Electrotonic transform and EPSCs for WT and Q175+/- spiny projection neurons (Goodliffe et al 2018)

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Accession:236310
This model achieves electrotonic transform and computes mean inward and outward attenuation from 0 to 500 Hz input; and randomly activates synapses along dendrites to simulate AMPAR mediated EPSCs. For electrotonic analysis, in Elec folder, the entry file is MSNelec_transform.hoc. For EPSC simulation, in Syn folder, the entry file is randomepsc.hoc. Run read_EPSCsims_mdb_alone.m next with the simulated parameter values specified to compute the mean EPSC.
Reference:
1 . Goodliffe JW, Song H, Rubakovic A, Chang W, Medalla M, Weaver CM, Luebke JI (2018) Differential changes to D1 and D2 medium spiny neurons in the 12-month-old Q175+/- mouse model of Huntington's Disease. PLoS One 13:e0200626 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism: Striatum;
Cell Type(s): Neostriatum spiny neuron;
Channel(s):
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Membrane Properties; Electrotonus; Synaptic-input statistic;
Implementer(s):
Search NeuronDB for information about:  AMPA;
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GoodliffeEtAl2018
Syn
tau_tables
bkkca.mod
cadyn.mod *
caL.mod
caL13.mod
caldyn.mod
can.mod
caq.mod *
car.mod
cat.mod
kaf.mod
kas.mod
kdr.mod
kir.mod *
krp.mod *
linearIclamp.mod
naf.mod
nap.mod
skkca.mod
stim.mod *
actionPotentialPlayer.hoc *
all_tau_vecs.hoc
analyticFunctions.hoc *
analyze_EPSC.m
aux_procs.hoc
baseline_values.txt
basic_procs.hoc
createFit_WTD1.m
electro_procs.hoc
fixnseg.hoc *
load_scripts.hoc
msp_template.hoc
PFC-V1_AddSynapses.hoc
PFC-V1_AddSynapses_fix.hoc
PFC-V1_AddSynapses_neg.hoc
PFC-V1_AddSynapses_negexp.hoc
plot_seClamp_i.ses
ran_test.hoc
randomepsc.hoc
ranstream.hoc
read_EPSCsims_mdb_alone.m
readcell.hoc
readNRNbin_Vclamp.m
                            
objectvar save_window_, rvp_
objectvar scene_vector_[3]
objectvar ocbox_, ocbox_list_, scene_, scene_list_
{ocbox_list_ = new List()  scene_list_ = new List()}
{
save_window_ = new Graph(0)
save_window_.size(0,1500,-0.5,0.2)
scene_vector_[2] = save_window_
{save_window_.view(-1000, -0.035, 14000, 0.035, 381, 91, 300.48, 200.32)}
graphList[1].append(save_window_)
save_window_.save_name("graphList[1].")
save_window_.addvar("seClamp.i", 1, 1, 0.8, 0.9, 2)
}
objectvar scene_vector_[1]
{doNotify()}

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