CogniGron Seminar: Alessio Franci (University of Liège) - "Excitable decision-making"

Understanding how the functional scale of cognition and the cellular scale of excitable neuronal activity are related is a fundamental question of neuroscience with important implications for artificial intelligence, robotics, and neuromorphic engineering applications.

I propose that this question can be addressed by focusing on decision-making as a universal and evolutionary conserved cognitive function and by using mathematical modeling grounded in control and bifurcation theory. Excitability can be understood as the minimal dynamical behavior needed to provide nonlinear signal-processing systems, modeling single neurons, neuronal circuits or networks, with adaptive decision-making capabilities. More precisely, excitability emerges as the synthesis of two defining properties of adaptive decision-making: the existence of a tunable threshold that determines the making of a decision and the existence of a reset mechanism that allows returning to a neutral decision state and the making of new decisions. The derived theoretical framework provides both new modeling and design tools to understand flexible cognition and reproducing it in artificial machines.