Abstract
How can we study, characterize, and understand the neural underpinnings of cognitive-emotional behaviors as inherently dynamic processes? In the past 50 years, Stephen Grossberg has developed a research program that embraces the themes of dynamics, decentralized computation, emergence, selection and competition, and autonomy. The present paper discusses how these principles can be heeded by experimental scientists to advance the understanding of the brain basis of behavior. It is suggested that a profitable way forward is to focus on investigating the dynamic multivariate structure of brain data. Accordingly, central research problems involve characterizing "neural trajectories" and the associated geometry of the underlying "neural space." Finally, it is argued that, at a time when the development of neurotechniques has reached a fever pitch, neuroscience needs to redirect its focus and invest comparable energy in the conceptual and theoretical dimensions of its research endeavor. Otherwise we run the risk of being able to measure "every atom" in the brain in a theoretical vacuum.