A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions

TL;DR

This paper proposes a simple, biologically plausible model based on random axonal outgrowth and competition for space to explain the common features of neural connectivity, including connection length distributions and filling fractions across various systems.

Contribution

It introduces a minimal model that reproduces key connectivity features using only random growth and space competition, providing a baseline for understanding neural circuit development.

Findings

Random axonal outgrowth explains connection length distributions.

Competition for space accounts for observed filling fractions.

Model aligns with connectivity patterns across multiple species.

Abstract

Neural connectivity at the cellular and mesoscopic level appears very specific and is presumed to arise from highly specific developmental mechanisms. However, there are general shared features of connectivity in systems as different as the networks formed by individual neurons in Caenorhabditis elegans or in rat visual cortex and the mesoscopic circuitry of cortical areas in the mouse, macaque, and human brain. In all these systems, connection length distributions have very similar shapes, with an initial large peak and a long flat tail representing the admixture of long-distance connections to mostly short-distance connections. Furthermore, not all potentially possible synapses are formed, and only a fraction of axons (called filling fraction) establish synapses with spatially neighboring neurons. We explored what aspects of these connectivity patterns can be explained simply by random axonal outgrowth. We found that random axonal growth away from the soma can already reproduce the known distance distribution of connections. We also observed that experimentally observed filling fractions can be generated by competition for available space at the target neurons--a model markedly different from previous explanations. These findings may serve as a baseline model for the development of connectivity that can be further refined by more specific mechanisms.