5-neuron-model of neocortex for producing realistic extracellular AP shapes (Van Dijck et al. 2012)

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Accession:226812
This is a 5-neuron model of neocortex, containing one tufted layer-5 pyramidal cell, two non-tufted pyramidal cells, and two inhibitory interneurons. It was used to reproduce extracellular spike shapes in a study comparing algorithms for spike sorting and electrode selection. The neuron models are adapted from Dyhrfjeld-Johnsen et al. (2005).
Reference:
1 . Van Dijck G, Seidl K, Paul O, Ruther P, Van Hulle MM, Maex R (2012) Enhancing the yield of high-density electrode arrays through automated electrode selection. Int J Neural Syst 22:1-19 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Extracellular; Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism:
Cell Type(s): Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: GENESIS;
Model Concept(s):
Implementer(s): Maex, Reinoud [reinoud at bbf.uia.ac.be];
Search NeuronDB for information about:  Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell;
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Five-neuron-neocortex
L5P37C-onlybasal
channels
README
Axon_chans.g *
Axon_chans_tab.g
Axon_comps.g
DiffRm.g *
DS1_141099_rot2_sc_defmesh_axon_onlybasal.p
electrodes_fixbug.g
electrodes_try.g *
Excitatory_fibres.g
Fibres.g *
Firing_rate_modulation.g *
Firing_rate_profile.g *
Golgi_grc_multicomp_ax.g
Gran_chan_tab.g *
Gran_comp_soma_dend_axon.g
Gran_const.g *
Gran_synchan.g *
Harsch-Robinson_modulation.g *
Hgradient.g *
Inhibitory_fibres.g *
L5P_ascout.g
L5P_ascout_exp.g *
L5P_chans.g *
L5P_chans_tab.g
L5P_chans_tab_Temp.g *
L5P_chans_Temp.g *
L5P_comps.g *
L5P_comps+axon+syn.g
L5P_const.g *
L5P_const+axon+syn.g *
L5P_graph.g
L5P_history.g
L5P_onlybasal_make.g
L5P_synchan.g
L5P37C_onlybasal.g
nsynapses.g *
                            
// parameters prototype granule cell 
float Ca_tab_max = 0.050
float tab_xdivs = 299
float tab_xfills = tab_xdivs
float tab_xmin = -0.10
float tab_xmax = 0.05
// only used for proto channels
float GNa = 1
float GCa = 1
float GK = 1
float Gh = 1
/* cable parameters */
float CM = 0.01
float RMs =  3.0300
float RA = 1.0 
// CAVE : the values of CM, RMs and RA are overwritten by the cell
// description file 
/* preset constants */
// Ek value used for the leak conductance
float EREST_ACT = -0.0650
// !!Change!!Ek value used for the RESET
float RESET_ACT = -0.0650
float ELEAK = -0.07 // -0.0650
/* concentrations */
//external Ca as in normal slice Ringer
float CCaO = 2.4000
//internal Ca in mM
float CCaI = 75.5e-6
//diameter of Ca_shells
float Shell_thick =  0.6e-6
// Ca_concen tau
float CaTau = 0.01 
float Temp = 37

float scaling_f = 314.15 / 2012.67 // surface soma over surface full Gabbiani model,
// scaling needed because active channels only on soma in Gabbiani model

float ENa = 0.055
float EK = -0.090
float ECa = 0.080
float EH = -0.042

float GInNas = 2.5       \  //   correction for 10 mV shift of (in-)activation rates
             * 2         \  //   correction for 37 deg. Celsius
             * scaling_f \  //   conversion to single compartment
             * 10        \  //   conversion to SI units (S/m^2)
             * 70           //   the Gabbiani value
float GKDrs   = 1.5  * 2 * scaling_f * 10 * 19
float GKAs    = 1.0  * 2 * scaling_f * 10 * 3.67
float GCaHVAs = 1.0  * 2 * scaling_f * 10 * 2.91
float GHs     = 1.1  * 2 * scaling_f * 10 * 0.09
float GMocs   = 0.72 * 2 * scaling_f * 10 * 80

/* Synapses */
float E_GABAA = -0.070
float G_GABAA = 1.0  
float E_NMDA = 0.0
float G_NMDA =  1200.0e-12 / 2012.67e-12   // the Gabbiani value expressed as conductance density
float E_AMPA = 0.0
float G_AMPA = 720.0e-12 / 2012.67e-12  // the Gabbiani value expressed as conductance density
float E_GABAB = -0.070
float G_GABAB = 1.0 

float G_GABAAs = G_GABAA
float GNMDAs = G_NMDA
float GAMPAs = G_AMPA
float G_GABABs = G_GABAB





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