title: Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons.
abstract: Conical pyramidal and stellate neurons were simulated using the GENESIS simulation package. Model neurons were leaky integrate-and-fire and consisted of from four to nine passive compartments. Neurophysiological measurements, based on single-cell recordings and patch-clamp experiments, provided estimations for the simulation of cortical neurons: transmitter-activated conductances, passive membrane time constants and axonal delays. Network connectivity was generated using a previously described probabilistic scheme based on known cortical histology, in which the probability of connections forming between one neuron and another fell off monotonically with increasing inter-cellular separation. Simulations of up to 6400 cortical neurons, approaching the scale of an individual cortical column, confirmed previous findings with smaller networks. Limit-cycle behaviour emerged in the network, in the frequency in the range of the mammalian alpha and beta rhythms (8-20 Hz). Contrary to expectation, near-linear relationships were found between the mean soma membrane potential and and neuronal firing probability. Some of the implications for cortical information processing, in particular the dynamical interactions between the neuronal and larger scales, are discussed.
authors.affiliation: School of Biophysical Sciences and Electrical Engineering, Swinburne University of Technology, Hawthorn, Vic, Australia.
authors.forename: D T
authors.initials: DT
authors.lastname: Liley
authors.forename: D M
authors.initials: DM
authors.lastname: Alexander
authors.forename: J J
authors.initials: JJ
authors.lastname: Wright
authors.forename: M D
authors.initials: MD
authors.lastname: Aldous
mesh_terms: D000513:Alpha Rhythm; D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology*; D003198:Computer Simulation; D008322:Mammals; D008959:Models, Neurological; D009415:Nerve Net; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D017966:Pyramidal Cells / Q000502:physiology