Colloquium Artificial Intelligence - Michael Nunez, University of Amsterdam

Title:Estimating cognitive computation of decision-making in individuals with Neuro-Cognitive Measurement Models

Abstract:

To understand and estimate cognitive computational in individuals, we need, among other methods, simple models of cognition that collapse across complex brain dynamics. These models seek to find and estimate cognitive explanations of observed data that are potentially simple to understand. I discuss my work on extending existing Cognitive Measurement Models of task-behavior during simple decision making. Specifically I talk about extending these methods to Neuro-Cognitive Measurement Models that explain both neural and behavioral data. Our recent work advances a new framework that better assumes that cognition produces both choice-response times and noisy EEG measures (specifically Event-Related Potentials, ERPs) on single experimental trials. The framework relies on simulation-based methods to extract Bayesian posterior distributions of cognitive parameters with Artificial Neural Networks. These methods also allow the estimation of cognitive parameters in individuals that could not have been previously estimated with behavioral data alone. I discuss the future of these methods and why I think they are necessary for the fields of Cognitive Neuroscience and AI.