DOI: 10.5061/dryad.5k67r
title: Data from: Recurrently connected and localized neuronal communities initiate coordinated spontaneous activity in neuronal networks

description: Developing neuronal systems intrinsically generate coordinated spontaneous
 activity that propagates by involving a large number of synchronously
 firing neurons. In vivo, waves of spikes transiently characterize the
 activity of developing brain circuits and are fundamental for
 activity-dependent circuit formation. In vitro, coordinated spontaneous
 spiking activity, or network bursts (NBs), interleaved within periods of
 asynchronous spikes emerge during the development of 2D and 3D neuronal
 cultures. Several studies have investigated this type of activity and its
 dynamics, but how a neuronal system generates these coordinated events
 remains unclear. Here, we investigate at a cellular level the generation
 of network bursts in spontaneously active neuronal cultures by exploiting
 high-resolution multielectrode array recordings and computational network
 modelling. Our analysis reveals that NBs are generated in specialized
 regions of the network (functional neuronal communities) that feature
 neuronal links with high cross-correlation peak values, sub-millisecond
 lags and that share very similar structural connectivity motifs providing
 recurrent interactions. We show that the particular properties of these
 local structures enable locally amplifying spontaneous asynchronous spikes
 and that this mechanism can lead to the initiation of NBs. Through the
 analysis of simulated and experimental data, we also show that AMPA
 currents drive the coordinated activity, while NMDA and GABA currents are
 only involved in shaping the dynamics of NBs. Overall, our results suggest
 that the presence of functional neuronal communities with recurrent local
 connections allows a neuronal system to generate spontaneous coordinated
 spiking activity events. As suggested by the rules used for implementing
 our computational model, such functional communities might naturally
 emerge during network development by following simple constraints on
 distance-based connectivity.
description: network_model_NEURONPackage containing Python and NEURON code used for simulations. Remember to compile .mod file . The code requires a community detection module available at https://bitbucket.org/taynaud/python-louvain. Up to date versions can be found at https://github.com/dlonardoni/Cell-Culture-Model.PLoScode_networkmodel.zipSpontaneous spiking activity recordingsThe data consist of the spiking activity of hippocampal cell cultures recorded with the high density 4096 electrodes MEA device. File format: Each file contains a matrix made two rows and N columns (N is the number of spikes). The second row corresponds to the time stamps of the spiking activity and the first one to the corresponding electrode ID (numbered from 1 - top left of the recording matrix - to 4096 - bottom right of the recording matrix).SPONT_recordings.zipBIC_recordingsThe data consist of the spiking activity of hippocampal cell cultures recorded with the high density 4096 electrodes MEA device. The following protocol was repeated for each chip 1. control: spontaneous activity is recorded 4. APV: spontaneous activity is recorded under APV. File format: Each file contains a matrix made two rows and N columns (N is the number of spikes). The second row corresponds to the time stamps of the spiking activity and the first one to the corresponding electrode ID (numbered from 1 - top left of the recording matrix - to 4096 - bottom right of the recording matrix).APV recordingsThe data consist of the spiking activity of hippocampal cell cultures recorded with the high density 4096 electrodes MEA device. The following protocol was repeated for each chip 1. control: spontaneous activity is recorded 4. bicuculline: spontaneous activity is recorded under bicuculline. File format: Each file contains a matrix made two rows and N columns (N is the number of spikes). The second row corresponds to the time stamps of the spiking activity and the first one to the corresponding electrode ID (numbered from 1 - top left of the recording matrix - to 4096 - bottom right of the recording matrix).APV_recordings.zip