Composite spiking network/neural field model of Parkinsons (Kerr et al 2013)

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This code implements a composite model of Parkinson's disease (PD). The composite model consists of a leaky integrate-and-fire spiking neuronal network model being driven by output from a neural field model (instead of the more usual white noise drive). Three different sets of parameters were used for the field model: one with basal ganglia parameters based on data from healthy individuals, one based on data from individuals with PD, and one purely thalamocortical model. The aim of this model is to explore how the different dynamical patterns in each each of these field models affects the activity in the network model.
1 . Kerr CC, Van Albada SJ, Neymotin SA, Chadderdon GL, Robinson PA, Lytton WW (2013) Cortical information flow in Parkinson's disease: a composite network-field model. Front Comput Neurosci 7:39:1-14 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neural mass;
Brain Region(s)/Organism: Neocortex; Thalamus;
Cell Type(s): Neocortex layer 5-6 pyramidal cell; Neocortex layer 2-3 pyramidal cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking low threshold (LTS) neuron;
Channel(s): I Chloride; I Sodium; I Potassium;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA; Gaba;
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON (web link to model); MATLAB; Python;
Model Concept(s): Oscillations; Methods; Parkinson's; Information transfer;
Implementer(s): Kerr, Cliff [cliffk at];
Search NeuronDB for information about:  Neocortex layer 5-6 pyramidal cell; Neocortex layer 2-3 pyramidal cell; GabaA; GabaB; AMPA; NMDA; Gaba; I Chloride; I Sodium; I Potassium; Gaba; Glutamate;

Kerr CC, Van Albada SJ, Neymotin SA, Chadderdon GL, Robinson PA, Lytton WW (2013) Cortical information flow in Parkinson's disease: a composite network-field model. Front Comput Neurosci 7:39:1-14[PubMed]

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