We study the biological basis of learning and decision making by monitoring, manipulating, and modeling neural activity

How do we remember something good and pursue it? How do we remember something bad and avoid it?
How do we make decisions and commit actions in complicated situations (e.g., things are uncertain)?
How do we recognize situations in a structured way (e.g., map) to achieve goals efficiently?
What anatomical and computational features of the brain make one species smarter than another species?
What are computational causes and consequences of brain disorders?
What can we learn about how the brain works from artificial intelligence?

We address these questions by monitoring and manipulating neuronal activities using advanced techniques. We use computational methods to understand how neural activity underlies cognition and behavior. By comparing neural activities across species (rodents and NHPs, including artificial neural network agents), we hope to understand how intelligence emerges (more info). Below is a selected summary of our scientific approaches.

If we figure out the essence of the brain, we may understand ourselves better - the origin of intelligence and consciousness. The fundamental understanding of reward-based learning and motivation will contribute to developing treatments of mental illness such as addiction and obsessive-compulsive disorder. Furthermore, we may apply the neural mechanisms of intelligent behaviors to improve current artificial intelligence technologies.

Topics related to what we do in the lab.