An Introductory Review of Information Theory in the Context of Computational Neuroscience

TL;DR

This paper reviews fundamental information theory concepts from engineering, emphasizing their importance in neuroscience for accurate application and highlighting the future integration of information theory with biological processes to understand neuronal computation.

Contribution

It provides an introductory overview of information theory tailored to neuroscience, clarifying assumptions and outlining future directions for integrating biological complexity.

Findings

Clarifies core information theory concepts for neuroscience

Highlights potential pitfalls of misapplication

Envisions future integration of information theory with biological processes

Abstract

This paper introduces several fundamental concepts in information theory from the perspective of their origins in engineering. Understanding such concepts is important in neuroscience for two reasons. Simply applying formulae from information theory without understanding the assumptions behind their definitions can lead to erroneous results and conclusions. Furthermore, this century will see a convergence of information theory and neuroscience; information theory will expand its foundations to incorporate more comprehensively biological processes thereby helping reveal how neuronal networks achieve their remarkable information processing abilities.