Simulated light response in rod photoreceptors (Liu and Kourennyi 2004)

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Accession:64228
We developed a complete computer model of the rod, which accurately reproduced the main features of the light response and allowed us to demonstrate that it was suppression of Kx channels that was essential for slowing SLR and increasing excitability of rods. The results reported in this work further establish the importance of Kx channels in rod photoreceptor function.
Reference:
1 . Liu XD, Kourennyi DE (2004) Effects of tetraethylammonium on Kx channels and simulated light response in rod photoreceptors. Ann Biomed Eng 32:1428-42 [PubMed]
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:
Cell Type(s): Retina photoreceptor cone GLU cell;
Channel(s): I Chloride; I L high threshold; I K; I h; I K,Ca; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Oscillations; Action Potentials; Calcium dynamics;
Implementer(s): Kourennyi, Dmitri E [dek at case.edu]; Liu, Xiaodong [xliu22 at jhmi.edu];
Search NeuronDB for information about:  Retina photoreceptor cone GLU cell; I Chloride; I L high threshold; I K; I h; I K,Ca; I Potassium;
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Liu-Kourennyi_2004
readme.txt
Ca.mod *
Cad.mod
Clca.mod
h.mod
IinjLT.mod *
IinjLTDim.mod *
IinjSin.mod
Kca.mod
Kv.mod
Kx.mod *
Leak.mod *
0222AP_BR.ses
0222AP_DIM.ses
0222Kx_BR.ses
0222Kx_DIM.ses
Fig5_IVCompare.ses
Fig9_AP_Patterns.ses
init.hoc
mosinit.hoc *
rod.hoc
                            
load_file("nrngui.hoc")
objectvar save_window_, rvp_
objectvar scene_vector_[15]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{pwman_place(0,0,0)}

//Begin PointProcessManager
{
load_file("pointman.hoc")
}
{
soma ocbox_ = new PointProcessManager(0)
}
{object_push(ocbox_)}
{
mt.select("IinjLT") i = mt.selected()
ms[i] = new MechanismStandard("IinjLT")
ms[i].set("del", 1000, 0)
ms[i].set("ton", 8000, 0)
ms[i].set("toff", 1000, 0)
ms[i].set("num", 2, 0)
ms[i].set("amp", 40, 0)
ms[i].set("ssI", 40, 0)
mt.select("IinjLTDim") i = mt.selected()
ms[i] = new MechanismStandard("IinjLTDim")
ms[i].set("del", 1000, 0)
ms[i].set("ton", 8000, 0)
ms[i].set("toff", 1000, 0)
ms[i].set("num", 2, 0)
ms[i].set("amp", 18.87, 0)
ms[i].set("ssI", 40, 0)
mt.select("IinjLT") i = mt.selected() maction(i)
hoc_ac_ = 1
sec.sec move() d1.flip_to(0)
}
{object_pop() doNotify()}
{
ocbox_ = ocbox_.v1
ocbox_.map("PointProcessManager", 629, 245, 247.68, 396.48)
}
objref ocbox_
//End PointProcessManager

{WindowMenu[0].ses_gid(1, 0, 1, "Central")}
{
xpanel("soma(0 - 1) (Parameters)", 0)
xlabel("para set 1 --  VD channels")
soma.gKvbar_Kv = 1
xvalue("gKvbar_Kv","soma.gKvbar_Kv", 1,"", 0, 0 )
soma.eKv_Kv = -74
xvalue("eKv_Kv","soma.eKv_Kv", 1,"", 0, 0 )
soma.ghbar_h = 2.5
xvalue("ghbar_h","soma.ghbar_h", 1,"", 0, 0 )
soma.eh_h = -32
xvalue("eh_h","soma.eh_h", 1,"", 0, 0 )
soma.Vhalfh_h = -75
xvalue("Vhalfh_h","soma.Vhalfh_h", 1,"", 0, 0 )
soma.Sh_h = -5.33
xvalue("Sh_h","soma.Sh_h", 1,"", 0, 0 )
soma.aoh_h = 1
xvalue("aoh_h","soma.aoh_h", 1,"", 0, 0 )
soma.gKxbar_Kx = 0.45
xvalue("gKxbar_Kx","soma.gKxbar_Kx", 1,"", 0, 0 )
soma.eKx_Kx = -74
xvalue("eKx_Kx","soma.eKx_Kx", 1,"", 0, 0 )
soma.VhalfKx_Kx = -49.9
xvalue("VhalfKx_Kx","soma.VhalfKx_Kx", 1,"", 0, 0 )
soma.aoKx_Kx = 0.66
xvalue("aoKx_Kx","soma.aoKx_Kx", 1,"", 0, 0 )
soma.SKx_Kx = 5.7
xvalue("SKx_Kx","soma.SKx_Kx", 1,"", 0, 0 )
soma.glbar_Leak = 0.52
xvalue("glbar_Leak","soma.glbar_Leak", 1,"", 0, 0 )
soma.el_Leak = -74
xvalue("el_Leak","soma.el_Leak", 1,"", 0, 0 )
xpanel(18,119)
}
{WindowMenu[0].ses_gid(0, 1, 1, "Para")}
{
xpanel("soma(0 - 1) (Parameters)", 0)
xlabel("para set 2 --  VD channels")
soma.gCabar_Ca = 4
xvalue("gCabar_Ca","soma.gCabar_Ca", 1,"", 0, 0 )
soma.eCa_Ca = 40
xvalue("eCa_Ca","soma.eCa_Ca", 1,"", 0, 0 )
soma.aomCa_Ca = 100
xvalue("aomCa_Ca","soma.aomCa_Ca", 1,"", 0, 0 )
soma.bomCa_Ca = 100
xvalue("bomCa_Ca","soma.bomCa_Ca", 1,"", 0, 0 )
soma.gammaohCa_Ca = 10
xvalue("gammaohCa_Ca","soma.gammaohCa_Ca", 1,"", 0, 0 )
soma.deltaohCa_Ca = 0.5
xvalue("deltaohCa_Ca","soma.deltaohCa_Ca", 1,"", 0, 0 )
soma.VhalfCam_Ca = -10
xvalue("VhalfCam_Ca","soma.VhalfCam_Ca", 1,"", 0, 0 )
soma.VhalfCah_Ca = 11
xvalue("VhalfCah_Ca","soma.VhalfCah_Ca", 1,"", 0, 0 )
soma.SCam_Ca = 6
xvalue("SCam_Ca","soma.SCam_Ca", 1,"", 0, 0 )
soma.SCah_Ca = 9
xvalue("SCah_Ca","soma.SCah_Ca", 1,"", 0, 0 )
xpanel(317,491)
}
{WindowMenu[0].ses_gid(0, 1, 1, "Para")}
{
xpanel("soma(0 - 1) (Parameters)", 0)
xlabel("para set 2 --  CaD channels")
soma.depth_Cad = 10
xvalue("depth_Cad","soma.depth_Cad", 1,"", 0, 0 )
soma.taur_Cad = 20
xvalue("taur_Cad","soma.taur_Cad", 1,"", 0, 0 )
soma.Cainf_Cad = 5e-05
xvalue("Cainf_Cad","soma.Cainf_Cad", 1,"", 0, 0 )
soma.eCl_Clca = -20
xvalue("eCl_Clca","soma.eCl_Clca", 1,"", 0, 0 )
soma.gClbar_Clca = 1.3
xvalue("gClbar_Clca","soma.gClbar_Clca", 1,"", 0, 0 )
soma.Clh_Clca = 1.5
xvalue("Clh_Clca","soma.Clh_Clca", 1,"", 0, 0 )
soma.eKca_Kca = -74
xvalue("eKca_Kca","soma.eKca_Kca", 1,"", 0, 0 )
soma.gKcabar_Kca = 0.2
xvalue("gKcabar_Kca","soma.gKcabar_Kca", 1,"", 0, 0 )
soma.Cahalf_Kca = 0.32
xvalue("Cahalf_Kca","soma.Cahalf_Kca", 1,"", 0, 0 )
xpanel(471,87)
}
{WindowMenu[0].ses_gid(0, 1, 1, "Para")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-0.12,-4.65661e-09)
scene_vector_[3] = save_window_
{save_window_.view(0, -0.12, 30000, 0.12, 557, 726, 727.68, 180.16)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iCa( 0.5 )", 6, 1, 0.638323, 0.714773, 2)
}
{WindowMenu[0].ses_gid(0, 2, 1, "Channels_1")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-69,4)
scene_vector_[4] = save_window_
{save_window_.view(0, -69, 30000, 73, 130, 269, 955.2, 453.76)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 9, 1, 0.771881, 0.402849, 2)
}
{WindowMenu[0].ses_gid(0, 2, 1, "Channels_1")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-0.007,9.99997e-05)
scene_vector_[5] = save_window_
{save_window_.view(0, -0.007, 30000, 0.0071, 100, 698, 353.28, 179.2)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.ih_h( 0.5 )", 2, 1, 0.661678, 0.752146, 2)
}
{WindowMenu[0].ses_gid(0, 3, 1, "Channels_2")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-0.019,0.029)
scene_vector_[6] = save_window_
{save_window_.view(0, -0.019, 30000, 0.048, 279, 726, 934.08, 314.56)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iCl( 0.5 )", 4, 1, 0.64345, 0.933546, 2)
}
{WindowMenu[0].ses_gid(0, 2, 1, "Channels_1")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-0.0037,0.0407)
scene_vector_[7] = save_window_
{save_window_.view(0, -0.0037, 30000, 0.0444, 758, 194, 300.48, 200.32)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iKx( 0.5 )", 7, 1, 0.659425, 0.952716, 2)
}
{WindowMenu[0].ses_gid(0, 3, 1, "Channels_2")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-0.0044,0.0484)
scene_vector_[8] = save_window_
{save_window_.view(0, -0.0044, 30000, 0.0528, 95, 631, 350.4, 203.2)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iKv( 0.5 )", 5, 1, 0.700941, 0.914037, 2)
}
{WindowMenu[0].ses_gid(0, 3, 1, "Channels_2")}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,-3.49246e-10,0.016)
scene_vector_[9] = save_window_
{save_window_.view(0, -3.49246e-10, 30000, 0.016, 557, 726, 775.68, 293.44)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("soma.iKca( 0.5 )", 2, 1, 0.8, 0.9, 2)
}
{WindowMenu[0].ses_gid(0, 2, 1, "Channels_1")}
{
save_window_ = new Graph(0)
save_window_.size(9800,13800,-68,7)
scene_vector_[10] = save_window_
{save_window_.view(9800, -68, 4000, 75, 168, 716, 815.04, 273.28)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 2, 1, 0.8, 0.9, 2)
}
{WindowMenu[0].ses_gid(0, 3, 1, "Channels_2")}
{
xpanel("RunControl", 0)
v_init = -34
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
tstop = 30000
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
dt = 1
xvalue("dt","dt", 1,"setdt()", 0, 1 )
steps_per_ms = 1
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
xpanel(707,109)
}
{WindowMenu[0].ses_gid(0, 0, 1, "Central")}
{
save_window_ = new Graph(0)
save_window_.size(9500,14000,-65,-10)
scene_vector_[11] = save_window_
{save_window_.view(9500, -65, 4500, 55, 168, 682, 776.64, 540.16)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(0,30000,1.16415e-10,0.01)
scene_vector_[12] = save_window_
{save_window_.view(0, 1.16415e-10, 30000, 0.01, 173, 176, 724.8, 407.68)}
graphList[0].append(save_window_)
save_window_.save_name("graphList[0].")
save_window_.addvar("soma.Cai( 0.5 )", 1, 1, 0.8, 0.9, 2)
}
{
save_window_ = new Graph(0)
save_window_.size(-1000,30000,4.65661e-10,0.04)
scene_vector_[14] = save_window_
{save_window_.view(-1000, 4.65661e-10, 31000, 0.04, 403, 158, 580.8, 346.24)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addexpr("IinjLT[0].i", 1, 1, 0.68764, 0.957508, 2)
}
objectvar scene_vector_[1]
{doNotify()}

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