Apprentissage visuel en réalité virtuelle chez Apis mellifera

Dotées d'un cerveau de moins d'un millimètre cube et contenant environ 950 000 neurones, les abeilles présentent un riche répertoire comportemental, parmi lesquels l'apprentissage appétitif et la mémoire jouent un rôle fondamental dans le contexte des activités de recherche de nourriture. Outre les formes élémentaires d'apprentissage, où les abeilles apprennent une association spécifique entre des événements de leur environnement, les abeilles maîtrisent également différentes formes d'apprentissage non-élémentaire, à la fois dans le domaine visuel et olfactif, y compris la catégorisation, l'apprentissage contextuel et l'abstraction de règles. Ces caractéristiques en font un modèle idéal pour l'étude de l'apprentissage visuel et pour explorer les mécanismes neuronaux qui sous-tendent leurs capacités d'apprentissage. Afin d'accéder au cerveau d'une abeille lors d'une tâche d'apprentissage visuel, l'insecte doit être immobilisé. Par conséquent, des systèmes de réalité virtuelle (VR) ont été développés pour permettre aux abeilles d'agir dans un monde virtuel, tout en restant stationnaires dans le monde réel. Au cours de mon doctorat, j'ai développé un logiciel de réalité virtuelle 3D flexible et open source pour étudier l'apprentissage visuel, et je l'ai utilisé pour améliorer les protocoles de conditionnement existants en VR et pour étudier le mécanisme neuronal de l'apprentissage visuel. En étudiant l'influence du flux optique sur l'apprentissage associatif des couleurs, j'ai découvert que l'augmentation des signaux de mouvement de l'arrière-plan nuisait aux performances des abeilles. Ce qui m'a amené à identifier des problèmes pouvant affecter la prise de décision dans les paysages virtuels, qui nécessitent un contrôle spécifique par les expérimentateurs. Au moyen de la VR, j'ai induit l'apprentissage visuel chez des abeilles et quantifié l'expression immédiate des gènes précoces (IEG) dans des zones spécifiques de leur cerveau pour détecter les régions impliquées dans l'apprentissage visuel. En particulier, je me suis concentré sur kakusei, Hr38 et Egr1, trois IEG liés à la recherche de nourriture et à l'orientation des abeilles et qui peuvent donc également être pertinents pour la formation d'association visuelle appétitive. Cette analyse suggère que les corps pédonculés sont impliqués dans l'apprentissage associatif des couleurs. Enfin, j'ai exploré la possibilité d'utiliser la VR sur d'autres modèles d'insectes et effectué un conditionnement différentiel sur des bourdons. Cette étude a montré que non seulement les bourdons sont capables de résoudre cette tâche cognitive aussi bien que les abeilles, mais aussi qu'ils interagissent davantage avec la réalité virtuelle, ce qui entraîne un ratio plus faible d'individus rejetés de l'expérience par manque de mouvement. Ces résultats indiquent que les protocoles VR que j'ai établis au cours de cette thèse peuvent être appliqués à d'autres insectes, et que le bourdon est un bon candidat pour l'étude de l'apprentissage visuel en VR.Equipped with a brain smaller than one cubic millimeter and containing ~950,000 neurons, honeybees display a rich behavioral repertoire, among which appetitive learning and memory play a fundamental role in the context of foraging activities. Besides elemental forms of learning, where bees learn specific association between environmental features, bees also master different forms of non-elemental learning, including categorization, contextual learning and rule abstraction. These characteristics make them an ideal model for the study of visual learning and its underlying neural mechanisms. In order to access the working brain of a bee during visual learning the insect needs to be immobilized. To do so, virtual reality (VR) setups have been developed to allow bees to behave within a virtual world, while remaining stationary within the real world. During my PhD, I developed a flexible and open source 3D VR software to study visual learning, and used it to improve existing conditioning protocols and to investigate the neural mechanism of visual learning. By developing a true 3D environment, we opened the possibility to add frontal background cues, which were also subjected to 3D updating based on the bee movements. We thus studied if and how the presence of such motion cues affected visual discrimination in our VR landscape. Our results showed that the presence of frontal background motion cues impaired the bees' performance. Whenever these cues were suppressed, color discrimination learning became possible. Our results point towards deficits in attentional processes underlying color discrimination whenever motion cues from the background were frontally available in our VR setup. VR allows to present insects with a tightly controlled visual experience during visual learning. We took advantage of this feature to perform ex-vivo analysis of immediate early gene (IEG) expression in specific brain area, comparing learner and non-learner bees. Using both 3D VR and a lore restrictive 2D version of the same task we tackled two questions, first what are the brain region involved in visual learning? And second, is the pattern of activation of the brain dependent on the modality of learning? Learner bees that solved the task in 3D showed an increased activity of the Mushroom Bodies (MB), which is coherent with the role of the MB in sensory integration and learning. Surprisingly we also found a completely different pattern of IEGs expression in the bees that solved the task in 2D conditions. We observed a neural signature that spanned the optic lobes and MB calyces and was characterized by IEG downregulation, consistent with an inhibitory trace. The study of visual learning's neural mechanisms requires invasive approach to access the brain of the insects, which induces stress in the animals and can thus impair behaviors in itself. To potentially mitigate this effect, bumble bees Bombus terrestris could constitute a good alternative to Apis mellifera as bumble bees are more robust. That's why in the last part of this work we explored the performances of bumblebees in a differential learning task in VR and compared them to those of honey bees. We found that, not only bumble bees are able to solve the task as well as honey bees, but they also engage more with the virtual environment, leading to a lower ratio of discarded individuals. We also found no correlation between the size of bumble bees and their learning performances. This is surprising as larger bumble bees, that assume the role of foragers in the colony, have been shown to be better at learning visual tasks in the literature

What Is Cognitive Psychology?

What Is Cognitive Psychology? identifies the theoretical foundations of cognitive psychology—foundations which have received very little attention in modern textbooks. Beginning with the basics of information processing, Michael R. W. Dawson explores what experimental psychologists infer about these processes and considers what scientific explanations are required when we assume cognition is rule-governed symbol manipulation. From these foundations, psychologists can identify the architecture of cognition and better understand its role in debates about its true nature. This volume offers a deeper understanding of cognitive psychology and presents ideas for integrating traditional cognitive psychology with more modern fields like cognitive neuroscience.Publishe

Cognition visuelle chez l'abeille Apis mellifera : catégorisation par extraction de configurations spatiales et de concepts relationnels

Dans ce travail nous avons étudié la sophistication cognitive dont est capable l'abeille domestique Apis mellifera dans l'analyse de son environnement visuel. Grâce à la mise en place d'une procédure expérimentale d'apprentissage permettant de mettre en évidence les performances fines de discrimination visuelle des abeilles, nous avons étudié la classification de stimuli visuels par catégorisation et formation de concepts. Dans le premier cas, les abeilles groupent des objets visuels en fonction de leur appartenance à une catégorie définie par une similarité perceptive; dans le deuxième cas, les abeilles regroupent les stimuli visuels à partir de règles abstraites (ex: 'plus grand que') et non de leurs propriétés physiques. Nous avons étudié en particulier la catégorisation de stimuli sur la base d'une configuration de type " visage ". Nous montrons que cet insecte peut extraire les relations entre les éléments d'un visage schématique et les combiner de façon à définir une catégorie. Ainsi, la présence de cette configuration permet de traiter de nouveaux stimuli comme appartenant à la catégorie d'intérêt. L'utilisation de configuration pour reconnaître des objets visuels semble être naturellement utilisée par l'abeille et n'est donc pas seulement induite par un entraînement spécifique. Nous avons par ailleurs étudié l'acquisition par l'abeille de concepts relationnels de nature spatiale tels que " au-dessus " ou " en-dessous ", indépendamment des éléments impliqués dans ces relations. L'abeille s'est de plus montrée capable d'associer deux concepts différents (relation spatiale et différence entre les éléments impliqués dans la relation) dans une règle permettant d'obtenir une récompense, transférable à de nouveaux stimuli physiquement très différents. Ces résultats mettent en évidence un niveau d'analyse et d'abstraction insoupçonné pour un invertébré et ouvrent le débat sur l'architecture neurale minimale requise pour atteindre une telle sophistication cognitive.In this work we studied the cognitive sophistication reached by the honeybee Apis mellifera when analysing its visual environment. Thanks to a new-designed learning protocol allowing better performance of bees' visual discrimination, we studied visual stimuli classification by categorization and concept formation. In the first case, bees grouped visual objects into classes defined by perceptual similarity; in the second case, bees extract abstract rules from visual stimuli (e.g. 'bigger than') instead of their specific physical properties. We studied in particular stimuli categorization based on a "face-like" configuration. We show that this insect can extract relationships between the elements of a schematic face and combine them to define a category. Thus, novel stimuli presenting this configuration would be process as member of the category of interest. Moreover, bees seem to naturally use configuration to recognize visual objects. This processing is thus not only inducing by our training procedure. We also studied the bees' acquisition of spatial relational concepts such as "above" or "below", regardless of the elements involved in these relationships. The bee has, in addition, shown its ability to combine two different concepts (spatial relationship and difference between the elements involved in the relationship) in a rule in order to obtain a reward. This rule is transferable to novel physically different stimuli. These results demonstrate an unsuspected level of analysis and abstraction in an invertebrate and open debate on the neural minimum architecture required to achieve such cognitive complexity

Decision-Making and Action Selection in Honeybees: a Theoretical and Experimental Study

Decision-making is an integral part of everyday life for animals of all species. Some decisions are rapid and based on sensory input alone, others rely on factors such as context and internal motivation. The possibilities for the experimental investigation of choice behaviour in mammals, especially in humans, are seemingly endless. However, neuroscience has struggled to define the neural circuitry behind decision-making processes due to the complex structure of the mammalian brain. For this work we turn to the honeybee for inspiration. With a brain composed of approximately one million neurons and sized at a tiny 1mm3, it may be assumed that such an insect produces mere `programmed' behaviours, yet, the honeybee exhibits a rich, elaborate behavioural repertoire and a large capacity for learning in a variety of different paradigms. Indeed, the honeybee has been identified as a powerful model for decision-making. Sequential sampling models, originating in psychology, have been used to explain rapid decision-making behaviours. Such models assume that noisy sensory evidence is integrated over time until a threshold is reached, whereby a decision is made. These models have proven popular because they are able to fit biological data and are furthermore supported by neural evidence. Additionally, they explain the speed-accuracy trade-off, a behavioural phenomenon also demonstrated in bees. For this work we examine honeybee choice behaviour in different levels of satiation, and show that hungry bees are faster and less accurate than partially satiated bees in a simple choice task. We suggest that differences in choice behaviour may be attributed to a simple mechanism which alters the level of the decision threshold according to how satiated the bee is. We further speculate that the honeybee olfactory system may be a drift-diffusion channel, and develop a simple computational model, based on honeybee neurobiology, with simulations that match behavioural results

Plasticity in the Olfactory System: Lessons for the Neurobiology of Memory

We are rapidly advancing toward an understanding of the molecular events underlying odor transduction, mechanisms of spatiotemporal central odor processing, and neural correlates of olfactory perception and cognition. A thread running through each of these broad components that define olfaction appears to be their dynamic nature. How odors are processed, at both the behavioral and neural level, is heavily dependent on past experience, current environmental context, and internal state. The neural plasticity that allows this dynamic processing is expressed nearly ubiquitously in the olfactory pathway, from olfactory receptor neurons to the higher-order cortex, and includes mechanisms ranging from changes in membrane excitability to changes in synaptic efficacy to neurogenesis and apoptosis. This review will describe recent findings regarding plasticity in the mammalian olfactory system that are believed to have general relevance for understanding the neurobiology of memory.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Learning and adaptation in the Drosophila olfactory system

All forms of memory rely on plasticity to correctly store information. Plasticity ensures that certain sets of cells consistently activate each other through the strengthening of certain synapses while others are weakened. This plasticity ensures that a stimulus (internally or externally generated) consistently activates the same cells to produce the same response. These plastic changes can be short-lived, lasting mere seconds, or longer-lived, lasting days, weeks, and months. To ensure accurate storage of memory tight regulation is required. Mammalian memory systems are complex, involving the integration and processing of information from a wide variety of areas. To overcome the issue of complexity memory is often studied in less complex organisms. One of the leading models for memory is the Drosophila olfactory system. In Drosophila, associative memories are formed in the Mushroom Body (MB). Over the past 30 years, work in the MB has given us massive insight into plasticity processes and the tight regulation required to ensure accurate coding. Here I aim to test the limits of this regulation and identify novel mechanisms that may ensure accurate memory storage. First, I tested how robust activity regulation in the mushroom body is and how well it adapts to a challenge that it could face in nature,i.e, overactivity induced by pesticides in a food source. Using pesticides that increase cholinergic signaling, I hoped to identify the maximum dose a fly can ingest and still accurately encode associative memory. Furthermore, I wanted to see if the system could adapt to this disruption over time to restore functionality. In the end, I could not find a dose that significantly disrupted learning before fly death, showing that olfactory regulation is at least as robust than other vital systems. Second, one of the major players in memory storage in mammals is nitric oxide (NO). It has also been identified as a factor in the pathogenesis of many neurological conditions. Until recently, no such role in memory had been identified in flies. I wanted to see if manipulating NO levels could disrupt memory and, if so, what effect NO had at a cellular level. Though behavioral experiments were inconclusive, I show here that mushroom body survival was reduced after high doses of the nitric oxide donor s-nitrosoglutathione (GSNO). Finally, I looked at a more everyday challenge to the olfactory system, complex odor mixtures. I used the α′3 mushroom body output neuron (MBON), which signals novelty, to show that suppression of certain cells of the mushroom body (MB) makes the components of a mixture appear novel compared to a mixture. This suppression could provide a mechanism by which flies can learn which part of a mixture is predictive of the reward or punishment. Furthermore, I show evidence that different Kenyon cell (KC) subtypes may code mixtures differently depending on the complexity of the odor environment

METHYL-CPG BINDING PROTEINS MEDIATE OCTOPAMINERGIC REGULATION OF COMPLEX BEHAVIORAL TRAITS

An organism’s survivability in the natural world is contingent to its ability to respond rapidly and appropriately to various cues and challenges in its physical and social environment. The dynamicity of various environmental and social factors necessitates plasticity in morphological, physiological and behavioral systems – both at the level of an individual organism and that of a species. For more than century, natural selection of existing genetic variation in populations has helped us understand such plasticity across generations. However, recent years have seen a re-emergence of somewhat contentious quasi-Lamarckian framework with which organisms can reliably transmit acquired traits to subsequent generations in response to changes in external conditions. Whether or not it can be categorized as such, a stable transgenerational transmission of acquired alterations in epigenetic code, including methylation patterns and small RNA molecules, associated with behavioral and physiological, and I use the term here loosely, ‘adaptations’ for up to three generations has indeed been demonstrated in a number of species. The focus on methyl-binding proteins in this dissertation is guided by a motivation to advance our understanding of such epigenetic systems in one of the most extensively used model systems in biological and biomedical research – Drosophila. In contrast to the vast body of literature on the genetics, physiology, ecology, and neurobiology of Drosophila, methylation and methylation-associated processes represent one of the few relatively unexplored territories in this system. This certainly hasn’t been for the lack of trying (see section 1.8). Consistent with their role in other species, Drosophila MBD proteins have been implicated in dynamic regulation of chromatin architecture and spatiotemporal regulation of gene expression. However, methylationdependence of their functions and their contribution to the overall organismal behavior remains equivocal. In this dissertation, I explore the role of the conserved methyl-CpG binding (MBD) proteins in the regulation of octopaminergic (OA) systems that are associated with a number of critical behaviors such as aggression, courtship, feeding, locomotion, sleep, and learning and memory. In chapter II, I, along with my colleagues, demonstrate functional conservation of human and Drosophila MBD-containing proteins. We show – (a) that a well-characterized human protein – MeCP2 – can regulate amine neuron output in Drosophila through MBD domain, (b) that endogenous MBD proteins in Drosophila regulate OA sleep circuitry in a manner similar to human MeCP2, and (c) that human and Drosophila MBD proteins may share a select few genomic binding sites on larval polytene chromosomes. In chapter III, we describe a novel function of these chromatin modifiers in the regulation of social behaviors, including aggression and courtship. Returning to the issue of methylation, we demonstrate an interaction effect between induced-DNA hypermethylation and MBD-function in context of aggression and intermale courtship. Species – and sex–specific behaviors such as courtship and aggression rely on an organism’s ability to reliably discriminate between species, sexes and social hierarchy of interacting partners, and adjust to the dynamic shifts in sensory and behavioral feedback cues. At the level of an individual organism, such behavioral flexibility is often achieved by modulating the strength and directionality of neural network outputs which endows a limited biological circuit the capacity to generate variable outputs and adds richness to the repertoire of behaviors it can display (Marder, 2012). The role of MBD proteins discussed in this dissertation highlights a mechanism that couples chromatin remodeling and OA neuromodulation in context-dependent decision-making processes

Abstracts of Papers, 88th Annual Meeting of the Virginia Academy of Science

Full list of Abstracts from the 88th Annual Meeting of the Virginia Academy of Science, May 20 - 21, 2010, James Madison University Harrisonburg, V

Language impairment and colour categories

Goldstein (1948) reported multiple cases of failure to categorise colours in patients that he termed amnesic or anomic aphasics. these patients have a particular difficulty in producing perceptual categories in the absence of other aphasic impairments. we hold that neuropsychological evidence supports the view that the task of colour categorisation is logically impossible without labels