// ----------------------------------------------------------------------------
// membrane.hoc
// loads the full cell morphology, inserts passive
// membrane properties, corrects membrane resistance
// and capacitance for spines, and corrects (roughly)
// for temperature if needed
//
// 2007-08-17, Christoph Schmidt-Hieber, University of Freiburg
//
// accompanies the publication:
// Schmidt-Hieber C, Jonas P, Bischofberger J (2007)
// Subthreshold Dendritic Signal Processing and Coincidence Detection
// in Dentate Gyrus Granule Cells. J Neurosci 27:8430-8441
//
// send bug reports and suggestions to christoph.schmidt-hieber@uni-freiburg.de
//
// 2007-08-31: adheres to NetworkReadyCell policy
//
// ----------------------------------------------------------------------------
// load gui or stdrun:
load_file("stdrun.hoc")
load_file("./genutils.hoc")
load_file("./calcSpines.hoc")
load_file("./fixnseg.hoc")
begintemplate cell_10
public is_art, has_bleb, axon_diam0
public init, topol, basic_shape, subsets, geom, biophys, geom_nseg, biophys_inhomo
public synlist, x, y, z, position, connect2target
public somaLoc,somaBorderLoc,blebLoc,distalDendLoc,proxDendLoc,synDendLoc,spineCount,n_sections,n_axon,n_soma
public section, axon
public all,den,axo,som
external verbose,debug_mode,accuracy,calc_spines
external q10_cm,q10_g_pas,q10_Ra,tempScale,geom_nseg_shared,lambda_f
objref somaLoc,somaBorderLoc,blebLoc,distalDendLoc,proxDendLoc,synDendLoc,spineCount,this,synlist
proc init() {
if (numarg() > 0) {
has_bleb = $1
} else {
has_bleb = 0
}
if (numarg() > 1) {
axon_diam0 = $2
} else {
axon_diam0 = 1.2
}
topol()
if (debug_mode) print "Loaded cell, n_sections=",n_sections
subsets()
geom()
biophys()
geom_nseg()
synlist = new List()
synapses()
x = y = z = 0 // only change via position
}
// dummy compartments, will be updated later:
create axon[1], section[1], soma[1]
proc init_spines() {local i
forall insert spines
for i=0,1 section[i] {scale_spines = 1.0}
for i=2,5 section[i] {scale_spines = 1.5}
for i=6,13 section[i] {scale_spines = 2.0}
for i=14,n_sections-1 section[i] {scale_spines = 2.5}
}
func fsigm() {
// $1: x
// $2: amplitude
// $3: center
// $4: slope
return $2-$2/(1.0+exp(($1-$3)/$4))
}
proc init_pas() {local Ra_soma, Ra_axon, i, dist
Ra_soma = 200
Ra_axon = 120
forall {
insert pas
e_pas=0
cm = 1.00 * tempScale(q10_cm) * scale_spines
g_pas = 2.5e-5 * tempScale(q10_g_pas) * scale_spines
Ra = 200.0 * tempScale(q10_Ra)
}
somaLoc.secRef.sec { distance(0,0) }
for i=0, n_axon-1 axon[i] {
dist = distance(0.5)
Ra = (Ra_soma - fsigm(dist, Ra_soma-Ra_axon, 100, 50)) * tempScale(q10_Ra)
}
}
proc basic_shape() {local i, soma_rad, soma_lhalf, soma_part0, soma_part1, diam0, diam1, soma_diam0, delta, axon_diam1
n_sections = 2 + 4 + 8 + 16
create section[n_sections]
if (has_bleb == 1) {
n_axon = 7
} else {
n_axon = 9
}
create axon[n_axon]
// Set nseg to something > 1 so that
// the tapering works
for i=0, n_axon-1 axon[i] { nseg=5 }
n_soma = 21
create soma[n_soma]
soma_rad = 5
soma_lhalf = 10
offset = 0.15 // offset to prevent soma from tapering too much
// elliptic soma:
for i=0, n_soma-1 soma[i] {
L = soma_lhalf * 2.0/n_soma
soma_part0 = (-1.0 + 2.0*(i+offset/2.0)/ (n_soma+offset) ) * soma_lhalf * 0.98
soma_part1 = (-1.0 + 2.0*(i+1+offset/2.0)/ (n_soma+offset) ) * soma_lhalf * 0.98
diam0 = sqrt((1 - soma_part0*soma_part0/ (soma_lhalf*soma_lhalf)) * soma_rad*soma_rad) * 2.0
diam1 = sqrt((1 - soma_part1*soma_part1/ (soma_lhalf*soma_lhalf)) * soma_rad*soma_rad) * 2.0
diam(0:1) = diam0:diam1
if (i==0) {
soma_diam0 = diam0
}
}
axon[0] { diam(0:1)=soma_diam0:axon_diam0 L = 8 }
// linear taper:
axon_diam1 = 0.3
delta = (axon_diam0-axon_diam1) / 20.0
for i=1,5 axon[i] {
L = 4
diam(0:1)=axon_diam0-(i-1)*delta*L : axon_diam0-i*delta*L
}
if (has_bleb == 1) {
axon[6] {
diam = 2.0
L = 2.0
blebLoc = new Location(0.0)
}
} else {
axon[6] {
diam = axon_diam1 L = 500
blebLoc = new Location(0.0)
}
// mfb
axon[7] {
diam = 3.0 // 0.4
L = 3.0 // 3.0
}
axon[8] { diam = axon_diam1 L = 470 }
}
for i=0,1 section[i] { diam(0:1)=soma[n_soma-1].diam(1.0):2.0 L=20 }
for i=2,5 section[i] { diam(0:1)=2.0:1.5 L=80 }
for i=6,13 section[i] { diam = 0.9 L=100 }
for i=14,n_sections-1 section[i] { diam=0.6 L=100 }
// define soma:
soma[n_soma/2.0] somaLoc = new Location(0.5)
soma[0] somaBorderLoc = new Location(0.0)
// define dendritic sites:
section[n_sections-1] distalDendLoc = new Location(0.8)
section[1] proxDendLoc = new Location(0.05)
section[n_sections-5] synDendLoc = new Location(0.8)
access somaLoc.secRef.sec
}
proc topol() {local i
basic_shape()
for i=0,1 section[i] { connect section[i](0.0), soma[n_soma-1](1.0) }
for i=2,n_sections-1 section[i] { connect section[i](0.0), section[int((i-2)/2.0)](1.0) }
for i=1, n_soma-1 soma[i] { connect soma[i](0.0), soma[i-1](1.0) }
connect axon[0](0.0), soma[0](0.0)
for i=1, n_axon-1 axon[i] { connect axon[i](0.0), axon[i-1](1.0) }
init_spines()
}
objref all,den,axo,som
proc subsets() {local i
all = new SectionList()
for i=0, n_sections-1 section[i] all.append()
for i=0, n_axon-1 axon[i] all.append()
for i=0, n_soma-1 soma[i] all.append()
den = new SectionList()
for i=0, n_sections-1 section[i] den.append()
axo = new SectionList()
for i=0, n_axon-1 axon[i] axo.append()
som = new SectionList()
for i=0, n_soma-1 soma[i] som.append()
}
proc geom() {
}
proc geom_nseg() {
geom_nseg_shared()
// increase nseg even further (tribute to Josef):
if (accuracy >= 1) {
forall nseg*=3
}
}
proc biophys() {
init_pas()
}
proc biophys_inhomo(){}
proc position() { local i
somaLoc.secRef.sec 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 = $3
}
obfunc connect2target() {localobj nc //$o1 target point process, optional $o2 returned NetCon
axon[0] nc = new NetCon(&v(0), $o1)
nc.threshold = 10
if (numarg() == 2) { $o2 = nc } // for backward compatibility
return nc
}
objref syn_
proc synapses() {
}
func is_art() { return 0 }
endtemplate cell_10