Experimental analysis and computational modeling of interburst intervals in spontaneous activity of cortical neuronal culture

Abstract

Rhythmic bursting is the most striking behavior of cultured cortical networks and may start in the second week after plating. In this study, we focus on the intervals between spontaneously occurring bursts, and compare experimentally recorded values with model simulations. In the models, we use standard neurons and synapses, with physiologically plausible parameters taken from literature. All networks had a random recurrent architecture with sparsely connected neurons. The number of neurons varied between 500 and 5,000. We find that network models with homogeneous synaptic strengths produce asynchronous spiking or stable regular bursts. The latter, however, are in a range not seen in recordings. By increasing the synaptic strength in a (randomly chosen) subset of neurons, our simulations show interburst intervals (IBIs) that agree better with in vitro experiments. In this regime, called weakly synchronized, the models produce irregular network bursts, which are initiated by neurons with relatively stronger synapses. In some noise-driven networks, a subthreshold, deterministic, input is applied to neurons with strong synapses, to mimic pacemaker network drive. We show that models with such "intrinsically active neurons" (pacemaker-driven models) tend to generate IBIs that are determined by the frequency of the fastest pacemaker and do not resemble experimental data. Alternatively, noise-driven models yield realistic IBIs. Generally, we found that large-scale noise-driven neuronal network models required synaptic strengths with a bimodal distribution to reproduce the experimentally observed IBI range. Our results imply that the results obtained from small network models cannot simply be extrapolated to models of more realistic

Repeated stimulation of cultured networks of rat cortical neurons induces parallel memory traces

“…To simulate the firing activity, we used a (pulse-coupled) spiking neural network model as described in Gritsun et al (2010Gritsun et al ( , 2011. We used a set of neuronal parameters that adequately reproduced the dynamics of cortical neurons (Izhikevich 2003), for details see "Neuron model."…”

“…To validate the solidity of our findings, we repeated all experiments in multiple simulations, based on different network realizations (different set of neurons and a different connectivity matrix), different noise realizations (with the same stochastic characterization), and different STDP models (see "Synaptic noise and model sensitivity"). A more thorough sensitivity analysis of this type of models can be found in Gritsun et al (2010Gritsun et al ( , 2011Gritsun et al ( , 2012. The model was implemented in Matlab and C++, codes are available upon request.…”

Emergent bursting and synchrony in computer simulations of neuronal cultures

“…Previous modeling efforts have shown that synchronous activity is a common phenomenon in simulated neuronal networks and have studied how individual neuronal and synaptic dynamics affect synchronization (Börgers and Kopell, 2003; Kudela et al, 2003; Kube et al, 2004; Belykh et al, 2005; Nesse et al, 2008). Recent work has also focused on studying the importance of network level parameters such as axonal delays, ratio of excitatory/inhibitory neurons (E/I ratio), and the maximum number of connections (Gritsun et al, 2010, 2011) through simulation of networks with pacemaker neurons and random connections. Here, we extend this work by studying the emergence of synchronized bursting in networks without inherent pacemaker neurons, and with variable densities and small-world connections.…”

Simulation of Spontaneous Activity in Neuronal Cultures with Long-Term Plasticity

“…В современных работах по изучению электрофизиологической активности нейрональных культур in vitro особое внимание уделяется феномену спонтанной пачечной активности [1][2][3][4][5][6][7][8][9][10]. Популяционной пачкой (или просто пачкой) активности культуры называется явление резкого возрастания активности групп нейронов в течение короткого промежутка времени.…”

“…В работе [8] произведено сравнение характеристик пачечной активности культур нейронов in vitro, таких как длительность пачек и пиковая амплитуда суммарной активности нейронов внутри пачки, с активностью модели культуры нейронов в широком диапазоне изменения внутренних параметров модели. В работе [9], являющейся продолжением работы [8], внимание уделено анализу межпаченых интервалов -периодам времени между популяционными пачками активности, выявлению параметров модели культуры нейронов, которые позволяют достичь наилучшего соответствия с данными о распределении межпачечных интервалов культур нейронов in vitro. Однако, несмотря на широкий круг исследований в области вычислительных нейронаук, приемлемой модели феномена пачечной активности, позволяющей получить полное согласование активности модели с активностью культуры in vitro, пока не существует.…”