We develop a new computationally efficient approach for the analysis of complex large-scale neurobiological networks. Its key element is the use of a new phenomenological model of a neuron capable of replicating important spike pattern characteristics and designed in the form of a system of difference equations (a map). ... Interconnected with synaptic currents these model neurons demonstrated responses very similar to those found with Hodgkin-Huxley models and in experiments. We illustrate the efficacy of this approach in simulations of one- and two-dimensional cortical network models consisting of regular spiking neurons and fast spiking interneurons to model sleep and activated states of the thalamocortical system. See paper for more.
Model Type: Realistic Network
Region(s) or Organism(s): Neocortex
Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex fast spiking (FS) interneuron
Model Concept(s): Activity Patterns; Oscillations; Spatio-temporal Activity Patterns; Simplified Models; Sleep
Simulation Environment: C or C++ program
Implementer(s): Bazhenov, Maxim [Bazhenov at Salk.edu]; Rulkov, Nikolai [nrulkov at ucsd.edu]
References:
Rulkov NF, Timofeev I, Bazhenov M. (2004). Oscillations in large-scale cortical networks: map-based model. Journal of computational neuroscience. 17 [PubMed]