Visual Coding of Objects During Free Movement

About the project

About the Project When an object moves across a visual field, its cause is ambiguous: the motion could be self-generated by observer locomotion, or externally driven by an independent object. Disentangling these sensory streams is a computational prerequisite for spatial awareness and navigation. How the visual system encodes and interprets these distinct informational streams remains a central question in systems neuroscience. Previous work, including pioneering studies from the academic partner, mapped these mechanisms using head-fixed rodent virtual reality (VR). While powerful for visual control, head-fixation disrupts the integration of vestibular cues, and thus our understanding of motion processing in the real world remains limited. We propose to investigate the neural mechanisms of visual motion processing in freely moving animals. To achieve this, we must present identical visual stimuli under distinct causal conditions: one tightly coupled to the animal's self-movement, and another driven by an external source. Aims Establish a closed-loop Augmented Reality (AR) environment for freely moving mice: Develop an immersive arena that updates visual stimuli in real-time based on the animal's position. Develop self- and externally-controlled stimulus scenarios: Design matched paradigms where the same stimulus displacement is generated either by the animal’s locomotion or via independent, external factors. Record and analyze neural activity across mouse visual areas: Employ high-density electrophysiology to investigate how cortical neurons multiplex self-motion signals and external visual dynamics. The key hypothesis we will be testing is that visual areas in the brain, particularly primary visual cortex and superior colliculus, can distinguish between visual motion caused by self-movement and externally- generated movements. Partnership & Training Project feasibility is enabled by the collaboration between NeuroGEARS Ltd and the Saleem Lab, who jointly developed the BonVision open-source VR platform. This proposal builds upon that software foundation, offering a unique training environment at the intersection of a pioneering biotech SME and a world-class laboratory. The student will gain an exceptional skillset. From the Saleem Lab, they will master in vivo methodologies, including chronic Neuropixels 2.0 implantations, high-density recordings, and miniature eye-tracking hardware. Through NeuroGEARS, they will acquire industry competencies in real-time closed-loop programming and systems engineering from a technical side, and curriculum design and instructional delivery for educational outreach. Between the two partners, they will also develop the highly transferrable skill of large-scale data analysis. Importance Systems neuroscience has long been restricted by a trade-off between experimental control (head-fixation) and ecological validity (free movement). This project breaks that paradigm by creating a closed-loop AR system to investigate whether the brain dynamically switches between reference frames, offering foundational insights for biomimetic robotics.

Research areas