Canonical circuits for cerebellar learning


  • Prof Michael Hausser

    University College London, United Kingdom

Project summary

Efficient learning and adaptation to changes in the environment are crucial for survival. The cerebellum is thought to contribute to learning by helping the brain to evaluate predictions about the consequences of actions and enabling appropriate corrections to be made. We recently discovered that the cerebellum signals information about rewards, complementing previous work showing that the cerebellum uses prediction errors to correct actions. In this project we will identify the circuits which drive these reward and error signals in the cerebellum, show how they are engaged and combined during learning and adaptation, and how these cerebellar signals instruct the rest of the brain. By recording from all cell types in the cerebellar circuit we will identify where changes take place during learning, and use new tools for light-activated control of neural circuits to manipulate learning in a precise way, allowing us to "correct" erroneous patterns of activity to improve learning.