Efficient mixed representation of active and passive motion in the mouse visual thalamus during natural behaviour

During natural behaviour, changes in the visual scene are largely driven by the subject’s own movements, which can be actively generated (e.g., walking) or passively imposed by external forces (e.g., riding a vehicle). How the visual system represents such active and passive motion components is poorly understood. To address these questions, we developed an assay to dissect the motion of freely moving mice into active and passive components and to study its influence upon neural activity in the dorsal lateral geniculate nucleus (dLGN) and adjacent regions. Chronically implanted mice were placed in an arena where they actively moved; at irregular intervals, the arena was tilted, resulting in passive movement. We then used 3D tracking to decompose mouse head motion into active and passive components. We observed widespread responses to tilt events in dLGN, which persisted in darkness. Light-responsive units exhibited mixed selectivity for active and passive motion, primarily encoding the speed of self-motion irrespectively of its causes. However, individual neurons varied in their relative tuning to active versus passive components, allowing partial separation at the population level. Furthermore, a decoding analysis showed that population activity decorrelated active and passive head motion signals by representing their leading principal components. Together, these results indicate that, during natural behaviour, the visual thalamus takes advantage of the coupled dynamics of active and passive movements to encode an efficient, low-dimensional representation of the subject’s motion.