Effect of motor control on sensory coding in the awake, freely moving mouse

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Textbook knowledge of how neurons respond to sensory stimuli (visual, tactile etc) comes mainly from a passive experimental paradigm where sensory stimuli are presented to the immobilised sense organ of an anaesthetised animal (e.g., spot of light projected on the retina). However, most species actively seek information by active sensation - they coordinate motor control of their sense organs (e.g., eyes, hands, whiskers) with sensory processing. For example, during natural, sensory-guided actions such as tea-making, humans make coordinated movements of torso, hands and eyes. Studies of neural mechanisms in behaving rodents have revealed that the activity of neurons in the primary sensory areas of the cerebral cortex, classically considered to be purely sensory areas (V1, S1, A1), depends on motor state (running speed, whisker movement, pupil size). The surprising, new picture emerging from these findings is that sensation and action are integrated even in the brain's early sensory systems.Whilst the head-fixed preparation has important experimental benefits, it substantially limits the range of movements that the animal can make. Head-fixed mice can walk/run on a treadmill but this is just one of many elementary motor actions in the behavioural repertoire of freely moving mice; others include head rotations along different axes, rearing, body bending and elongation. These motor actions combine to generate a wide repertoire of behavioural motifs that cannot occur when under head-fixation. Thus, the question of exactly how sensory coding depends on motor state in early sensory systems remains unresolved.The ideal way to approach our objectives is to record neural activity from mice which are free to move so that they can exhibit as many different motor actions as possible. Our approach is to image the behaviour of mice as they explore objects with their whiskers, using a system of video cameras. We have recently developed powerful machine vision algorithms that can automatically extract the 3D pose of a mouse and the 3D shape of its whiskers. We have also recently established an electrophysiological system for state-of-the-art wireless recording of neural activity. Putting these methods together, we are ideally placed to contribute to the field.