Thèse Voir en Mouvement Comment les Circuits Visuels Exploitent nos Mouvements pour Construire une Représentation Stable du Monde 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 : Guy BOUVIER ORCID 0000000261607186
Début de la thèse : 2026-10-01
Date limite de candidature : 2026-05-01T23:59:59

Lorsque nous nous déplaçons, nos yeux et notre tête bougent sans cesse, pourtant notre expérience visuelle demeure stable. Cette stabilité perceptive exige que le cerveau distingue les signaux visuels causés par nos propres mouvements de ceux reflétant les changements dans l'environnement. Les mécanismes neuronaux qui sous-tendent cette intégration par les circuits cortico-thalamiques restent cependant mal compris. Les mouvements de tête volontaires et imposés empruntent des voies distinctes qui semblent converger vers une même structure : le pulvinar thalamus. Les rotations imposées y transitent via les afférences vestibulaires, tandis que les rotations volontaires recrutent les aires motrices, elles aussi connectées au pulvinar. Grâce à des enregistrements longitudinaux utilisant des électrodes à forte densité de canaux et de l'imagerie biphotonique chez la souris libre de ses mouvements, nous établirons comment le pulvinar intègre ces signaux, comment ces circuits transforment les représentations visuelles. Ce projet révèlera les mécanismes permettant une vision stable durant le mouvement.

The construction of a stable spatial representation of the external world is fundamental to an organism's survival. Yet sensory inputs are acquired through organs in near-continuous mo-tion, creating a fundamental challenge: the visual system must contend with constant eye and head movements that shift images on the retina, while interpreting motion of objects in the external world. To detect head motion, the brain relies on the motor system and on the vestibular system-sensory organs in the inner ear that signal head motion. Therefore, to ac-curately interpret the visual world, the brain must integrate retinal signals with self-motion information. Understanding these mechanisms is essential not only for basic neuroscience but also for insights into disorders where sensory-motor integration is disrupted, such as schizophrenia and autism spectrum disorders, where patients exhibit atypical responses in distinguishing the sensory consequences of their own actions from externally-caused sen-sory events.
The first cortical stage of visual perception, primary visual cortex (V1), represents an ideal entry point for investigating how head motion impacts visual processing. V1 neurons in mice respond to both eye movements and externally- or self-generated head movements, even in the dark. Remarkably, recent evidence reveals that V1 employs a largely invariant code for head movement: decoders trained on externally-imposed rotations accurately pre-dict head angular velocity during self-generated movements, suggesting V1 constructs a uni-fied representation despite fundamentally different movement origins. However, the neuro-nal circuits and mechanisms enabling V1 to achieve this unification remain largely unk-nown.
Critically, the circuits mediating head motion differ fundamentally between self- versus ex-ternally-generated head turns. Passive (externally-imposed) rotations engage vestibular-cerebellar pathways-vestibular organs detect the imposed rotation and trigger compensato-ry eye movements (vestibulo-ocular reflex) that stabilize gaze. These signals likely reach pulvinar thalamus through deep cerebellar nuclei (DCN). In contrast, active (self-initiated) gaze shifts combine voluntary head movements with saccadic eye movements-a coordi-nated motor program that requires secondary motor cortex (M2). M2 is dispensable for V1 modulation during passive rotations but essential during active turns, likely through direct M2 projections to lateral posterior thalamus (LP, mouse pulvinar). Both pathways may also engage higher visual areas (HVAs) and retrosplenial cortex (RSC), which could provide in-direct routes or additional contextual inputs, forming a complex cortico-thalamic loop.
This circuit organization raises a fundamental paradox: how do divergent vestibular-cerebellar and motor pathways, which convey different types of head movements accompa-nied by distinct eye movement patterns, give rise to V1's unified head movement repre-sentation? And how does this unified code enable V1 to distinguish visual motion caused by self-motion from motion caused by moving objects in the external world? Resolving this pa-radox requires addressing three complementary questions: (1) Circuit architecture - Do ves-tibular-cerebellar and motor pathways converge at the thalamus, at cortical intermediates such as HVAs and RSC, or remain segregated until reaching V1? (2) Computational trans-formations - How do these pathways propagate and transform self-motion signals, and does V1 inherit a unified representation from upstream areas or actively normalize divergent in-puts? (3) Causal contributions - Which thalamo-cortical and cortico-cortical pathways are necessary for V1's context-invariant coding, and how do these pathways interact to enable stable visual perception across both externally- and self-generated movements?

This project seeks to illuminate how cortico-thalamic circuits integrate self-motion signals with visual information to sustain stable perception of the world. Our preliminary findings reveal a striking paradox: V1 encodes head movement through a remarkably context-invariant code - whether that movement is self-generated (active) or externally imposed via servo motor (passive). Yet active and passive head movements likely engage fundamen-tally different upstream pathways: passive head rotations signal through vestibular-cerebellar circuits, while self-generated head rotation recruit motor-related cortical areas, such as the secondary motor cortex (M2). How do these divergent pathways give rise to V1's unified representation? We will address this question through complementary aims that leverage miniaturized two-photon imaging to track neurons and their projections longi-tudinally across passive and active conditions.