Neural dynamics of emotion and cognition: from trajectories to underlying neural geometry

TL;DR

This paper advocates for a dynamic, geometry-based framework to understand the neural underpinnings of emotion and cognition, emphasizing the importance of neural trajectories and structure over static causation.

Contribution

It introduces a novel research program focusing on neural dynamics and geometry, integrating computational tools to better understand complex brain functions.

Findings

Proposes analyzing neural trajectories and their geometry.

Highlights the importance of dynamic multivariate brain data.

Calls for a shift from static causation to dynamic structure analysis.

Abstract

This paper describes the outlines of a research program for understanding the cognitive-emotional brain, with an emphasis on the issue of dynamics: How can we study, characterize, and understand the neural underpinnings of cognitive-emotional behaviors as inherently dynamic processes? The framework embraces many of the central themes developed by Steve Grossberg in his extensive body of work in the past 50 years. By embracing head on the leitmotifs of dynamics, decentralized computation, emergence, selection and competition, and autonomy, it is proposed that a science of the mind-brain can be developed that is built upon a solid foundation of understanding behavior while employing computational and mathematical tools in an integral manner. A key implication of the framework is that standard ways of thinking about causation are inadequate when unravelling the workings of a complex system such as the brain. Instead, it is proposed that researchers should focus on determining the dynamic multivariate structure of brain data. Accordingly, central problems become to characterize the dimensionality of neural trajectories, and the geometry of the underlying neural space. 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.