Thèse Circuits Neuronaux Sous-Jacents aux Sequences d'Action Flexibles H/F - 75

Établissement : Université Paris-Saclay GS Life Sciences and Health
École doctorale : Signalisations et Réseaux Intégratifs en Biologie
Laboratoire de recherche : Institut des Neurosciences Paris-Saclay
Direction de la thèse : Tihana JOVANIC ORCID 0000000205258620
Début de la thèse : 2026-10-01
Date limite de candidature : 2026-05-05T23:59:59

De nombreux comportements sont organisés en séquences d'actions individuelles. Le système nerveux doit donc être capable de contrôler les transitions entre les actions et d'établir l'ordre des actions dans les séquences. L'ordre des actions dans la séquence peut dépendre d'informations contextuelles ou de l'état interne. Bien que des modèles théoriques expliquant comment le système nerveux peut générer des séquences d'actions flexibles aient été proposés, les circuits neuronaux qui implémente la génération de séquence dans les systèmes nerveux réels reste difficile à cerner. Nous proposons de tirer parti d'un modèle puissant d'analyse des circuits, la larve de drosophile, afin de déterminer l'architecture des circuits neuronaux capables de générer des séquences comportementales flexibles d'actions défensives en réponse à des signaux aversifs. Nous combinerons la connectomique par microscopie électronique et l'imagerie fonctionnelle avec la manipulation de cellules individuelles et le tracking et la classification automatisés des comportements afin de cartographier les motifs des circuits qui contrôlent les transitions flexibles entre les actions d'une séquence. Nous étudierons comment ces séquences sont modulées par les états internes et l'information sensorielle contextuelle. La détermination des mécanismes des circuits neuronaux sous-jacents aux séquences d'actions flexibles chez la larve de drosophile, où nous pouvons relier la structure et la fonction des circuits neuronaux au niveau cellulaire et synaptique, permettra de mieux comprendre les mécanismes sous-jacents à la génération de séquences en général, y compris dans des systèmes plus complexes.

Movement is a key characteristic of animals, which enables individuals or groups to interact with the environment, other individuals or groups, and achieve a wide range of goals. These goals can vary from the essential, such as finding food, escaping predators or mating, to the more creative, such as playing music, dancing, or engaging in other forms of play . Many of these behaviors across the animal kingdom are organized in sequences. This implies that the nervous system needs to be able to set the order of the different actions in the sequence and also regulate the transitions between these actions: determine when one action ends and when another starts. How the order of actions in a sequence is implemented and how the transitions to the subsequent actions are controlled to ensure the progress of the sequences at the neural circuit level remain an open question. To generate action sequences the nervous system needs to regulate transitions from one action to the next and at the same time prevent reversals from later actions back to earlier ones to ensure orderly progression within a sequence. There are two main hypotheses that try to explain how the serial organization of actions in a sequence is established. One hypothesis suggests that modules that promote earlier actions in a sequence provide the excitation for the module that promote the following action. Probabilistic sequences, such as human typing or fly grooming, are better described by models that propose all actions in a sequence are readied in parallel and the order is established through gradients of excitation and winner-take-all competition. However, it has been difficult to determine the circuits that would implement sequences consistent with either of these models with cellular and synaptic resolution. In addition, how the type and dynamic of actions in the sequence depend on the context is also not understood. Indeed, to survive and thrive, animals must continuously adapt their locomotion actions to account for dynamic changes in their environment, as well as internal drives and motivations. Here again, the exact mechanism by which the contextual/state information affects sensorimotor circuits and how this information is integrated to produce to adjust locomotion and action sequences to the changes in the environment at different scales from single neurons and synapse to whole-body movement is not well understood. On one hand, in complex brains, it is challenging to map the circuitry from sensory inputs to motor outputs and monitoring activity with single neuron and muscle precision during behavior. We propose to fill this gap in a powerful model organism for neural circuit analysis: the Drosophila larva. Drosophila larvae are ideally suited for combining comprehensive, synaptic-resolution circuit mapping across the nervous system with targeted manipulation of uniquely identified circuit motifs at the individual neuron level, which makes it possible to establish a causal relationship between circuit structure and function brain-wide In addition, its semi-transparent cuticle and the well-characterized motor system makes it possible to monitor pattern of muscle activity using fluorescence during movement.

Aim 1) Characterize neuromuscular patterns underlying sequence transitions
Aim 2) Determine the neural architecture underlies the production of sequences How are longer
sequences (with more than to actions) controlled? What types of motifs are involved?
Aim 3) Determine the mechanisms of context/state dependent flexibility of sequences