TY - JOUR TI - A unified internal model theory to resolve the paradox of active versus passive self-motion sensation AU - Laurens, Jean AU - Angelaki, Dora E A2 - Glasauer, Stefan VL - 6 PY - 2017 DA - 2017/10/18 SP - e28074 C1 - eLife 2017;6:e28074 DO - 10.7554/eLife.28074 UR - https://doi.org/10.7554/eLife.28074 AB - Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements. KW - bayesian KW - vestibular KW - efference copy KW - vestibular nucleus KW - cerebellum KW - internal model JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -