An internal model of self-motion based on inertial signals

The question of how the central nervous system can distinguish tilt with respect to gravity from inertial acceleration due to translation in a horizontal plane using vestibular information has long been debated by the scientific community over the past ten years. Recently, it was hypothesized that such discrimination may be based on the multisensory integration of information provided by the otolith organs and the semicircular canals. Some evidence of such processing was found in the neural activity of cells in the fastigial nuclei and vestibular nuclei. To investigate the ability of the central nervous system to build an internal model of self motion based on vestibular signals, we developed an artificial vestibular sensor composed of accelerometers and gyroscopes providing movement data of the same nature as that transduced by the otoliths and canals, respectively. Here we show that the processing of these signals based on the multisensory integration hypothesis can be successfully used to discriminate tilt from translation and that the internal model based on such processing can successfully track angular and linear displacements over short periods of time