/* tuftIB/tuftIB_template.hoc
automatically written from f2nrn/neuron_code_writer.f
via subroutines that were inserted into the fortran
code e.g., tuftIB/integrate_tuftIB.hoc
The template's form was derived by
Tom Morse and Michael Hines
from a template, pyr3_template created
by Roger Traub and Maciej Lazarewicz when they ported
Traub RD, Buhl EH, Gloveli T, Whittington MA.
Fast Rhythmic Bursting Can Be Induced in Layer 2/3
Cortical Neurons by Enhancing Persistent Na(+)
Conductance or by Blocking BK Channels.J Neurophysiol.
2003 Feb;89(2):909-21.
to NEURON
*/
begintemplate tuftIB
public type
public name
strdef name
// parts of the template were lifted from a default
// cell writing from Network Builder NetGUI[0]
public is_art
public init, topol, basic_shape, subsets
public geom, biophys
public synlist, x, y, z, position
public connect2target
public set_netcon_src_comp
// the above function added to set neton
// compartment source in the presyn cell
public comp, level, Soma, Dendrites
public Soma_Dendrites, Axon, all
public presyn_comp, top_level
// it is the responsibility of the calling
// program to set the above presynaptic
// compartment number
external traub_connect
objref this
create comp[ 61+1]
objref level[ 18+1], Soma, Dendrites
objref Soma_Dendrites, Axon
objref synlist
func type() {return 6 }
proc init() {
doubler = 1
comp[0] delete_section() // clean up for fortran code
traub_connect( 61+1)
titlePrint()
presyn_comp = 60
// in Traub model;changed by calling prog.
objref Soma, Axon, Dendrites, Soma_Dendrites
objref level
topol()
shape()
geom() // the geometry and
subsets() // subsets and
biophys() // active currents
synlist = new List() // list of synapses
// NetGUI[0] stores synapses in the cell object, in
// Traub model it is easier to store them outside
set_doubler() // to double or not
if (doubler) {double_dend_cond()}
/* for taking
spine membrane area correction into account (the
method used doubles max cond's when spines present)
*/
more_adjustments()
name = "tuftIB"
}
proc double_dend_cond() {
/* this function gets replaced later with
another one if double_dend_cond() is tacked on. */
}
proc titlePrint() {
/* print "
print "-----"
print "
print "tuftIB Neuron Model based on "
print "Traub RD et al (2005, 2003)"
print "
print "-----"
Remove title printing with this comment for now.
Printing otherwise repeats (for each cell)
-too voluminous for a network creation */
}
proc set_doubler() {doubler=1}
// this function gets replaced with one that
// sets doubler to 0 when there are no spines
// in the cell (for no spines the additional
// hoc code is written from integrate_cell.f
// where cell is nRT, TCR. Woops I just
// found that deepaxax, deepbask, deepLTS,
// supaxax, supbask, supLTS all use the script
// cell/run_fortran.sh to replace the =1's with
// =0's. I will change the fortran code to
// make it all run_fortran.sh replacements or
// not for uniformity.
proc topol() {
// create comp[ 62] // note one greater than numcomp due to fortran indicies
// last argument, parent location for connection
// is overwritten to 1 for parents with connected children
// in below traub_connect proc calls
traub_connect(this, 1, 56, 0.198609787, 0)
traub_connect(this, 1, 2, 0.0301519221, 1)
traub_connect(this, 1, 3, 0.0301519221, 1)
traub_connect(this, 1, 4, 0.0301519221, 1)
traub_connect(this, 1, 5, 0.0301519221, 1)
traub_connect(this, 1, 6, 0.0301519221, 1)
traub_connect(this, 1, 35, 0.131870466, 1)
traub_connect(this, 2, 13, 0.0151319918, 1.)
traub_connect(this, 3, 14, 0.0151319918, 1.)
traub_connect(this, 4, 15, 0.0151319918, 1.)
traub_connect(this, 5, 16, 0.0151319918, 1.)
traub_connect(this, 6, 17, 0.0151319918, 1.)
traub_connect(this, 7, 35, 0.0143749099, 1.)
traub_connect(this, 7, 18, 0.00805084797, 1.)
traub_connect(this, 12, 35, 0.0143749099, 1.)
traub_connect(this, 12, 23, 0.00805084797, 1.)
traub_connect(this, 13, 24, 0.0151319918, 1.)
traub_connect(this, 14, 25, 0.0151319918, 1.)
traub_connect(this, 15, 26, 0.0151319918, 1.)
traub_connect(this, 16, 27, 0.0151319918, 1.)
traub_connect(this, 17, 28, 0.0151319918, 1.)
traub_connect(this, 18, 29, 0.00805084797, 1.)
traub_connect(this, 23, 34, 0.00805084797, 1.)
traub_connect(this, 35, 36, 0.0635858917, 1.)
traub_connect(this, 36, 37, 0.0572189482, 1.)
traub_connect(this, 37, 38, 0.0511871097, 1.)
traub_connect(this, 38, 39, 0.0454903769, 1.)
traub_connect(this, 39, 40, 0.0401287504, 1.)
traub_connect(this, 40, 41, 0.0351022313, 1.)
traub_connect(this, 41, 42, 0.0304108207, 1.)
traub_connect(this, 42, 43, 0.0260545207, 1.)
traub_connect(this, 43, 44, 0.0197765666, 1.)
traub_connect(this, 44, 45, 0.0130771876, 1.)
traub_connect(this, 45, 46, 0.00929984778, 1.)
traub_connect(this, 46, 47, 0.00695437146, 1.)
traub_connect(this, 47, 48, 0.00617996773, 1)
traub_connect(this, 47, 49, 0.00617996773, 1)
traub_connect(this, 48, 49, 0.00633553983, 1)
traub_connect(this, 48, 50, 0.00633553983, 1.)
traub_connect(this, 49, 51, 0.00633553983, 1.)
traub_connect(this, 50, 52, 0.00633553983, 1.)
traub_connect(this, 51, 53, 0.00633553983, 1.)
traub_connect(this, 52, 54, 0.00633553983, 1.)
traub_connect(this, 53, 55, 0.00633553983, 1.)
traub_connect(this, 56, 57, 0.0472757183, 1.)
traub_connect(this, 57, 58, 0.0208024203, 1)
traub_connect(this, 57, 59, 0.0208024203, 1)
traub_connect(this, 58, 59, 0.01570795, 1)
traub_connect(this, 58, 60, 0.01570795, 1.)
traub_connect(this, 59, 61, 0.01570795, 1.)
traub_connect(this, 36, 8, 0.0142102732, 1.)
traub_connect(this, 37, 9, 0.0140221731, 1.)
traub_connect(this, 37, 10, 0.0140221731, 1.)
traub_connect(this, 36, 11, 0.0142102732, 1.)
traub_connect(this, 8, 19, 0.00805084797, 1.)
traub_connect(this, 10, 21, 0.00805084797, 1.)
traub_connect(this, 19, 30, 0.00805084797, 1.)
traub_connect(this, 21, 32, 0.00805084797, 1.)
traub_connect(this, 9, 20, 0.00805084797, 1.)
traub_connect(this, 20, 31, 0.00805084797, 1.)
traub_connect(this, 11, 22, 0.00805084797, 1.)
traub_connect(this, 22, 33, 0.00805084797, 1.)
access comp[1] // handy statement if want to start gui's from nrnmainmenu
}
proc geom() {
// the "traub level" subsets are created and defined below
top_level = 18
objref level[top_level+1]
for i=0,top_level { level[i] = new SectionList() }
comp[ 1] { level[ 1].append() L= 25. diam = 2* 9. }
comp[ 2] { level[ 2].append() L= 60. diam = 2* 0.85 }
comp[ 3] { level[ 2].append() L= 60. diam = 2* 0.85 }
comp[ 4] { level[ 2].append() L= 60. diam = 2* 0.85 }
comp[ 5] { level[ 2].append() L= 60. diam = 2* 0.85 }
comp[ 6] { level[ 2].append() L= 60. diam = 2* 0.85 }
comp[ 7] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 8] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 9] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 10] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 11] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 12] { level[ 2].append() L= 60. diam = 2* 0.62 }
comp[ 13] { level[ 3].append() L= 60. diam = 2* 0.85 }
comp[ 14] { level[ 3].append() L= 60. diam = 2* 0.85 }
comp[ 15] { level[ 3].append() L= 60. diam = 2* 0.85 }
comp[ 16] { level[ 3].append() L= 60. diam = 2* 0.85 }
comp[ 17] { level[ 3].append() L= 60. diam = 2* 0.85 }
comp[ 18] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 19] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 20] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 21] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 22] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 23] { level[ 3].append() L= 60. diam = 2* 0.62 }
comp[ 24] { level[ 4].append() L= 60. diam = 2* 0.85 }
comp[ 25] { level[ 4].append() L= 60. diam = 2* 0.85 }
comp[ 26] { level[ 4].append() L= 60. diam = 2* 0.85 }
comp[ 27] { level[ 4].append() L= 60. diam = 2* 0.85 }
comp[ 28] { level[ 4].append() L= 60. diam = 2* 0.85 }
comp[ 29] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 30] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 31] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 32] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 33] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 34] { level[ 4].append() L= 60. diam = 2* 0.62 }
comp[ 35] { level[ 5].append() L= 75. diam = 2* 2. }
comp[ 36] { level[ 6].append() L= 75. diam = 2* 1.9 }
comp[ 37] { level[ 7].append() L= 75. diam = 2* 1.8 }
comp[ 38] { level[ 8].append() L= 75. diam = 2* 1.7 }
comp[ 39] { level[ 9].append() L= 75. diam = 2* 1.6 }
comp[ 40] { level[ 10].append() L= 75. diam = 2* 1.5 }
comp[ 41] { level[ 11].append() L= 75. diam = 2* 1.4 }
comp[ 42] { level[ 12].append() L= 75. diam = 2* 1.3 }
comp[ 43] { level[ 13].append() L= 75. diam = 2* 1.2 }
comp[ 44] { level[ 14].append() L= 75. diam = 2* 1. }
comp[ 45] { level[ 15].append() L= 75. diam = 2* 0.8 }
comp[ 46] { level[ 16].append() L= 75. diam = 2* 0.7 }
comp[ 47] { level[ 17].append() L= 75. diam = 2* 0.6 }
comp[ 48] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 49] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 50] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 51] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 52] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 53] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 54] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 55] { level[ 18].append() L= 60. diam = 2* 0.55 }
comp[ 56] { level[ 0].append() L= 25. diam = 2* 0.9 }
comp[ 57] { level[ 0].append() L= 50. diam = 2* 0.7 }
comp[ 58] { level[ 0].append() L= 50. diam = 2* 0.5 }
comp[ 59] { level[ 0].append() L= 50. diam = 2* 0.5 }
comp[ 60] { level[ 0].append() L= 50. diam = 2* 0.5 }
comp[ 61] { level[ 0].append() L= 50. diam = 2* 0.5 }
}
// Here are some commonly used subsets of sections
objref all
proc subsets() { local i
objref Soma, Dendrites, Soma_Dendrites, Axon
objref all
Soma = new SectionList()
Dendrites = new SectionList()
Soma_Dendrites = new SectionList()
Axon = new SectionList()
for i=1,top_level {
forsec level[i] { // recall level 0 is axon, 1 is soma, higher are dends
Soma_Dendrites.append()
if (i>1) {Dendrites.append()}
}
}
forsec level[1] {
Soma.append()
}
forsec level[0] { Axon.append() }
all = new SectionList()
for i=1, 61 comp[i] all.append()
}
proc shape() {
/* This section could contain statements like
{pt3dclear() pt3dadd(-1,-1,0,1) pt3dadd(-1,-2,0,1)}
These visual settings do not effect the electrical
and chemical systems of equations. */
}
proc biophys() {
//
// insert the mechanisms and assign max conductances
//
forsec all { insert pas } // g_pas has two values; soma-dend,axon
forsec level[ 0] {
insert naf
gbar_naf = 0.45
insert kdr
gbar_kdr = 0.45
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.042
insert k2
gbar_k2 = 0.0005
}
forsec level[ 1] {
insert naf
gbar_naf = 0.2
insert nap
gbar_nap = 0.00016
insert kdr
gbar_kdr = 0.17
insert kc
gbar_kc = 0.016
insert ka_ib
gbar_ka_ib = 0.020
insert km
gbar_km = 0.0119
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.01
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 4333.33333
}
forsec level[ 2] {
insert naf
gbar_naf = 0.075
insert nap
gbar_nap = 0.00006
insert kdr
gbar_kdr = 0.075
insert kc
gbar_kc = 0.016
insert ka_ib
gbar_ka_ib = 0.008
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.02
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 3] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 4] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 5] {
insert naf
gbar_naf = 0.15
insert nap
gbar_nap = 0.00012
insert kdr
gbar_kdr = 0.12
insert kc
gbar_kc = 0.016
insert ka_ib
gbar_ka_ib = 0.008
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 6] {
insert naf
gbar_naf = 0.075
insert nap
gbar_nap = 0.00006
insert kdr
gbar_kdr = 0.075
insert kc
gbar_kc = 0.016
insert ka_ib
gbar_ka_ib = 0.008
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 7] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.004
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 8] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 9] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 10] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 11] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 12] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 13] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 14] {
insert naf
gbar_naf = 0.015
insert nap
gbar_nap = 0.000012
insert kc
gbar_kc = 0.0005
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.01904
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0045
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 15] {
insert naf
gbar_naf = 0.003
insert nap
gbar_nap = 0.0000024
insert kc
gbar_kc = 0.0012
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.0056
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.001
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 16] {
insert naf
gbar_naf = 0.003
insert nap
gbar_nap = 0.0000024
insert kc
gbar_kc = 0.0012
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.0056
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.001
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 17] {
insert naf
gbar_naf = 0.003
insert nap
gbar_nap = 0.0000024
insert kc
gbar_kc = 0.0012
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.0056
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.001
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0001
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
forsec level[ 18] {
insert naf
gbar_naf = 0.003
insert nap
gbar_nap = 0.0000024
insert kc
gbar_kc = 0.0012
insert ka_ib
gbar_ka_ib = 0.0006
insert km
gbar_km = 0.0056
insert k2
gbar_k2 = 0.0005
insert kahp_deeppyr
gbar_kahp_deeppyr = 0.0002
insert cal
gbar_cal = 0.0027
insert cat
gbar_cat = 0.0001
insert ar
gbar_ar = 0.0002
insert cad
// *** ca diffusion: beta=1/tau
beta_cad = 0.075
// cafor(I) (FORTRAN) converted to phi (NEURON)
phi_cad = 86666.6667
}
// Special case: individually specified beta_cad's in level 2
comp[ 2] beta_cad = 0.02
comp[ 3] beta_cad = 0.075
comp[ 4] beta_cad = 0.075
comp[ 5] beta_cad = 0.02
comp[ 6] beta_cad = 0.02
comp[ 7] beta_cad = 0.075
comp[ 8] beta_cad = 0.075
comp[ 9] beta_cad = 0.075
comp[ 10] beta_cad = 0.075
comp[ 11] beta_cad = 0.075
comp[ 12] beta_cad = 0.075
forsec all {
cm = 0.9 // assign global specific capac.
}
//
// passive membrane resistance (leak) and axial resistance
//
forsec Soma_Dendrites {
g_pas = 2.E-05
Ra = 250.
}
forsec Axon {
g_pas = 0.001
Ra = 100.
}
ceiling_cad = 1e6 // nearly unlimited Ca concentration
// print "made it to end of initialization from SCORTMAJ_FRB()"
} // end of biophys
// Compartment Area: Dendritic.spines double area of
// dend. membrane, which in Traubs method is equivalent to
// only multiplying all dend. max conductances by two
// (the area is doubled but the volume is const.)
proc double_dend_cond() {
spine_area_multiplier = 2
forsec Dendrites {
if (ismembrane("nap")) { gbar_nap *= spine_area_multiplier }
if (ismembrane("napf")) { gbar_napf *= spine_area_multiplier }
if (ismembrane("napf_tcr")) { gbar_napf_tcr *= spine_area_multiplier }
if (ismembrane("naf")) { gbar_naf *= spine_area_multiplier }
if (ismembrane("naf_tcr")) { gbar_naf_tcr *= spine_area_multiplier }
if (ismembrane("naf2")) { gbar_naf2 *= spine_area_multiplier }
if (ismembrane("kc")) { gbar_kc *= spine_area_multiplier }
if (ismembrane("kc_fast")) { gbar_kc_fast *= spine_area_multiplier }
if (ismembrane("kahp_deeppyr")) { gbar_kahp_deeppyr *= spine_area_multiplier }
if (ismembrane("km")) { gbar_km *= spine_area_multiplier }
if (ismembrane("kdr")) { gbar_kdr *= spine_area_multiplier }
if (ismembrane("kdr_fs")) { gbar_kdr_fs *= spine_area_multiplier }
if (ismembrane("ka_ib")) { gbar_ka_ib *= spine_area_multiplier }
if (ismembrane("ka_ib_ib")) { gbar_ka_ib_ib *= spine_area_multiplier }
if (ismembrane("k2")) { gbar_k2 *= spine_area_multiplier }
if (ismembrane("cal")) { gbar_cal *= spine_area_multiplier }
if (ismembrane("cat")) { gbar_cat *= spine_area_multiplier }
if (ismembrane("cat_a")) { gbar_cat_a *= spine_area_multiplier }
if (ismembrane("ar")) { gbar_ar *= spine_area_multiplier }
if (ismembrane("pas")) { g_pas *= spine_area_multiplier }
cm = cm * spine_area_multiplier
}
}
// double_dend_cond() // run for cells w/ spines
proc position() { local i
// comp switched to comp[1] since 0 deleted
comp[1] for i = 0, n3d()-1 {
pt3dchange(i, $1-x+x3d(i), \
$2-y+y3d(i), $3-z+z3d(i),diam3d(i))
}
x=$1 y=$2 z=$3
}
proc connect2target() {
// $o1 targ point process, $o2 returned NetCon
comp[presyn_comp] $o2 = new NetCon(&v(1),$o1)
$o2.threshold = 0
}
objref syn_
proc synapses() {
// place for each compartment that has input
// statements like
//comp[3] syn_=new AlphaSynKinT(1) synlist.append(syn_)
//comp[4] syn_=new NMDA(1) synlist.append(syn_)
}
// is not an artificial cell:
func is_art() { return 0 }
proc more_adjustments() {
forsec all {
// global reversal potentials
ek = -95.
e_pas = -70.
ena = 50.
vca = 125.
forsec all if (ismembrane("ar")) erev_ar = -35.
e_gaba_a = -75.
}
// v(1,1)= -70.
forsec all if (ismembrane("naf")) {fastNa_shift_naf=-3.5}
// extended initializations from integrate_tuftIB()
/* forsec Soma_Dendrites { if (ismembrane("nap")) {gbar_nap *= 0.2}}
forsec Soma_Dendrites { if (ismembrane("kc")) {gbar_kc *= 2.}}
forsec Soma_Dendrites { if (ismembrane("cal")) {gbar_cal *= 1.}}
forsec Soma_Dendrites { if (ismembrane("km")) {gbar_km *= 1.4}}
comp[48] { if (ismembrane("cal")) {gbar_cal *= 4.5 }}
comp[49] { if (ismembrane("cal")) {gbar_cal *= 4.5 }}
comp[ 38] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 39] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 40] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 41] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 42] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 43] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
comp[ 44] { if (ismembrane("cal")) {gbar_cal *= 2.0 }}
*/
}
endtemplate tuftIB