Neuronal activity

In order to fulfill this goal of making neuronal cultures process information, we must first understand the origin of the behavior observed in isolated neuronal cultures. Once unconstrained cultures are understood, we can then determine how their intrinsic behavior can be used or modulated in order to process afferent inputs.

Synchronization in neuronal cultures

A common type of activity observed in neuronal cultures is a synchronized state were the neurons fire in phase. This activity is mostly observed under the form of synchronized bursts, where the neurons fire several spikes on a short time window, then become quiet over a long period of time before they start firing again.

Simple model: neurons as adaptive oscillators

Several studies have shown the presence of self-ocillating neurons, called pacemaker neurons, in neuronal networks. Considering a population of such neurons, I demonstrated in a recent paper how spike-driven adaptation can shape an oscillating activity into well-defined and synchronous network bursts.

What drives the initiation and termination of such bursts?

Using dynamical systems and phase-plane analysis, I demonstrated that, in an adaptive integrate-and-fire model, the termination of a burst is determined by the hyperpolarizing currents following from the series spikes emitted by a neuron during the burst. In this model, the termination is the source of the neuronal synchronisation, while the initiation of the subsequent burst caused by persistent currents, such as \(I_{Na,p}\) or \(I_M\), which drive the progressive depolarization of the membrane and makes the first neurons fire. These first neurons trigger (advance) the firing of the rest of the network.

Propagation of the activity to the whole network

How a whole neuronal population is recruited into a network burst from the first few firing neurons has been extensively discussed in the litterature, notably in the framework of percolation theory. In a [new paper published in Physica A](), we demonstrated the the relevance of this model in the presence of inhibitory neurons, showing that their presence was simply equivalent to making the network less excitable. In this paper, we also showed that dynamical integrate-and-fire neurons also followed this universal percolation behavior. Hence, above a certain level of excitation, unstructured network will necessarily give rise to such network-wide bursting events.

(work in progress)