The information transmitted by spike patterns in single neurons

TL;DR

This paper investigates how different spike patterns in single neurons encode sensory information, comparing various readout schemes to identify the most informative patterns and exploring the interaction of categorical and temporal coding.

Contribution

It introduces a method to rank neural coding alphabets based on information transmission, revealing key spike patterns and their roles in neural encoding.

Findings

Certain spike patterns carry more information than others.

The choice of readout alphabet significantly affects information extraction.

Temporal and categorical coding interact to influence neural information redundancy.

Abstract

Spike patterns have been reported to encode sensory information in several brain areas. Here we assess the role of specific patterns in the neural code, by comparing the amount of information transmitted with different choices of the readout neural alphabet. This allows us to rank several alternative alphabets depending on the amount of information that can be extracted from them. One can thereby identify the specific patterns that constitute the most prominent ingredients of the code. We finally discuss the interplay of categorical and temporal information in the amount of synergy or redundancy in the neural code.