Brain: Biological noise-based logic

TL;DR

This paper explores how the brain may utilize noise-based logic, leveraging the stochastic nature of neural spikes to efficiently process information despite apparent randomness.

Contribution

It proposes a noise-based logic model for brain function, explaining how stochastic neural spikes can be harnessed for efficient information processing.

Findings

Neural spikes exhibit stochastic sequences akin to pulse noise.

Noise-based logic can explain rapid information extraction in the brain.

The brain may use randomness to enhance processing speed.

Abstract

Neural spikes in the brain form stochastic sequences, i.e., belong to the class of pulse noises. This stochasticity is a counterintuitive feature because extracting information - such as the commonly supposed neural information of mean spike frequency - requires long times for reasonably low error probability. The mystery could be solved by noise-based logic, wherein randomness has an important function and allows large speed enhancements for special-purpose tasks, and the same mechanism is at work for the brain logic version of this concept.