Every decision and behavior is haunted by uncertainty, introduced by the noisy and ambiguous nature of the world that surrounds us. Despite this, we make such decisions with seeming ease. The goal of the Drugowitsch Lab is to understand the fundamental computations and their neurobiological implementations that allow the nervous system to support such efficient behavior.

By using tools from artificial intelligence and neuroscience research, we approach this goal by developing theories about how the networks of neurons in our brains are able to infer, represent, and process the state of the world, and how this processing leads to decisions we make on a daily basis.

Our current research focuses on decisions based on evidence we directly observe, rather than memorized knowledge. We have previously shown that, in this context, decision-makers are able to trade off the time they contemplate such decisions with their accuracy in a close-to-optimal manner. We are further asking how decision strategies change once these decisions are between options of different intrinsic values, and what might be the computations involved to make up one’s mind about these values. In the close future, we plan on extending our investigations not only to decisions that require taking into account the more complex structure of every-day visual scenes, but also to address behavior of higher dimensions, such as spatial navigation under uncertainty.