Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens

TL;DR

This paper reviews the evolution of neural networks from simple nerve nets in early animals to complex, hierarchical systems in humans, highlighting conserved features and developmental mechanisms across species.

Contribution

It provides a comparative analysis of neural network evolution, emphasizing conserved topological features and developmental constraints from Cnidaria to Homo sapiens.

Findings

Small-world topology is common across species.

Hubs and long-range connections are conserved features.

Evolution increases complexity while maintaining fundamental mechanisms.

Abstract

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.