Modularity Induced Gating and Delays in Neuronal Networks

PLoS Comput Biol. 2016 Apr 22;12(4):e1004883. doi: 10.1371/journal.pcbi.1004883. eCollection 2016 Apr.

Abstract

Neural networks, despite their highly interconnected nature, exhibit distinctly localized and gated activation. Modularity, a distinctive feature of neural networks, has been recently proposed as an important parameter determining the manner by which networks support activity propagation. Here we use an engineered biological model, consisting of engineered rat cortical neurons, to study the role of modular topology in gating the activity between cell populations. We show that pairs of connected modules support conditional propagation (transmitting stronger bursts with higher probability), long delays and propagation asymmetry. Moreover, large modular networks manifest diverse patterns of both local and global activation. Blocking inhibition decreased activity diversity and replaced it with highly consistent transmission patterns. By independently controlling modularity and disinhibition, experimentally and in a model, we pose that modular topology is an important parameter affecting activation localization and is instrumental for population-level gating by disinhibition.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bioengineering
  • Cell Communication / physiology
  • Cells, Cultured
  • Computational Biology
  • Computer Simulation
  • Electrophysiological Phenomena
  • In Vitro Techniques
  • Models, Neurological*
  • Nerve Net / physiology*
  • Neurons / physiology
  • Rats
  • Synaptic Transmission / physiology

Grants and funding

This work was supported by Israeli Science Foundation grant (827/10) Tauber Family Foundation and the European Research Council funding under the European Community’s Seventh Framework Programme (FP7/2007– 2013)/ERC grant agreement FUNMANIA-306707. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.