Skip to main content
Dryad

Data from: Modularity induced gating and delays in neuronal networks

Cite this dataset

Shein-Idelson, Mark; Cohen, Gilad; Ben-Jacob, Eshel; Hanein, Yael (2017). Data from: Modularity induced gating and delays in neuronal networks [Dataset]. Dryad. https://doi.org/10.5061/dryad.p56mf

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.

Usage notes