PhD Position Neuronal Networks Underlying Learning and Decision-Making: Dynamics and Analysis

Understanding the mechanisms of human cognition, e.g. learning and decision-making, is among the key components behind developments of efficient human-in-the-loop algorithms as well as advances in human cognitive health. Cognitive abilities are rooted in the activities of dynamic networks of neurons. A central topic in this domain is to understand the relations between the cognitive functioning and the brain neuronal activities in particular in the light of dynamic changes in neuronal interactions. This project will consider system level modeling and analysis of dynamic neuronal networks whose activities form the underlying mechanisms of learning and decision-making. We will capitalize mainly on the tools from nonlinear and adaptive control theory. Physics-based and data-driven approaches will be employed for the dynamical modeling part. The outcome of this project, in collaboration with cognitive neuroscientists and AI experts, will contribute to mechanistic understandings of human cognition as well as advances in artificial learning algorithms.