Bridging the information and dynamics attributes of neural activities

TL;DR

This paper explores the connection between neural information attributes and neural dynamics, revealing how dynamics influence information processing and representation in the brain.

Contribution

It introduces a unified framework linking neural information metrics with dynamical properties, advancing understanding of brain information processing mechanisms.

Findings

Identifies differences in neural chaos during information processing

Shows neural dynamics shape encoding and decoding properties

Reveals how neural dynamics influence stimulus representation

Abstract

The brain works as a dynamic system to process information. Various challenges remain in understanding the connection between information and dynamics attributes in the brain. The present research pursues exploring how the characteristics of neural information functions are linked to neural dynamics. We attempt to bridge dynamics (e.g., Kolmogorov-Sinai entropy) and information (e.g., mutual information and Fisher information) metrics on the stimulus-triggered stochastic dynamics in neural populations. On the one hand, our unified analysis identifies various essential features of the information-processing-related neural dynamics. We discover spatiotemporal differences in the dynamic randomness and chaotic degrees of neural dynamics during neural information processing. On the other hand, our framework reveals the fundamental role of neural dynamics in shaping neural information processing. The neural dynamics creates an oppositely directed variation of encoding and decoding properties under specific conditions, and it determines the neural representation of stimulus distribution. Overall, our findings demonstrate a potential direction to explain the emergence of neural information processing from neural dynamics and help understand the intrinsic connections between the informational and the physical brain.