MPRG NeuroCode | Neural and Computational Basis of Learning, Memory and Decision Making

Head: Nicolas W. Schuck

Introduction

Our group’s mission is to unravel the mechanisms through which the human brain uses past experiences to inform our choices. Our research primarily concentrates on investigating neural representations and replay of past experiences with fMRI, and on developing computational approaches that model how these elements shape the decisions we make. Our approach to understanding these processes is inspired by the principles of (deep) reinforcement learning algorithms, enabling us to draw valuable insights about the parallels between human cognitive processes and AI. We also apply our research to cognitive aging and psychiatric disorders. Ultimately, our research aims to uncover fundamental insights into the nature of human cognition and neural computation, which we hope might lead to innovative therapies in the future.

Our research is structured into three areas: (1) learning representations of values and states, (2) neural replay, and (3) computational psychiatry and aging. We have published over 20 papers in highly competitive journals related to these topics over the past reporting period, in addition to nine preprints that are currently being considered for publication. In the Research section, we describe exemplary projects for each area. To provide an up-to-date account of our activities, we present a mix of published and ongoing projects.