Basal ganglia network model of subthalamic deep brain stimulation (Hahn and McIntyre 2010)

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Accession:127388
Basal ganglia network model of parkinsonian activity and subthalamic deep brain stimulation in non-human primates from the article Instructions are provided in the README.txt file. Contact hahnp@ccf.org if you have any questions about the implementation of the model. Please include "ModelDB - BGnet" in the subject heading.
Reference:
1 . Hahn PJ, McIntyre CC (2010) Modeling shifts in the rate and pattern of subthalamopallidal network activity during deep brain stimulation. J Comput Neurosci 28:425-41 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Basal ganglia;
Cell Type(s): Subthalamus nucleus projection neuron; Globus pallidus neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Dopamine; Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Bursting; Parkinson's; Deep brain stimulation;
Implementer(s): Hahn, Philip [hahnp at ccf.org];
Search NeuronDB for information about:  Dopamine; Gaba; Glutamate;
// mosinit.hoc
// created for auto-launch from modeldb by modeldb administrators 20100624-25
// Note that this file, init.hoc, simulation_run.hoc, spkplt2.hoc, and
// pBGLaunchNoQuit.000 were derived from the original model files provided
// by P. Hahn (the other files in this collection not named above)

load_file("nrngui.hoc")

load_file("init.hoc")

xpanel("start parallel network version")
  xlabel("Below creates graphs similar to Fig. 6b1, Fig. 8b")
  xbutton("Start","run_sim()")
xpanel()

objref vbox, fig6b1, fig8b

proc run_sim() {
  load_file("simulation_run.hoc")
  load_file("spkplt2.hoc")
  vbox= new VBox()
    vbox.intercept(1)
     xpanel("Fig 6b1")
     xlabel("Graph similar to Fig 6 b1:")
     xpanel()
     fig6b1= new Graph()
     spkplt2("spikes000.txt",fig6b1)
     fig6b1.size(-10, 1000, -4, 50)
     xpanel("Fig 8b")
     xlabel("Graph similar to Fig 8 b:")
     xpanel()
     fig8b= new Graph()
     spkplt2("spikes001.txt",fig8b)
     fig8b.size(-10, 1000, -4, 50)
   vbox.intercept(0)
  vbox.map()
}