Visual navigation in ants

Les remarquables capacités de navigation des insectes nous prouvent à quel point ces " mini-cerveaux " peuvent produire des comportements admirablement robustes et efficaces dans des environnements complexes. En effet, être capable de naviguer de façon efficace et autonome dans un environnement parfois hostile (désert, forêt tropicale) sollicite l'intervention de nombreux processus cognitifs impliquant l'extraction, la mémorisation et le traitement de l'information spatiale préalables à une prise de décision locomotrice orientée dans l'espace. Lors de leurs excursions hors du nid, les insectes tels que les abeilles, guêpes ou fourmis, se fient à un processus d'intégration du trajet, mais également à des indices visuels qui leur permettent de mémoriser des routes et de retrouver certains sites alimentaires familiers et leur nid. L'étude des mécanismes d'intégration du trajet a fait l'objet de nombreux travaux, par contre, nos connaissances à propos de l'utilisation d'indices visuels sont beaucoup plus limitées et proviennent principalement d'études menées dans des environnements artificiellement simplifiés, dont les conclusions sont parfois difficilement transposables aux conditions naturelles. Cette thèse propose une approche intégrative, combinant 1- des études de terrains et de laboratoire conduites sur deux espèces de fourmis spécialistes de la navigation visuelle (Melophorus bagoti et Gigantiops destructor) et 2- des analyses de photos panoramiques prisent aux endroits où les fourmis naviguent qui permettent de quantifier objectivement l'information visuelle accessible à l'insecte. Les résultats convergents obtenus sur le terrain et au laboratoire permettent de montrer que, chez ces deux espèces, les fourmis ne fragmentent pas leur monde visuel en multiples objets indépendants, et donc ne mémorisent pas de 'repères visuels' ou de balises particuliers comme le ferait un être humain. En fait, l'efficacité de leur navigation émergerait de l'utilisation de paramètres visuels étendus sur l'ensemble de leur champ visuel panoramique, incluant repères proximaux comme distaux, sans les individualiser. Contre-intuitivement, de telles images panoramiques, même à basse résolution, fournissent une information spatiale précise et non ambiguë dans les environnements naturels. Plutôt qu'une focalisation sur des repères isolés, l'utilisation de vues dans leur globalité semble être plus efficace pour représenter la complexité des scènes naturelles et être mieux adaptée à la basse résolution du système visuel des insectes. Les photos panoramiques enregistrées peuvent également servir à l'élaboration de modèles navigationnels. Les prédictions de ces modèles sont ici directement comparées au comportement des fourmis, permettant ainsi de tester et d'améliorer les différentes hypothèses envisagées. Cette approche m'a conduit à la conclusion selon laquelle les fourmis utilisent leurs vues panoramiques de façons différentes suivant qu'elles se déplacent en terrain familier ou non. Par exemple, aligner son corps de manière à ce que la vue perçue reproduise au mieux l'information mémorisée est une stratégie très efficace pour naviguer le long d'une route bien connue ; mais n'est d'aucune efficacité si l'insecte se retrouve en territoire nouveau, écarté du chemin familier. Dans ces cas critiques, les fourmis semblent recourir à une seconde stratégie qui consiste à se déplacer vers les régions présentant une ligne d'horizon plus basse que celle mémorisée, ce qui généralement conduit vers le terrain familier. Afin de choisir parmi ces deux différentes stratégies, les fourmis semblent tout simplement se fier au degré de familiarisation avec le panorama perçu. Cette thèse soulève aussi la question de la nature de l'information visuelle mémorisée par les insectes. Le modèle du " snapshot " qui prédomine dans la littérature suppose que les fourmis mémorisent une séquence d'instantanés photographiques placés à différents points le long de leurs routes. A l'inverse, les résultats obtenus dans le présent travail montrent que l'information visuelle mémorisée au bout d'une route (15 mètres) modifie l'information mémorisée à l'autre extrémité de cette même route, ce qui suggère que la connaissance visuelle de l'ensemble de la route soit compactée en une seule et même représentation mémorisée. Cette hypothèse s'accorde aussi avec d'autres de nos résultats montrant que la mémoire visuelle ne s'acquiert pas instantanément, mais se développe et s'affine avec l'expérience répétée. Lorsqu'une fourmi navigue le long de sa route, ses récepteurs visuels sont stimulés de façon continue par une scène évoluant doucement et régulièrement au fur et à mesure du déplacement. Mémoriser un pattern général de stimulations, plutôt qu'une série de " snapshots " indépendants et très ressemblants les uns aux autres, constitue une hypothèse parcimonieuse. Cette hypothèse s'applique en outre particulièrement bien aux modèles en réseaux de neurones, suggérant sa pertinence biologique. Dans l'ensemble, cette thèse s'intéresse à la nature des perceptions et de la mémoire visuelle des fourmis, ainsi qu'à la manière dont elles sont intégrées et traitées afin de produire une réponse navigationnelle appropriée. Nos résultats sont aussi discutés dans le cadre de la cognition comparée. Insectes comme vertébrés ont résolu le même problème qui consiste à naviguer de façon efficace sur terre. A la lumière de la théorie de l'évolution de Darwin, il n'y a 'a priori' aucune raison de penser qu'il existe une forme de transition brutale entre les mécanismes cognitifs des différentes espèces animales. Le fossé marqué entre insectes et vertébrés au sein des sciences cognitives pourrait bien être dû à des approches différentes plutôt qu'à de vraies différences ontologiques. Historiquement, l'étude de la navigation de l'insecte a suivi une approche de type 'bottom-up' qui recherche comment des comportements apparemment complexes peuvent découler de mécanismes simples. Ces solutions parcimonieuses, comme celles explorées dans cette thèse, peuvent fournir de remarquables hypothèses de base pour expliquer la navigation chez d'autres espèces animales aux cerveaux et comportements apparemment plus complexes, contribuant ainsi à une véritable cognition comparée.Navigating efficiently in the outside world requires many cognitive abilities like extracting, memorising, and processing information. The remarkable navigational abilities of insects are an existence proof of how small brains can produce exquisitely efficient, robust behaviour in complex environments. During their foraging trips, insects, like ants or bees, are known to rely on both path integration and learnt visual cues to recapitulate a route or reach familiar places like the nest. The strategy of path integration is well understood, but much less is known about how insects acquire and use visual information. Field studies give good descriptions of visually guided routes, but our understanding of the underlying mechanisms comes mainly from simplified laboratory conditions using artificial, geometrically simple landmarks. My thesis proposes an integrative approach that combines 1- field and lab experiments on two visually guided ant species (Melophorus bagoti and Gigantiops destructor) and 2- an analysis of panoramic pictures recorded along the animal's route. The use of panoramic pictures allows an objective quantification of the visual information available to the animal. Results from both species, in the lab and the field, converged, showing that ants do not segregate their visual world into objects, such as landmarks or discrete features, as a human observers might assume. Instead, efficient navigation seems to arise from the use of cues widespread on the ants' panoramic visual field, encompassing both proximal and distal objects together. Such relatively unprocessed panoramic views, even at low resolution, provide remarkably unambiguous spatial information in natural environment. Using such a simple but efficient panoramic visual input, rather than focusing on isolated landmarks, seems an appropriate strategy to cope with the complexity of natural scenes and the poor resolution of insects' eyes. Also, panoramic pictures can serve as a basis for running analytical models of navigation. The predictions of these models can be directly compared with the actual behaviour of real ants, allowing the iterative tuning and testing of different hypotheses. This integrative approach led me to the conclusion that ants do not rely on a single navigational technique, but might switch between strategies according to whether they are on or off their familiar terrain. For example, ants can recapitulate robustly a familiar route by simply aligning their body in a way that the current view matches best their memory. However, this strategy becomes ineffective when displaced away from the familiar route. In such a case, ants appear to head instead towards the regions where the skyline appears lower than the height recorded in their memory, which generally leads them closer to a familiar location. How ants choose between strategies at a given time might be simply based on the degree of familiarity of the panoramic scene currently perceived. Finally, this thesis raises questions about the nature of ant memories. Past studies proposed that ants memorise a succession of discrete 2D 'snapshots' of their surroundings. Contrastingly, results obtained here show that knowledge from the end of a foraging route (15 m) impacts strongly on the behaviour at the beginning of the route, suggesting that the visual knowledge of a whole foraging route may be compacted into a single holistic memory. Accordingly, repetitive training on the exact same route clearly affects the ants' behaviour, suggesting that the memorised information is processed and not 'obtained at once'. While navigating along their familiar route, ants' visual system is continually stimulated by a slowly evolving scene, and learning a general pattern of stimulation rather than storing independent but very similar snapshots appears a reasonable hypothesis to explain navigation on a natural scale; such learning works remarkably well with neural networks. Nonetheless, what the precise nature of ants' visual memories is and how elaborated they are remain wide open question. Overall, my thesis tackles the nature of ants' perception and memory as well as how both are processed together to output an appropriate navigational response. These results are discussed in the light of comparative cognition. Both vertebrates and insects have resolved the same problem of navigating efficiently in the world. In light of Darwin's theory of evolution, there is no a priori reason to think that there is a clear division between cognitive mechanisms of different species. The actual gap between insect and vertebrate cognitive sciences may result more from different approaches rather than real differences. Research on insect navigation has been approached with a bottom-up philosophy, one that examines how simple mechanisms can produce seemingly complex behaviour. Such parsimonious solutions, like the ones explored in the present thesis, can provide useful baseline hypotheses for navigation in other larger-brained animals, and thus contribute to a more truly comparative cognition

Neural systems supporting navigation

Highlights: • Recent neuroimaging and electrophysiology studies have begun to shed light on the neural dynamics of navigation systems. • Computational models have advanced theories of how entorhinal grid cells and hippocampal place cells might serve navigation. • Hippocampus and entorhinal cortex provide complementary representations of routes and vectors for navigation. Much is known about how neural systems determine current spatial position and orientation in the environment. By contrast little is understood about how the brain represents future goal locations or computes the distance and direction to such goals. Recent electrophysiology, computational modelling and neuroimaging research have shed new light on how the spatial relationship to a goal may be determined and represented during navigation. This research suggests that the hippocampus may code the path to the goal while the entorhinal cortex represents the vector to the goal. It also reveals that the engagement of the hippocampus and entorhinal cortex varies across the different operational stages of navigation, such as during travel, route planning, and decision-making at waypoints

Urban Drone Navigation: Autoencoder Learning Fusion for Aerodynamics

Drones are vital for urban emergency search and rescue (SAR) due to the challenges of navigating dynamic environments with obstacles like buildings and wind. This paper presents a method that combines multi-objective reinforcement learning (MORL) with a convolutional autoencoder to improve drone navigation in urban SAR. The approach uses MORL to achieve multiple goals and the autoencoder for cost-effective wind simulations. By utilizing imagery data of urban layouts, the drone can autonomously make navigation decisions, optimize paths, and counteract wind effects without traditional sensors. Tested on a New York City model, this method enhances drone SAR operations in complex urban settings.Comment: 47 page

The world is not flat: Can people reorient using slope?

Studies of spatial representation generally focus on flat environments and visual input. However, the world is not flat, and slopes are part of most natural environments. In a series of 4 experiments, we examined whether humans can use a slope as a source of allocentric, directional information for reorientation. A target was hidden in a corner of a square, featureless enclosure tilted at a 5° angle. Finding it required using the vestibular, kinesthetic, and visual cues associated with the slope gradient. In Experiment 1, the overall sample performed above chance, showing that slope is sufficient for reorientation in a real environment. However, a sex difference emerged; men outperformed women by 1.4 SDs because they were more likely to use a slope-based strategy. In Experiment 2, attention was drawn to the slope, and participants were prompted to rely on it to solve the task; however, men still outperformed women, indicating a greater ability to use slope. In Experiment 3, we excluded the possibility that women\u27s disadvantage was due to wearing heeled footwear. In Experiment 4, women required more time than men to identify the uphill direction of the slope gradient; this suggests that, in a bottom-up fashion, a perceptual or attentional difficulty underlies women\u27s disadvantage in the ability to use slope and their decreased reliance on this cue. Overall, a bi-coordinate representation was used to find the goal: The target was encoded primarily with respect to the vertical axis and secondarily with respect to the orthogonal axis of the slope

Deterministic Graph Exploration with Advice

We consider the task of graph exploration. An $n$-node graph has unlabeled nodes, and all ports at any node of degree $d$ are arbitrarily numbered $0,\dots, d-1$. A mobile agent has to visit all nodes and stop. The exploration time is the number of edge traversals. We consider the problem of how much knowledge the agent has to have a priori, in order to explore the graph in a given time, using a deterministic algorithm. This a priori information (advice) is provided to the agent by an oracle, in the form of a binary string, whose length is called the size of advice. We consider two types of oracles. The instance oracle knows the entire instance of the exploration problem, i.e., the port-numbered map of the graph and the starting node of the agent in this map. The map oracle knows the port-numbered map of the graph but does not know the starting node of the agent. We first consider exploration in polynomial time, and determine the exact minimum size of advice to achieve it. This size is $\log\log\log n -\Theta(1)$, for both types of oracles. When advice is large, there are two natural time thresholds: $\Theta(n^2)$ for a map oracle, and $\Theta(n)$ for an instance oracle, that can be achieved with sufficiently large advice. We show that, with a map oracle, time $\Theta(n^2)$ cannot be improved in general, regardless of the size of advice. We also show that the smallest size of advice to achieve this time is larger than $n^\delta$, for any $\delta <1/3$. For an instance oracle, advice of size $O(n\log n)$ is enough to achieve time $O(n)$. We show that, with any advice of size $o(n\log n)$, the time of exploration must be at least $n^\epsilon$, for any $\epsilon <2$, and with any advice of size $O(n)$, the time must be $\Omega(n^2)$. We also investigate minimum advice sufficient for fast exploration of hamiltonian graphs

Making a stronger case for comparative research to investigate the behavioral and neurological bases of three-dimensional navigation

The rich diversity of avian natural history provides exciting possibilities for comparative research aimed at understanding three-dimensional navigation. We propose some hypotheses relating differences in natural history to potential behavioral and neurological adaptations possessed by contrasting bird species. This comparative approach may offer unique insights into some of the important questions raised by Jeffery et al