Influence of dendritic structure on neocortical neuron firing patterns (Mainen and Sejnowski 1996)

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Accession:2488
This package contains compartmental models of four reconstructed neocortical neurons (layer 3 Aspiny, layer 4 Stellate, layer 3 and layer 5 Pyramidal neurons) with active dendritic currents using NEURON. Running this simulation demonstrates that an entire spectrum of firing patterns can be reproduced in this set of model neurons which share a common distribution of ion channels and differ only in their dendritic geometry. The reference paper is: Z. F. Mainen and T. J. Sejnowski (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382: 363-366. See also http://www.cnl.salk.edu/~zach/methods.html and http://www.cnl.salk.edu/~zach/ More info in readme.txt file below made visible by clicking on the patdemo folder and then on the readme.txt file.
Reference:
1 . Mainen ZF, Sejnowski TJ (1996) Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382:363-6 [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): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Myelinated neuron; Neocortex spiny stellate cell;
Channel(s): I Na,t; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models;
Implementer(s): Mainen, Zach [Mainen at cshl.edu];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; I Na,t; I K; I M; I K,Ca; I Sodium; I Calcium; I Potassium;
/* --------------------------------------------------------------
   Multi-compartment simulations of neocortical neurons
   DEMO
  
   Z. F. Mainen and T. J. Sejnowski (1996) Influence of dendritic
   structure on firing pattern in model neocortical neurons. 
   Nature 382: 363-366. 
   
   Demo of Figure 1.

   updated: 11/1/96
   author:
   Zach Mainen
   zach@salk.edu or zach@cshl.org


   Corrections to methods of Figure 1 misprinted in paper:

   1. Time step = 25 usec, not 250 usec
   
   2. I_Na rate functions are all shifted 5 mV negative
   m:
   alpha = 0.182(v+30)/(1-exp(-(v+30)/9))
   beta = -0.124(v+30)/(1-exp((v+30)/9))
   h:
   alpha = 0.024(v+45)/(1-exp(-(v+45)/5))
   beta = -0.0091(v+70)/(1-exp((v+70)/5))
   beta_inf = 1/(1+exp(v+60)/6.2)

   3. I_Ca activation not inactivation  is given first 

   4. I_Km rates 
   alpha =  0.001 (v+30)/(1-exp(-(v+30)/9))
   beta =   0.001 (v+30)/(1-exp((v+30)/9)

   5. g_kca = 3 (pS um^-2)

   Correction to Figure 4:

   "transfer impedance" should be "transfer conductance"
   Z^-1 = I/V (uS) 
   
Minor revisions to GUI code by Ted Carnevale 2/2011
to use load_file rather than load_proc,
and to control locations of RunControl panel, 
model selection panel, voltage axis graph, 
and PlotShape.
 
   -------------------------------------------------------------- */

load_file("nrngui.hoc")

objref sh, st, axonal, dendritic, dendritic_only

create soma
access soma

tstop = 1000
steps_per_ms = 40
dt = 0.025


// --------------------------------------------------------------
// passive & active membrane 
// --------------------------------------------------------------

ra        = 150
global_ra = ra
rm        = 30000
c_m       = 0.75
cm_myelin = 0.04
g_pas_node = 0.02

v_init    = -70
celsius   = 37

Ek = -90
Ena = 60


gna_dend = 20
gna_node = 30000
gna_soma = gna_dend

gkv_axon = 2000
gkv_soma = 200

gca = .3
gkm = .1
gkca = 3

gca_soma = gca
gkm_soma = gkm
gkca_soma = gkca
 

// --------------------------------------------------------------
// Axon geometry
//
// Similar to Mainen et al (Neuron, 1995)
// --------------------------------------------------------------

n_axon_seg = 5

create soma,iseg,hill,myelin[2],node[2]

// after http://www.neuron.yale.edu/phpbb/viewtopic.php?f=8&t=858
func secarea() { local x, sum
  sum = 0
  for (x,0) sum += area(x)
  return sum
}

proc create_axon() {

  create iseg,hill,myelin[n_axon_seg],node[n_axon_seg]

  soma {
    equiv_diam = sqrt(secarea()/(4*PI))
    // area = equiv_diam^2*4*PI
  }
  if (numarg()) equiv_diam = $1

  iseg {                // initial segment between hillock + myelin
     L = 15
     nseg = 5
     diam = equiv_diam/10        // see Sloper and Powell 1982, Fig.71
  }

  hill {                
    L = 10
    nseg = 5
    diam(0:1) = 4*iseg.diam:iseg.diam
  }

  // construct myelinated axon with nodes of ranvier

  for i=0,n_axon_seg-1 {
    myelin[i] {         // myelin element
      nseg = 5
      L = 100
      diam = iseg.diam         
    }
    node[i] {           // nodes of Ranvier
      nseg = 1
      L = 1.0           
      diam = iseg.diam*.75       // nodes are thinner than axon
    }
  }

  soma connect hill(0), 0.5
  hill connect iseg(0), 1
  iseg connect myelin[0](0), 1
  myelin[0] connect node[0](0), 1

  for i=0,n_axon_seg-2  { 
      node[i] connect myelin[i+1](0), 1 
      myelin[i+1] connect node[i+1](0), 1
  }
}

// --------------------------------------------------------------
// Spines
// --------------------------------------------------------------

      // Based on the "Folding factor" described in
      // Jack et al (1989), Major et al (1994)
      // note, this assumes active channels are present in spines 
      // at same density as dendrites

spine_dens = 1
      // just using a simple spine density model due to lack of data on some 
      // neuron types.

spine_area = 0.83 // um^2  -- K Harris

proc add_spines() { local a
  forsec $o1 {
    a =0
    for(x) a=a+area(x)

    F = (L*spine_area*spine_dens + a)/a

    L = L * F^(2/3)
    for(x) diam(x) = diam(x) * F^(1/3)
  }
}



proc init_cell() {

  // passive
  forall {
    insert pas
    Ra = ra 
    cm = c_m 
    g_pas = 1/rm
    e_pas = v_init
  }

  // exceptions along the axon
  forsec "myelin" cm = cm_myelin
  forsec "node" g_pas = g_pas_node

  // na+ channels
  forall insert na
  forsec dendritic gbar_na = gna_dend
  forsec "myelin" gbar_na = gna_dend
  hill.gbar_na = gna_node
  iseg.gbar_na = gna_node
  forsec "node" gbar_na = gna_node

  // kv delayed rectifier channels
  iseg { insert kv  gbar_kv = gkv_axon }
  hill { insert kv  gbar_kv = gkv_axon }
  soma { insert kv  gbar_kv = gkv_soma }

  // dendritic channels
  forsec dendritic {
    insert km    gbar_km  = gkm
    insert kca   gbar_kca = gkca
    insert ca    gbar_ca = gca
    insert cad
  }

  soma {
    gbar_na = gna_soma
    gbar_km = gkm_soma
    gbar_kca = gkca_soma
    gbar_ca = gca_soma
  }

 
  forall if(ismembrane("k_ion")) ek = Ek
  forall if(ismembrane("na_ion")) {
    ena = Ena
    // seems to be necessary for 3d cells to shift Na kinetics -5 mV
    vshift_na = -5
  }
  forall if(ismembrane("ca_ion")) {
    eca = 140
    ion_style("ca_ion",0,1,0,0,0)
    vshift_ca = 0
  }
}

proc load_3dcell() {

// $s1 filename

  aspiny = 0
  forall delete_section()
  xopen($s1)
  access soma

  dendritic = new SectionList()

  // make sure no compartments exceed 50 uM length
  forall {
    diam_save = diam
    n = L/50
    nseg = n + 1
    if (n3d() == 0) diam = diam_save
    dendritic.append()
  }    


  // show cell
/*
  sh = new PlotShape()
  sh.size(-300,300,-300,300)
*/
  // but control position of PlotShape window -- Ted Carnevale
  sh = new PlotShape(0)
  sh.size(-300,300,-299.522,299.522)
  sh.variable("v")
  {sh.view(-300, -299.522, 600, 599.043, 265, 369, 200.64, 200.32)}

  dendritic_only = new SectionList()
  forsec dendritic dendritic_only.append()
  soma  dendritic_only.remove()

  create_axon()

  init_cell()

  if (!aspiny) add_spines(dendritic_only,spine_dens)

  st=new IClamp(.5)
  st.dur = 900
  st.del = 5
}

// GUI

// run control panel

{
xpanel("RunControl")
xvalue("Init","v_init", 1,"stdinit()", 1, 1 )
xbutton("Init & Run","run()")
xbutton("Stop","stoprun=1")
xvalue("Continue til","runStopAt", 1,"{continuerun(runStopAt) stoprun=1}", 1, 1 )
xvalue("Continue for","runStopIn", 1,"{continuerun(t + runStopIn) stoprun=1}", 1, 1 )
xbutton("Single Step","steprun()")
xvalue("t","t", 2 )
xvalue("Tstop","tstop", 1,"tstop_changed()", 0, 1 )
xvalue("dt","dt", 1,"setdt()", 0, 1 )
xvalue("Points plotted/ms","steps_per_ms", 1,"setdt()", 0, 1 )
xvalue("Scrn update invl","screen_update_invl", 1,"", 0, 1 )
xvalue("Real Time","realtime", 0,"", 0, 1 )
xpanel(0,105)
}

// menu of models

proc fig1a() {
  load_3dcell("cells/lcAS3.hoc")
  st.amp = 0.05
}

proc fig1b() {
  load_3dcell("cells/j7.hoc")  
  st.amp = 0.07
}

proc fig1c() {
  load_3dcell("cells/j8.hoc")
  st.amp = 0.1
}

proc fig1d() {
  load_3dcell("cells/j4a.hoc") 
  st.amp = 0.2
}

xpanel("Figure 1")
xbutton("a. L3 Aspiny","fig1a()")
xbutton("b. L4 Stellate","fig1b()")
xbutton("c. L3 Pyramid","fig1c()")
xbutton("d. L5 Pyramid","fig1d()")
xpanel(159,481)

// graph of v(0.5) vs. t

objref g

{
g = new Graph(0)
g.size(0,1000,-80,40)
{g.view(0, -80, 1000, 120, 265, 105, 300.48, 200.32)}
graphList[0].append(g)
g.addexpr("v(.5)", 1, 1, 0.8, 0.9, 2)
}

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