Phase response curve of a globus pallidal neuron (Fujita et al. 2011)

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Accession:143100
We investigated how changes in ionic conductances alter the phase response curve (PRC) of a globus pallidal (GP) neuron and stability of a synchronous activity of a GP network, using a single-compartmental conductance-based neuron model. The results showed the PRC and the stability were influenced by changes in the persistent sodium current, the Kv3 potassium, the M-type potassium and the calcium-dependent potassium current.
Reference:
1 . Fujita T, Fukai T, Kitano K (2012) Influences of membrane properties on phase response curve and synchronization stability in a model globus pallidus neuron. J Comput Neurosci 32:539-53 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Basal ganglia;
Cell Type(s): Globus pallidus neuron;
Channel(s): I Na,p; I Na,t; I A; I M; I h; I K,Ca; I Calcium; I A, slow; KCNQ1;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Ions;
Simulation Environment: NEURON;
Model Concept(s): Synchronization; Parkinson's; Phase Response Curves;
Implementer(s): Kitano, Katsunori [kitano at ci.ritsumei.ac.jp];
Search NeuronDB for information about:  I Na,p; I Na,t; I A; I M; I h; I K,Ca; I Calcium; I A, slow; KCNQ1; Ions;
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objectvar scene_vector_[5]
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save_window_.size(0,3000,-80,40)
scene_vector_[2] = save_window_
{save_window_.view(0, -80, 3000, 120, 256, 22, 713, 203)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
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save_window_ = new Graph(0)
save_window_.size(0,3000,-1.5,0.5)
scene_vector_[3] = save_window_
{save_window_.view(0, -1.5, 3000, 2, 257, 253, 712, 200)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iNa_NaF( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iKv3_Kv3( 0.5 )", 3, 1, 0.8, 0.9, 2)
}
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save_window_ = new Graph(0)
save_window_.size(0,3000,-0.04,0.01)
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{save_window_.view(0, -0.04, 3000, 0.05, 258, 480, 711, 201)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iNa_NaP( 0.5 )", 2, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iKv2_Kv2( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iKv4f_Kv4f( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iKv4s_Kv4s( 0.5 )", 3, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iKCNQ_KCNQ( 0.5 )", 1, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iCaH_CaH( 0.5 )", 5, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iHCN_HCN( 0.5 )", 7, 1, 0.8, 0.9, 2)
save_window_.addvar("soma.iSK_SK( 0.5 )", 4, 1, 0.8, 0.9, 2)
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{
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v_init = -65
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xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
runStopAt = 5
xvalue("Continue til","runStopAt", 1,"{continuerun(runStopAt) stoprun=1}", 1, 1 )
runStopIn = 1
xvalue("Continue for","runStopIn", 1,"{continuerun(t + runStopIn) stoprun=1}", 1, 1 )
xbutton("Single Step","steprun()")
t = 0
xvalue("t","t", 2 )
tstop = 3000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 0.0125
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 20
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
screen_update_invl = 0.05
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
realtime = 0
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(3,365)
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objectvar scene_vector_[1]
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