How does the brain learn from experience, make predictions about how to behave, and remember what it has learned? 

Research at SWC focuses on understanding different types of learning including statistical learning, where the brain finds and exploits meaningful patterns in the environment, and reinforcement learning, where the brain makes predictions based on previous outcomes. 

Our research also focuses on the theory of deep learning, a class of artificial neural network models that take inspiration from the brain. Neuroscientists at SWC are working closely with GCNU, to develop better learning algorithms, a fundamental goal in machine learning that has proven essential in real world applications.

Read more about SWC's Mission

Research News

• Deciphering the brain’s prediction machine

• Structured exploration allows biological brains to learn faster than AI

• Learning to learn: sacrificing short-term reward for long-term gain

• Neuroscientists demonstrate flexibility of innate behaviour

• Mice choose best escape route without ever experiencing threat

• Does the brain recycle mechanisms for learning and attention?

• Equipping artificial intelligence with motivation

• Instinct and learning: two sides of the same coin

• Disentangling the interneuron web of learning