The dynamics of neural activation variables

Abstract

This paper presents a comprehensive and detailed analysis of the elementary building blocks of neurally inspired architectures for cognitive robotics. It provides a brief outline of the fundamental principles by which biological nervous systems link to the environment in terms of perception, cognition, and behavior. We describe a class of dynamic neural activation variable based on these principles. We show that these dynamic neurons have the appropriate stability properties.Adding even simple connections between a small number of nodes is sufficient to constitute systems that make important decisions. Going through these mechanisms in detail, this paper should facilitate the design of neurally inspired architectures for behavior generation in robotic agents.