When Random Variation Results in Functional Segregation.

Abstract

Many functional properties vary dramatically across neurons in cerebral cortex. Two fundamental goals of systems neuroscience are to determine which neurons execute which functions and how the different functional properties of a neuron are related. Here we focus on functional segregation - when two separate subpopulation of neurons encodes two distinct functions. Often, it is assumed that if two functional properties are uncorrelated across the population, then there is no functional segregation. Here we show that this assumption can lead to wrong conclusions; functional segregation can emerge, by chance, due to random variation when that variation is distributed according to skewed, heavy-tailed distributions. We reexamine the results we previously reported (Nature communications, 10(1), 1575-1575 2019), which showed that neurons in primary motor cortex tend to be functionally segregated, with neurons that are either strongly coupled to body movements or to ongoing cortical population activity. Here we show that this is a prime example of functional segregation due to random variation.