Our research goal is to understand the neural circuit mechanisms & computations that underlie predictive processing in the brain

Our field of research is known as predictive processing. Predictive processing is a theory of brain function that assumes the brain contains an internal model of the world, which constantly generates and updates predictions about the world.

Impaired predictive processing is thought to underlie hallucinations and social disconnection in neurological disorders such as schizophrenia and autism. It can also lead to motor disorders, such as impaired movement adaptation following sensorimotor perturbations.


Our vision is to understand the circuit mechanisms and computations that allow the brain to process prediction signals. We strive to apply our findings to the treatment of psychiatric disorders such as schizophrenia and autism, as well as motor disorders.


But how does predictive processing happen in the brain?

Prediction signals are observed in both the cerebellum and cortex. Therefore, we believe both regions contain an internal model of the world. This raises the following key questions:

  1. How do cortical and cerebellar predictions signals interact with each other to support cognitive and sensorimotor behavior?

  2. How distinct are the cerebellar and cortical internal models of the world?

  3. What computations and cell-type specific circuit mechanisms underlie predictive processing in each region?


To address these questions, we perform the following experiments in awake, behaving mice:

  1. Large-scale recording of neural activity, using electrophysiological and optical methods

  2. Optogenetics to manipulate neural activity

  3. Behavioral paradigms in rodents

  4. Computational methods, such as machine learning and modeling of neural and behavioral data.