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 *
                            
//genesis

// This scripts regulates the temporal modulation of the fibres.
// Feedforward input modulated by Harsch-Robinson.
// Intracolumnar feedback input regulated by membrane potential of L5P.
// Intercolumner feedback: to be implemented later.



/*************** Feedforward input  *******************/


// feedforward input from the Harsch-Robinson external stochastic process


// kept this in main script
// include Harsch-Robinson_modulation.g
// Harsch_Robinson_modulation 20 0.05


addmsg /HR_modulation/RC/diffamp  /Excitatory_fibres/FF/FF_diffamp[] GAIN output
addmsg /HR_modulation/RC/diffamp  /Inhibitory_fibres/FF/FF_diffamp[] GAIN output




/********** Intracolumnar feedback input  **************/

// feedback input from L5P
// As feedback signal, we use the continuous soma membrane potential instead the 
// discrete action potential timing.
// Diffamps are used to covert Vm to values positive (set plus field) and to change their amplitude
// (set gain field).

// It is expected that this intracolumnar feedback will suffice to induce oscillations.
// The delay of this feedback can be set by the delay field of the synapses.
// The position of the feedback synapses can be tuned via Firing_rate_profile.g



// Excitatory

   ce /L5P
   create diffamp soma/E_diffamp
   setfield soma/E_diffamp plus 0.08  minus 0 \
                         saturation 10e10 \
                         gain 10
   addmsg soma soma/E_diffamp PLUS Vm
//   addmsg /L5P/solve soma/E_diffamp PLUS {findsolvefield /L5P/solve /L5P/soma Vm}


addmsg /L5P/soma/E_diffamp /Excitatory_fibres/FBintra/FBintra_diffamp[] GAIN output

    addmsg soma/E_diffamp      /output/{asc_name} SAVE output
 

// Inhibitory

   ce /L5P
   create diffamp soma/I_diffamp
   setfield soma/I_diffamp plus 0.08  minus 0 \
                         saturation 10e10 \
                         gain 10
   addmsg soma soma/I_diffamp PLUS Vm
//   addmsg /L5P/solve soma/I_diffamp PLUS {findsolvefield /L5P/solve /L5P/soma Vm}

   addmsg soma/I_diffamp /Inhibitory_fibres/FBintra/FBintra_diffamp[] GAIN output

    addmsg soma/I_diffamp      /output/{asc_name} SAVE output
 

/********** Intercolumnar feedback input  **************/

// Note that strictly speaking this input can be of the feedforward type !





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