Network bursts in cortical cultures are best simulated using pacemaker neurons and adaptive synapses

Abstract

One of the most specific and exhibited features in the electrical activity of dissociated cultured neural networks (NNs) is the phenomenon of synchronized bursts, whose profiles vary widely in shape, width and firing rate. On the way to understanding the organization and behavior of biological NNs, we reproduced those features with random connectivity network models with 5,000 neurons. While the common approach to induce bursting behavior in neuronal network models is noise injection, there is experimental evidence suggesting the existence of pacemaker-like neurons. In our simulations noise did evoke bursts, but with an unrealistically gentle rising slope. We show that a small subset of 'pacemaker' neurons can trigger bursts with a more realistic profile. We found that adding pacemaker-like neurons as well as adaptive synapses yield burst features (shape, width, and height of the main phase) in the same ranges as obtained experimentally. Finally, we demonstrate how changes in network connectivity, transmission delays, and excitatory fraction influence network burst features quantitatively.

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

“…We used the same network model with a random recurrent scale-free connection topology as in a previous study that focused on intraburst characteristics (Gritsun et al 2010). It is described by the following set of equations: Fig.…”

“…In the noise-driven networks each neuron received a Poissonian train of 1-ms pulses with amplitudes normally distributed between 0 and 6 mV for excitatory and between 0 and 3 mV for inhibitory neurons. The same method, validated by Destexhe et al (2004), was used in Gritsun et al (2010). The mean rate and variance were gradually increased from F n = 0 to F n = 1 kHz, as suggested by Rodriguez-Molina et al (2007).…”

“…Cultured cortical networks usually show bursting activity at several different time scales; for instance, Baker et al (2006) measured such bursting behavior in organotypic mega-cocultures of neonatal rat cerebral cortex, and distinguished so-called network bursts, minibursts, and microbursts, based on spike clustering analysis. It is necessary to stress that burst profiles usually have highly variable features in their leading and trailing slopes (Gritsun et al 2010), and can be easily entangled with subsequent bursts. The latter so-called superbursts are not uncommon in cortical neuronal cultures (Wagenaar et al 2006) and may last up to several seconds.…”

“…In a previous study (Gritsun et al 2010) we modeled the intraburst phenomena, whereas in this study we focus on the interburst intervals (IBIs). As before, we will compare models with experimental outcomes.…”

“…In previous work we successfully investigated network models of 5,000 neurons with heterogeneously distributed synaptic weights (Gritsun et al 2010). In this study we proceed with models incorporating 500-5,000 neurons.…”