Wako Yoshida

My research addresses the computational neuroscience of human cognitive decision making and social interaction, with a particular focus on the function of the prefrontal cortex.

Every day we try our best to make optimal decisions, but the information we get from our environment is often uncertain and incomplete. In machine learning, these situations are referred to as partially observable decision-making problems, in which the true (or hidden) state of the world cannot be directly observed. Instead, we can only estimate the hidden state of the world using available observations, and make decisions based on our inferred 'beliefs'. I’m studying the mechanisms by which uncertainty is resolved and beliefs constructed in the brain.

Another especially interesting type of cognitive decision-making problem occurs in social communication, as the ability to optimise mutual interactions requires the ability to read each others’ minds. My previous work probes some of the complexities of how Theory of Mind is achieved in the brain, and at the moment I am studying human brain activity during group decision-making tasks, including 'hyper-scanning' two subjects as they interact (cooperate) to solve a task together in separate fMRI scanners.