Lookup NU author(s): Dr Colin Tosh
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative functional efficiency of modular and non-modular neural networks at a range of sizes. We conduct a detailed analysis of efficiency in networks of two size classes: ‘small’ and ‘large’, and a less detailed analysis across a range of network sizes. The former analysis reveals that while the modular network is less efficient than one of the two non-modular networks considered when networks are small, it is usually equally or more efficient than both non-modular networks when networks are large. The latter analysis shows that in networks of small to intermediate size modular networks are much more efficient that non-modular networks of the same (low) connective density. If connective density must be kept low to reduce energy needs for example, this could promote modularity. We have shown how relative functionality/performance scales with network size, but the precise nature of evolutionary relationship between network size and prevalence of modularity will depend on the costs of connectivity.
Author(s): Tosh CR, McNally L
Publication type: Article
Publication status: Published
Journal: Proceedings of the Royal Society of London B: Biological Sciences
Print publication date: 01/03/2015
Online publication date: 28/01/2015
Acceptance date: 23/12/2014
ISSN (print): 0962-8452
ISSN (electronic): 1471-2954
Publisher: The Royal Society Publishing
Altmetrics provided by Altmetric