be implemented in the insect brain, as well as potential alternative explanations to our results, are discussed.

A Systematic Nomenclature for the <i>Drosophila</i> Ventral Nervous System

The fruit fly, Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

基于三维重建技术的昆虫脑结构研究进展

基于三维重建技术的昆虫脑结构研究进展

The reniform body: An integrative lateral protocerebral neuropil complex of Eumalacostraca identified in Stomatopoda and Brachyura

Mantis shrimps (Stomatopoda) possess in common with other crustaceans, and with Hexapoda, specific neuroanatomical attributes of the protocerebrum, the most anterior part of the arthropod brain. These attributes include assemblages of interconnected centers called the central body complex and in the lateral protocerebra, situated in the eyestalks, paired mushroom bodies. The phenotypic homologues of these centers across Panarthropoda support the view that ancestral integrative circuits crucial to action selection and memory have persisted since the early Cambrian or late Ediacaran. However, the discovery of another prominent integrative neuropil in the stomatopod lateral protocerebrum raises the question whether it is unique to Stomatopoda or at least most developed in this lineage, which may have originated in the upper Ordovician or early Devonian. Here, we describe the neuroanatomical structure of this center, called the reniform body. Using confocal microscopy and classical silver staining, we demonstrate that the reniform body receives inputs from multiple sources, including the optic lobe's lobula. Although the mushroom body also receives projections from the lobula, it is entirely distinct from the reniform body, albeit connected to it by discrete tracts. We discuss the implications of their coexistence in Stomatopoda, the occurrence of the reniform body in another eumalacostracan lineage and what this may mean for our understanding of brain functionality in Pancrustacea.

Neuroarchitecture of the central complex of the desert locust: Tangential neurons.

The central complex (CX) comprises a group of midline neuropils in the insect brain, consisting of the protocerebral bridge (PB), the upper (CBU) and lower division (CBL) of the central body and a pair of globular noduli. It receives prominent input from the visual system and plays a major role in spatial orientation of the animals. Vertical slices and horizontal layers of the CX are formed by columnar, tangential, and pontine neurons. While pontine and columnar neurons have been analyzed in detail, especially in the fruit fly and desert locust, understanding of the organization of tangential cells is still rudimentary. As a basis for future functional studies, we have studied the morphologies of tangential neurons of the CX of the desert locust Schistocerca gregaria. Intracellular dye injections revealed 43 different types of tangential neuron, 8 of the PB, 5 of the CBL, 24 of the CBU, 2 of the noduli, and 4 innervating multiple substructures. Cell bodies of these neurons were located in 11 different clusters in the cell body rind. Judging from the presence of fine versus beaded terminals, the vast majority of these neurons provide input into the CX, especially from the lateral complex (LX), the superior protocerebrum, the posterior slope, and other surrounding brain areas, but not directly from the mushroom bodies. Connections are largely subunit- and partly layer-specific. No direct connections were found between the CBU and the CBL. Instead, both subdivisions are connected in parallel with the PB and distinct layers of the noduli.

The case for emulating insect brains using anatomical “wiring diagrams” equipped with biophysical models of neuronal activity

Developing whole-brain emulation (WBE) technology would provide immense benefits across neuroscience, biomedicine, artificial intelligence, and robotics. At this time, constructing a simulated human brain lacks feasibility due to limited experimental data and limited computational resources. However, I suggest that progress toward this goal might be accelerated by working toward an intermediate objective, namely insect brain emulation (IBE). More specifically, this would entail creating biologically realistic simulations of entire insect nervous systems along with more approximate simulations of non-neuronal insect physiology to make "virtual insects." I argue that this could be realistically achievable within the next 20years. I propose that developing emulations of insect brains will galvanize the global community of scientists, businesspeople, and policymakers toward pursuing the loftier goal of emulating the human brain. By demonstrating that WBE is possible via IBE, simulating mammalian brains and eventually the human brain may no longer be viewed as too radically ambitious to deserve substantial funding and resources. Furthermore, IBE will facilitate dramatic advances in cognitive neuroscience, artificial intelligence, and robotics through studies performed using virtual insects.

In Vivo Optical Calcium Imaging of Learning-Induced Synaptic Plasticity in Drosophila melanogaster.

Decades of research in many model organisms have led to the current concept of synaptic plasticity underlying learning and memory formation. Learning-induced changes in synaptic transmission are often distributed across many neurons and levels of processing in the brain. Therefore, methods to visualize learning-dependent synaptic plasticity across neurons are needed. The fruit fly Drosophila melanogaster represents a particularly favorable model organism to study neuronal circuits underlying learning. The protocol presented here demonstrates a way in which the processes underlying the formation of associative olfactory memories, i.e., synaptic activity and their changes, can be monitored in vivo. Using the broad array of genetic tools available in Drosophila, it is possible to specifically express genetically encoded calcium indicators in determined cell populations and even single cells. By fixing a fly in place, and opening the head capsule, it is possible to visualize calcium dynamics in these cells whilst delivering olfactory stimuli. Additionally, we demonstrate a set-up in which the fly can be subjected, simultaneously, to electric shocks to the body. This provides a system in which flies can undergo classical olfactory conditioning - whereby a previously naïve odor is learned to be associated with electric shock punishment - at the same time as the representation of this odor (and other untrained odors) is observed in the brain via two-photon microscopy. Our lab has previously reported the generation of synaptically localized calcium sensors, which enables one to confine the fluorescent calcium signals to pre- or postsynaptic compartments. Two-photon microscopy provides a way to spatially resolve fine structures. We exemplify this by focusing on neurons integrating information from the mushroom body, a higher-order center of the insect brain. Overall, this protocol provides a method to examine the synaptic connections between neurons whose activity is modulated as a result of olfactory learning.

Immunohistochemistry and Fluorescent Whole Mount RNA In Situ Hybridization in Larval and Adult Brains of Tribolium.

Arthropod brains are fascinating structures that exhibit great complexity but also contain conserved elements that can be recognized between species. There is a long tradition of research in insect neuroanatomy, cell biology, and in studying the genetics of insect brain development. Recently, the beetle Tribolium castaneum has gained attention as a model for insect head and brain development, and many anterior patterning genes have so far been characterized in beetle embryos. The outcome of embryonic anterior development is the larval and, subsequently, the adult brain. A basic requirement to understand genetic cell type diversity within these structures is the ability to localize mRNA and protein of neural genes. Here we detail our protocols for RNA in situ hybridization in combination with immunohistochemistry, optimized for dissected brains of larval and adult beetles.

Memristor design rules for dynamic learning and edge processing applications

The ability to dynamically learn and adapt to changes in the environment is one of the hallmarks of biological systems. In this work, we identify the subset of the design space of memristive materials that is optimal for dynamic learning applications. Using an architecture inspired on the learning center of the insect brain, we implement a model system consisting of a discrete implementation of spiking neurons where dynamic learning takes place on a set of plastic synapses formed by memristor pairs in a crossbar array. Using two separate benchmarks, one comprising the dynamic learning of the Modified National Institute of Standards and Technology dataset and another one targeting one shot learning, we have identified the key properties that memristive materials should have to be optimal dynamic learners. The results obtained show that a fine degree of control of the memristor internal state is key to achieve high classification accuracy during dynamic learning but that within this optimal region learning is extremely robust both to device variability and to errors in the writing of the internal state, in all cases allowing for 2σ variations greater than 40% without significant loss of accuracy, hence overcoming two of the perceived limitations of memristors. By additionally requiring that learning takes place concurrently to information processing, we are able to derive a set constraints to the memristor dynamics.

Insect brain plasticity: effects of olfactory input on neuropil size.

Insect brains are known to express a high degree of experience-dependent structural plasticity. One brain structure in particular, the mushroom body (MB), has been attended to in numerous studies as it is implicated in complex cognitive processes such as olfactory learning and memory. It is, however, poorly understood to what extent sensory input per se affects the plasticity of the mushroom bodies. By performing unilateral blocking of olfactory input on immobilized butterflies, we were able to measure the effect of passive sensory input on the volumes of antennal lobes (ALs) and MB calyces. We showed that the primary and secondary olfactory neuropils respond in different ways to olfactory input. ALs show absolute experience-dependency and increase in volume only if receiving direct olfactory input from ipsilateral antennae, while MB calyx volumes were unaffected by the treatment and instead show absolute age-dependency in this regard. We therefore propose that cognitive processes related to behavioural expressions are needed in order for the calyx to show experience-dependent volumetric expansions. Our results indicate that such experience-dependent volumetric expansions of calyces observed in other studies may have been caused by cognitive processes rather than by sensory input, bringing some causative clarity to a complex neural phenomenon.

From skylight input to behavioural output: A computational model of the insect polarised light compass.

Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to ‘true north’ during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.

Brain Organization of Apolygus lucorum: A Hemipteran Species With Prominent Antennal Lobes.

The anatomical organization of distinct regions in the insect brain often reflects their functions. In the present study, the brain structure of Apolygus lucorum was examined by using immunolabeling and three-dimensional reconstruction. The results revealed the location and volume of prominent neuropils, such as the antennal lobes (AL), optic lobes (OL), anterior optic tubercles (AOTU), central body (CB), lateral accessory lobes (LAL), mushroom lobes, and distinct tritocerebral neuropils. As expected, this brain is similar to that of other insects. One exception, however, is that the antennal lobes were found to be the most prominent neuropils. Their size relative to the entire brain is the largest among all insect species studied so far. In contrast, the calyx, a region getting direct input from the antennal lobe, has a smaller size relative to the brain than that of other species. These findings may suggest that olfaction plays an essential role for A. lucorum.

A neuronal correlate of insect stereopsis

A puzzle for neuroscience—and robotics—is how insects achieve surprisingly complex behaviours with such tiny brains. One example is depth perception via binocular stereopsis in the praying mantis, a predatory insect. Praying mantids use stereopsis, the computation of distances from disparities between the two retinal images, to trigger a raptorial strike of their forelegs when prey is within reach. The neuronal basis of this ability is entirely unknown. Here we show the first evidence that individual neurons in the praying mantis brain are tuned to specific disparities and eccentricities, and thus locations in 3D-space. Like disparity-tuned cortical cells in vertebrates, the responses of these mantis neurons are consistent with linear summation of binocular inputs followed by an output nonlinearity. Our study not only proves the existence of disparity sensitive neurons in an insect brain, it also reveals feedback connections hitherto undiscovered in any animal species.

Symbolic representation of numerosity by honeybees ( Apis mellifera): matching characters to small quantities.

The assignment of a symbolic representation to a specific numerosity is a fundamental requirement for humans solving complex mathematical calculations used in diverse applications such as algebra, accounting, physics and everyday commerce. Here we show that honeybees are able to learn to match a sign to a numerosity, or a numerosity to a sign, and subsequently transfer this knowledge to novel numerosity stimuli changed in colour properties, shape and configuration. While honeybees learned the associations between two quantities (two; three) and two signs (N-shape; inverted T-shape), they failed at reversing their specific task of sign-to-numerosity matching to numerosity-to-sign matching and vice versa (i.e. a honeybee that learned to match a sign to a number of elements was not able to invert this learning to match the numerosity of elements to a sign). Thus, while bees could learn the association between a symbol and numerosity, it was linked to the specific task and bees could not spontaneously extrapolate the association to a novel, reversed task. Our study therefore reveals that the basic requirement for numerical symbolic representation can be fulfilled by an insect brain, suggesting that the absence of its spontaneous emergence in animals is not due to cognitive limitation.

Queen Dominance May Reduce Worker Mushroom Body Size in a Social Bee.

The mushroom body (MB) is an area of the insect brain involved in learning, memory, and sensory integration. Here, we used the sweat bee Megalopta genalis (Halictidae) to test for differences between queens and workers in the volume of the MB calyces. We used confocal microscopy to measure the volume of the whole brain, MB calyces, optic lobes, and antennal lobes of queens and workers. Queens had larger brains, larger MB calyces, and a larger MB calyces:whole brain ratio than workers, suggesting an effect of social dominance in brain development. This could result from social interactions leading to smaller worker MBs, or larger queen MBs. It could also result from other factors, such as differences in age or sensory experience. To test these explanations, we next compared queens and workers to other groups. We compared newly emerged bees, bees reared in isolation for 10days, bees initiating new observation nests, and bees initiating new natural nests collected from the field to queens and workers. Queens did not differ from these other groups. We suggest that the effects of queen dominance over workers, rather than differences in age, experience, or reproductive status, are responsible for the queen-worker differences we observed. Worker MB development may be affected by queen aggression directly and/or manipulation of larval nutrition, which is provisioned by the queen. We found no consistent differences in the size of antennal lobes or optic lobes associated with differences in age, experience, reproductive status, or social caste.