title: On the distribution of firing rates in networks of cortical neurons.
abstract: The distribution of in vivo average 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 the in vivo f-I curve. During in vivo conditions, ongoing synaptic activity produces significant fluctuations in the membrane potential of neurons, resulting in an expansive nonlinearity of the f-I curve for low and moderate inputs. Here, we investigate the effects of single-cell and network parameters on the shape of the f-I curve and, by extension, on the distribution of firing rates in randomly connected networks.
authors.affiliation: Center for Theoretical Neuroscience, Columbia University, New York, New York 10032, USA. aroxin@clinic.ub.es
authors.forename: Alex
authors.initials: A
authors.lastname: Roxin
authors.forename: Nicolas
authors.initials: N
authors.lastname: Brunel
authors.forename: David
authors.initials: D
authors.lastname: Hansel
authors.forename: Gianluigi
authors.initials: G
authors.lastname: Mongillo
authors.forename: Carl
authors.initials: C
authors.lastname: van Vreeswijk
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D002540:Cerebral Cortex / Q000166:cytology*; D003198:Computer Simulation; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics; D016011:Normal Distribution; D013997:Time Factors
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