Predictive coding of Natural Self-Motion: Implications for Perception & Action

Integrating sensory with motor signals during voluntary behavior is essential for distinguishing stimuli that are a consequence of intended actions from those that are externally generated. This ability enables the brain to flexibly fine-tune motor actions based on sensory feedback, a computation necessary for subjective awareness of the effects of movements. The lecture will explore the neural circuits that perform this computation, highlighting the cerebellum's role in building predictive models of voluntary movement as individuals explore the world. Our findings advance understanding of how the brain's predictions of self-motion learned, adapted, and flexibly implemented in daily life.

Integrating sensory with motor signals during voluntary behavior is essential for distinguishing stimuli that are a consequence of intended actions from those that are externally generated. This ability enables the brain to flexibly fine-tune motor actions based on sensory feedback, a computation necessary for subjective awareness of the effects of movements. The lecture will explore the neural circuits that perform this computation, highlighting the cerebellum's role in building predictive models of voluntary movement as individuals explore the world. Our findings advance understanding of how the brain's predictions of self-motion learned, adapted, and flexibly implemented in daily life.