On the Distribution of Firing Rates in Networks of Cortical Neurons

The distribution ofin vivoaverage firing rates within local cortical networks has been reported to be highly skewed and long tailed. The distribution of average single-cell inputs, conversely, is expected to be Gaussian by the central limit theorem. This raises the issue of how a skewed distribution of firing rates might result from a symmetric distribution of inputs. We argue that skewed rate distributions are a signature of the nonlinearity of thein vivo f–Icurve. Duringin vivoconditions, ongoing synaptic activity produces significant fluctuations in the membrane potential of neurons, resulting in an expansive nonlinearity of thef–Icurve for low and moderate inputs. Here, we investigate the effects of single-cell and network parameters on the shape of thef–Icurve and, by extension, on the distribution of firing rates in randomly connected networks.

Auteurs Bordeaux Neurocampus