Title:

Decoding Decision-Making Dynamics

Abstract

A challenge in studying decision-making is that the process is subjective and unobservable. Techniques pioneered in the field of brain-computer interfaces offer a potential solution. Our work has applied these techniques to understand how prefrontal cortex enables optimal decision-making. Population-level decoding allows us to measure the dynamics of decision-making and examine how those dynamics are translated into action—cortical oscillations co-ordinate firing rate dynamics between brain areas. Closed-loop control enables us to perturb decision-making dynamics and demonstrate the necessity of orbitofrontal-hippocampal theta oscillations. Taken together, results show the complexity of the neural code that supports cognitive processes.