/****************************************************************************
Copyright (c) California Institute of Technology, 2006 -- All Rights Reserved
Royalty free license granted for non-profit research and educational purposes.
******************************************************************************/
/*
These file contains utilities used by the main program to setup the
cell and perform some miscellaneous aspects of the simulation.
There are 3 sections:
Making Lists
Defining The Number of Compartments
Simulated Synaptic Input
*/
// --------------------------------------------------------------
// MAKING LISTS
// --------------------------------------------------------------
/*
These procedures serve the purpose of separating the classification of
dendrites from the initialization of their properties (in
membrane_init.) The general idea is based on Poirazi et al. (2003)
although the specifics of the implemenation are changed.
*/
/***********************************************************
make_apical_lists()
This procedure further classifies apical dendrites based on their
diameter. It assumes that the section list apical_sections has
already been define. The parameters setting the diameter limits are
defined in the standard parameter set for a cell type
(i.e. ca1pyr_standard_params for d151).
*/
proc make_apical_lists() {
trunk_sections = new SectionList()
oblique_sections = new SectionList()
tuft_sections = new SectionList()
print "Making make_apical_lists..."
forsec apical_sections {
if (n3d() == 0) {
continue
}
if (diam3d(0) >= trunk_min_diam) {
trunk_sections.append()
}
if (diam3d(0) < trunk_min_diam && diam3d(0) > tuft_max_diam) {
oblique_sections.append()
}
if (diam3d(0) <= tuft_max_diam) {
tuft_sections.append()
}
}
}
/****************************************************************
make_lists()
Simply divide the sections up into lists based on their names.
The categories used are:
soma
nodes of ranvier
myelinated sections
apical
basal
We assume a naming convention where the apical dendrites
will always have 'apical' somewhere in their name somewhere.
Basal is used as a default for any sections whose name does
not match anything else. So a dendrite named "dend_x" would
be listed as basal.
If you use a cell with a different naming convention for the sections
you would have to change the name patterns in this method. (The best
way to do this would be to make if .. else ... alternatives based on
the neuron_name and/or cell_type variables defined in the cell file.)
*/
proc make_lists() {
node_sections = new SectionList()
my_sections = new SectionList()
basal_sections = new SectionList()
apical_sections = new SectionList()
forall {
if (issection("soma")) {
soma_ref = new SectionRef()
continue
}
if (issection("iseg")) {
iseg_ref = new SectionRef()
continue
}
if (issection("hill")) {
hill_ref = new SectionRef()
continue
}
if (issection(".*myelin.*")) {
my_sections.append()
continue
}
if ( issection(".*node.*")) {
node_sections.append()
continue
}
// after soma, axon, apical, basal (default dendrite) should be the only option left
if (issection(".*apical.*")) {
apical_sections.append()
} else {
basal_sections.append()
}
}
// further categorize the apical sections based on diameter and distance
make_apical_lists()
}
// --------------------------------------------------------------
// DEFINING COMPARTMENTS
// --------------------------------------------------------------
/*
This procedure and function define the number of compartments using
the "D-Lambda" method described in Hines & Carnevale (2001). These
procedures are actually called from membrane_init.hoc when the
properties of the membrane are setup.
*/
/**********************************************************
calc_nsegs_dlambda()
Calculates the number of segments for the currently accessed section
based on the dlambda criteria (but without actually setting the number
of segments)
*/
func calc_nsegs_dlambda() {local ns, lambda_f100
lambda_f100 = 0
ns = 0
lambda_f100 = .5 * sqrt(diam/(Ra*100*cm*100*PI))*1e6
ns = int(L/(my_dlambda*lambda_f100))
// make sure to always use an odd number of segments
if ((ns % 2) == 0) {
ns = ns+1
}
return ns
}
/************************************************************
define_nsegs(section, max_compartment_length)
$o1 = sections to do it for
$2 = max seg length param to force more segs in wide sections
Takes in a section as an argument and sets the number of compartments
(nseg). The procedures also accepts a "maximum_compartment_length"
parameter and the number of compartments is set to the greater of the
number based on dlambda and the number based on simple length
consideration. This is useful for the apical trunk where the dlambda
method would chooser longer compartments than I would prefer based on
"aesthetic considerations" such as the need to have plots of the
compartment details at specific locations. If not then a zero
max_length is used the default is just the dlambda calculation.
*/
proc define_nsegs() {local lam_ns, max_length, min_ns
tmp_ref = $o1
max_length = $2
forsec tmp_ref {
if (max_length != 0) {
min_ns = int(L/max_length + 0.5) // make int() round up with + 0.5
// make sure to always use an odd number of segments
if ((min_ns % 2) == 0) {
min_ns = min_ns+1
}
} else {
min_ns = 0
}
lam_ns = calc_nsegs_dlambda()
if (min_ns < lam_ns) {
nseg = lam_ns
} else {
nseg = min_ns
}
}
}
//---------------------------------------------------------------
// SIMULATED SYNAPTIC INPUT
//----------------------------------------------------------------
/* These procedures implement the system of simulated synaptic input
as described in Gold et al. (2006): Synaptic input is simulated with
the passive (pas) mechanism by simply setting the reversal potential
to be above threshold and increasing the conductance. It is originally
based on the system used by Holt and Koch (1999).
*/
/****************************************************************
Global variables for synaptic input.
*/
syn_in_on = 0 // =1 when the synaptic input is currently turned on
syn_in_on_time = 0 // = the exact time at which it was turned on
/****************************************************************
set_syn_in_for_sec(epas_new, gpas_ratio)
Modifies the passive mechanism for the current section
$1 = new epas
$2 = change gpas factor
*/
proc set_syn_in_for_sec() {local epas_new, gpas_ratio, g_pas_old
epas_new = $1
gpas_ratio = $2
e_pas = epas_new
g_pas_old = g_pas
g_pas = g_pas_old*gpas_ratio
// print "Setting synaptic input to " , secname(), ", gpas_old=", g_pas_old, ", gpas_new=", g_pas , ", epas=" , e_pas
}
/****************************************************************
do_sim_syn_input()
Logic controlling turing synaptic input on/off. The function returns
1 on the call where the input is turned on and and -1 on the call
where the input is turned off, otherwise it returns 0. The procedure
is called on each iteration of the main loop and it uses pre-defined
parameters and the 2 global variables (above) to determine what to do.
Five variables should be set in the cell specific parameters file to
control the simulated synaptic input:
Note that the call to cvode.reinit is required after turning the
simulated synaptic input on/off as the procedure changes the state
variables of the the passive mechanism.
syn_input_del = delay before starting the input
syn_input_dur = how long the input should last
epas_syn_input = the reversal potential for the passive mechanism to
use during synaptic input
gpas_syn_input = the factor by which to increase the passive mechanism
conductance during synaptic input
min_dist_syn_input = the minimum distance from the soma for a dendrite
to receive simulated synaptic input
*/
func do_sim_syn_input() {
if (gpas_syn_input_apical==0 && gpas_syn_input_basal==0) {
return 0.0
}
soma_ref.sec { distance(0,0.5) }
if ((t >= syn_input_del) && (syn_in_on == 0) && (syn_in_on_time == 0)) {
syn_in_on = 1
syn_in_on_time = t
if (VERBOSE == 1) {
print "***********************************************************"
print "ADDING SIMULATED SYNAPTIC INPUT TO DENDRITIC SECTIONS!!!!!!"
print "epas_syn_input_apical = ", epas_syn_input_apical
print "gpas_syn_input_apical = ", gpas_syn_input_apical
print "epas_syn_input_basal = ", epas_syn_input_basal
print "gpas_syn_input_basal = ", gpas_syn_input_basal
print "***********************************************************"
}
// adding input to all basal sections beyond the minimum distance...
if (gpas_syn_input_basal!=0) {
forsec basal_sections {
if (distance(0) > min_dist_syn_input) {
set_syn_in_for_sec(epas_syn_input_basal, gpas_syn_input_basal)
}
}
}
// adding input to all apical sections beyond the minimum distance...
if (gpas_syn_input_apical!=0) {
forsec apical_sections {
if (distance(0) > min_dist_syn_input) {
set_syn_in_for_sec(epas_syn_input_apical, gpas_syn_input_apical)
}
}
}
cvode.re_init()
return 1.0
} else if ((t >= syn_in_on_time+syn_input_dur) && (syn_in_on ==1)) {
syn_in_on = 0
if (VERBOSE == 1) {
print "***************************************************************"
print "REMOVING SIMULATED SYNAPTIC INPUT FROM DENDRITIC SECTIONS!!!!!!"
print "***************************************************************"
}
// removing input from all basal sections beyond the minimum distance...
if (gpas_syn_input_basal!=0) {
forsec basal_sections {
if (distance(0) > min_dist_syn_input) {
set_syn_in_for_sec(V_rest, (1/gpas_syn_input_basal))
}
}
}
// removing input from all apical sections beyond the minimum distance..
if (gpas_syn_input_apical!=0) {
forsec apical_sections {
if (distance(0) > min_dist_syn_input) {
set_syn_in_for_sec(V_rest, (1/gpas_syn_input_apical))
}
}
}
cvode.re_init()
return -1.0
}
return 0.0
}
/****************************************************************
do_sim_syn_input()
Addds the time of that synaptic input is turned/on off to the
event queue to ensure that it will take place exactly at that
time.
*/
proc setup_sim_syn_input() {
if (!(gpas_syn_input_apical == 0 && gpas_syn_input_basal==0)) {
print "-> Adding Cvode events for synaptic input on/off, t=", syn_input_del, " & ", syn_input_del + syn_input_dur
cvode.event(syn_input_del)
cvode.event(syn_input_del + syn_input_dur)
}
}