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718 lines
27 KiB
718 lines
27 KiB
from __future__ import print_function |
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from neuron import h |
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from ..util import nstomho |
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from ..util import Params |
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import numpy as np |
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from .cell import Cell |
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from .. import data |
|
|
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""" |
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Original hoc code from RMmodel.hoc |
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// including the "Octopus" cell: |
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proc set_Type2o() { |
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gbar_na = nstomho(1000) |
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gbar_kht = nstomho(150) |
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gbar_klt = nstomho(600) |
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gbar_ka = nstomho(0) |
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gbar_ih = nstomho(0) |
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gbar_hcno = nstomho(40) |
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gbar_leak = nstomho(2) |
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model = 6 |
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modelname = "Type IIo (Octopus)" |
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vm0 = -66.67 |
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} |
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|
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""" |
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|
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__all__ = ["Octopus", "OctopusRothman", "OctopusSpencer"] |
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|
|
|
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class Octopus(Cell): |
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|
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type = "octopus" |
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|
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@classmethod |
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def create(cls, modelType="RM03", **kwds): |
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if modelType in ["RM03", "II-o"]: |
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return OctopusRothman(**kwds) |
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elif modelType == "Spencer": |
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return OctopusSpencer(**kwds) |
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else: |
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raise ValueError("Octopus cell type %s is unknown" % modelType) |
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|
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def make_psd(self, terminal, psd_type, **kwds): |
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""" |
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Connect a presynaptic terminal to one post section at the specified location, with the fraction |
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of the "standard" conductance determined by gbar. |
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The default condition is to try to pass the default unit test (loc=0.5) |
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|
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Parameters |
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---------- |
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terminal : Presynaptic terminal (NEURON object) |
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|
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psd_type : either simple or multisite PSD for bushy cell |
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|
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kwds: dict of options. Two are currently handled: |
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postsize : expect a list consisting of [sectionno, location (float)] |
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AMPAScale : float to scale the ampa currents |
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|
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""" |
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if ( |
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"postsite" in kwds |
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): # use a defined location instead of the default (soma(0.5) |
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postsite = kwds["postsite"] |
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loc = postsite[1] # where on the section? |
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uname = ( |
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"sections[%d]" % postsite[0] |
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) # make a name to look up the neuron section object |
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post_sec = self.hr.get_section(uname) # Tell us where to put the synapse. |
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else: |
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loc = 0.5 |
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post_sec = self.soma |
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|
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if psd_type == "simple": |
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if terminal.cell.type in ["sgc"]: |
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weight = data.get( |
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"%s_synapse" % terminal.cell.type, |
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species=self.species, |
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post_type=self.type, |
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field="weight", |
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) |
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tau1 = data.get( |
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"%s_synapse" % terminal.cell.type, |
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species=self.species, |
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post_type=self.type, |
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field="tau1", |
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) |
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tau2 = data.get( |
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"%s_synapse" % terminal.cell.type, |
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species=self.species, |
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post_type=self.type, |
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field="tau2", |
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) |
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erev = data.get( |
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"%s_synapse" % terminal.cell.type, |
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species=self.species, |
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post_type=self.type, |
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field="erev", |
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) |
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return self.make_exp2_psd( |
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post_sec, |
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terminal, |
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weight=weight, |
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loc=loc, |
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tau1=tau1, |
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tau2=tau2, |
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erev=erev, |
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) |
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else: |
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raise TypeError( |
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"Cannot make simple PSD for %s => %s" |
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% (terminal.cell.type, self.type) |
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) |
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|
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elif psd_type == "multisite": |
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if terminal.cell.type == "sgc": |
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# Max conductances for the glu mechanisms are calibrated by |
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# running `synapses/tests/test_psd.py`. The test should fail |
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# if these values are incorrect |
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self.AMPAR_gmax = ( |
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data.get( |
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"sgc_synapse", |
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species=self.species, |
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post_type=self.type, |
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field="AMPAR_gmax", |
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) |
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* 1e3 |
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) |
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self.NMDAR_gmax = ( |
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data.get( |
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"sgc_synapse", |
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species=self.species, |
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post_type=self.type, |
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field="NMDAR_gmax", |
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) |
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* 1e3 |
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) |
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self.Pr = data.get( |
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"sgc_synapse", species=self.species, post_type=self.type, field="Pr" |
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) |
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# adjust gmax to correct for initial Pr |
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self.AMPAR_gmax = self.AMPAR_gmax / self.Pr |
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self.NMDAR_gmax = self.NMDAR_gmax / self.Pr |
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# AMPA_gmax = 3.314707700918133*1e3 # factor of 1e3 scales to pS (.mod mechanisms) from nS. |
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# NMDA_gmax = 0.4531929783503451*1e3 |
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if "AMPAScale" in kwds: |
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self.AMPAR_gmax = ( |
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self.AMPAR_gmax * kwds["AMPAScale"] |
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) # allow scaling of AMPA conductances |
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if "NMDAScale" in kwds: |
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self.NMDAR_gmax = self.NMDAR_gmax * kwds["NMDAScale"] |
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return self.make_glu_psd( |
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post_sec, terminal, self.AMPAR_gmax, self.NMDAR_gmax, loc=loc |
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) |
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elif terminal.cell.type == "dstellate": |
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return self.make_gly_psd(post_sec, terminal, psdtype="glyslow", loc=loc) |
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else: |
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raise TypeError( |
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"Cannot make PSD for %s => %s" % (terminal.cell.type, self.type) |
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) |
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else: |
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raise ValueError("Unsupported psd type %s" % psd_type) |
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|
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|
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class OctopusRothman(Octopus, Cell): |
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""" |
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VCN octopus cell model (point cell). |
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Rothman and Manis, 2003abc (Type II, with high gklt and hcno - octopus cell h current). |
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""" |
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|
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def __init__( |
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self, |
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morphology=None, |
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decorator=None, |
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nach=None, |
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ttx=False, |
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species="guineapig", |
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modelType=None, |
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debug=False, |
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): |
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""" |
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initialize the octopus cell, using the default parameters for guinea pig from |
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R&M2003, as a type II cell with modified conductances. |
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Modifications to the cell can be made by calling methods below. |
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|
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Parameters |
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---------- |
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morphology : string (default: None) |
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a file name to read the cell morphology from. If a valid file is found, a cell is constructed |
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as a cable model from the hoc file. |
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If None (default), the only a point model is made, exactly according to RM03. |
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|
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decorator : Python function (default: None) |
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decorator is a function that "decorates" the morphology with ion channels according |
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to a set of rules. |
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If None, a default set of channels aer inserted into the first soma section, and the |
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rest of the structure is "bare". |
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|
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nach : string (default: None) |
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nach selects the type of sodium channel that will be used in the model. A channel mechanism |
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by that name must exist. None implies the default channel (jsrna for this model). |
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|
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ttx : Boolean (default: False) |
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If ttx is True, then the sodium channel conductance is set to 0 everywhere in the cell. |
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Currently, this is not implemented. |
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|
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species: string (default 'guineapig') |
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species defines the channel density that will be inserted for different models. Note that |
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if a decorator function is specified, this argument is ignored. |
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|
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modelType: string (default: None) |
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modelType specifies the type of the model that will be used (e.g., "II", "II-I", etc). |
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modelType is passed to the decorator, or to species_scaling to adjust point models. |
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|
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debug: boolean (default: False) |
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debug is a boolean flag. When set, there will be multiple printouts of progress and parameters. |
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|
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Returns |
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------- |
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Nothing |
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""" |
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|
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super(OctopusRothman, self).__init__() |
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if modelType == None: |
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modelType = "II-o" |
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if nach == None and species == "guineapig": |
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nach = "jsrna" |
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if nach == None and species == "mouse": |
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nach = "nacn" |
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self.status = { |
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"soma": True, |
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"axon": False, |
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"dendrites": False, |
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"pumps": False, |
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"na": nach, |
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"species": species, |
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"modelType": modelType, |
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"ttx": ttx, |
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"name": "Octopus", |
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"morphology": morphology, |
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"decorator": decorator, |
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"temperature": None, |
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} |
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self.i_test_range = {"pulse": (-4.0, 4.0, 0.2)} |
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self.spike_threshold = -50 |
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self.vrange = [-70.0, -57.0] # set a default vrange for searching for rmp |
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|
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if morphology is None: |
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""" |
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instantiate a basic soma-only ("point") model |
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""" |
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soma = h.Section( |
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name="Octopus_Soma_%x" % id(self) |
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) # one compartment of about 29000 um2 |
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soma.nseg = 1 |
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self.add_section(soma, "soma") |
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else: |
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""" |
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instantiate a structured model with the morphology as specified by |
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the morphology file |
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""" |
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self.set_morphology(morphology_file=morphology) |
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|
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# decorate the morphology with ion channels |
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if decorator is None: # basic model, only on the soma |
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self.e_leak = -73.0 # from McGinley et al., 2016 |
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self.e_h = -38.0 # from McGinley et al. |
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self.R_a = 195 # McGinley et al. |
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if self.status["species"] == "mouse": |
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self.mechanisms = ["klt", "kht", "hcnobo", "leak", nach] |
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else: |
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self.mechanisms = ["klt", "kht", "ihvcn", "leak", nach] |
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for mech in self.mechanisms: |
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self.soma.insert(mech) |
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self.soma.ek = self.e_k |
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self.soma.ena = self.e_na |
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if self.status["species"] == "mouse": |
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self.soma().hcnobo.eh = self.e_h |
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else: |
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self.soma().ihvcn.eh = self.e_h |
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self.soma().leak.erev = self.e_leak |
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self.soma.Ra = self.R_a |
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self.species_scaling( |
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silent=True, species=species, modelType=modelType |
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) # set the default type II cell parameters |
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else: # decorate according to a defined set of rules on all cell compartments |
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self.decorate() |
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self.save_all_mechs() # save all mechanisms inserted, location and gbar values... |
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self.get_mechs(self.soma) |
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|
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if debug: |
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print("<< octopus: octopus cell model created >>") |
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# print 'Cell created: ', self.status |
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|
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def species_scaling(self, species="guineapig", modelType="II-o", silent=True): |
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""" |
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Adjust all of the conductances and the cell size according to the species requested. |
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Used ONLY for point models. |
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|
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Parameters |
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---------- |
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species : string (default: 'guineapig') |
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name of the species to use for scaling the conductances in the base point model |
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Must be guineapig |
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|
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modelType: string (default: 'II-o') |
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definition of model type from RM03 models, currently limited to type II-o |
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|
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silent : boolean (default: True) |
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run silently (True) or verbosely (False) |
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""" |
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soma = self.soma |
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|
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if species == "guineapig" and modelType == "II-o": |
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self.c_m = 0.9 |
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self.set_soma_size_from_Cm(25.0) |
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self._valid_temperatures = (22.0, 38.0) |
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if self.status["temperature"] is None: |
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self.set_temperature(22.0) |
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sf = 1.0 |
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if ( |
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self.status["temperature"] == 38.0 |
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): # adjust for 2003 model conductance levels at 38 |
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sf = 3.03 # Q10 of 2, 22->38C. (p3106, R&M2003c) |
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# note that kinetics are scaled in the mod file. |
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# self.print_soma_info() |
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self.adjust_na_chans(soma, sf=sf) |
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soma().kht.gbar = sf * nstomho(150.0, self.somaarea) # 6.1 mmho/cm2 |
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soma().klt.gbar = sf * nstomho( |
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1000.0, self.somaarea |
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) # 40.7 mmho/cm2 3195? |
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soma().ihvcn.gbar = sf * nstomho( |
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30.0, self.somaarea |
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) # 7.6 mmho/cm2, cf. Bal and Oertel, Spencer et al. 25 u dia cell 40ns? |
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soma().leak.gbar = sf * nstomho(2.0, self.somaarea) |
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self.axonsf = 1.0 |
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elif species == "mouse" and modelType == "II-o": |
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self.set_soma_size_from_Cm(25.0) |
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self._valid_temperatures = (34.0,) |
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if self.status["temperature"] is None: |
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self.set_temperature(34.0) |
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# self.print_soma_info() |
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self.adjust_na_chans(soma, gbar=3000.0) |
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soma().kht.gbar = nstomho(150.0, self.somaarea) # 6.1 mmho/cm2 |
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soma().klt.gbar = nstomho(3196.0, self.somaarea) # 40.7 mmho/cm2 |
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soma().hcnobo.gbar = nstomho( |
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40.0, self.somaarea |
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) # 7.6 mmho/cm2, cf. Bal and Oertel, Spencer et al. 25 u dia cell |
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soma().leak.gbar = nstomho(2.0, self.somaarea) |
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self.axonsf = 1.0 |
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else: |
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raise ValueError( |
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'Species "%s" or species-type "%s" is not recognized for octopus cells' |
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% (species, type) |
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) |
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self.status["species"] = species |
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self.status["modelType"] = modelType |
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# self.cell_initialize(showinfo=True) |
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self.check_temperature() |
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if not silent: |
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print("set cell as: ", species) |
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print(" with Vm rest = %6.3f" % self.vm0) |
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|
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def adjust_na_chans(self, soma, sf=1.0, gbar=1000.0, debug=False): |
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""" |
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adjust the sodium channel conductance |
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|
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Parameters |
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---------- |
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soma : neuron section object |
|
a soma object whose sodium channel complement will have it's |
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conductances adjusted depending on the channel type |
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|
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gbar : float (default: 1000.) |
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the maximal conductance for the sodium channel |
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|
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debug : boolean (false): |
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verbose printing |
|
|
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Returns |
|
------- |
|
Nothing |
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""" |
|
|
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if self.status["ttx"]: |
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gnabar = 0.0 |
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else: |
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gnabar = sf * nstomho(gbar, self.somaarea) # mmho/cm2 - 4244.1 moh - 4.2441 |
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nach = self.status["na"] |
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if nach == "jsrna": |
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soma().jsrna.gbar = gnabar |
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soma.ena = self.e_na |
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if debug: |
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print("octopus using jsrna, gbar: ", soma().jsrna.gbar) |
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elif nach == "nav11": |
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soma().nav11.gbar = gnabar |
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soma.ena = self.e_na |
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soma().nav11.vsna = 4.3 |
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if debug: |
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print("octopus using inva11, gbar:", soma().nav11.gbar) |
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elif nach in ["na", "nacn"]: |
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soma().nacn.gbar = gnabar |
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soma.ena = self.e_na |
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if debug: |
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print("octopus cell using na/nacn, gbar: ", soma().na.gbar) |
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else: |
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raise ValueError( |
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"Sodium channel %s is not recognized for octopus cells", nach |
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) |
|
|
|
|
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class OctopusSpencer(Octopus, Cell): |
|
""" |
|
VCN octopus cell model (with dendrites). |
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Based on Spencer et al Front. Comput. Neurosci., 22 October 2012 |
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https://doi.org/10.3389/fncom.2012.00083 |
|
""" |
|
|
|
def __init__( |
|
self, |
|
morphology=None, |
|
decorator=None, |
|
nach="jsrna", |
|
ttx=False, |
|
species="guineapig", |
|
modelType=None, |
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debug=False, |
|
): |
|
""" |
|
initialize the octopus cell, using the parameters Spencer et al. 2012 |
|
Modifications to the cell can be made by calling methods below. |
|
|
|
Parameters |
|
---------- |
|
morphology : string (default: None) |
|
a file name to read the cell morphology from. If a valid file is found, a cell is constructed |
|
as a cable model from the hoc file. |
|
If None (default), the only a point model is made, exactly according to RM03. |
|
|
|
decorator : Python function (default: None) |
|
decorator is a function that "decorates" the morphology with ion channels according |
|
to a set of rules. |
|
If None, a default set of channels aer inserted into the first soma section, and the |
|
rest of the structure is "bare". |
|
|
|
nach : string (default: 'na') |
|
nach selects the type of sodium channel that will be used in the model. A channel mechanism |
|
by that name must exist. |
|
|
|
ttx : Boolean (default: False) |
|
If ttx is True, then the sodium channel conductance is set to 0 everywhere in the cell. |
|
Currently, this is not implemented. |
|
|
|
species: string (default 'guineapig') |
|
species defines the channel density that will be inserted for different models. Note that |
|
if a decorator function is specified, this argument is ignored. |
|
|
|
modelType: string (default: None) |
|
modelType specifies the type of the model that will be used (e.g., "II", "II-I", etc). |
|
modelType is passed to the decorator, or to species_scaling to adjust point models. |
|
|
|
debug: boolean (default: False) |
|
debug is a boolean flag. When set, there will be multiple printouts of progress and parameters. |
|
|
|
Returns |
|
------- |
|
Nothing |
|
""" |
|
|
|
super(OctopusSpencer, self).__init__() |
|
if modelType == None: |
|
modelType = "Spencer" |
|
self.status = { |
|
"soma": True, |
|
"axon": False, |
|
"dendrites": False, |
|
"pumps": False, |
|
"na": nach, |
|
"species": species, |
|
"modelType": modelType, |
|
"ttx": ttx, |
|
"name": "Octopus", |
|
"morphology": morphology, |
|
"decorator": decorator, |
|
"temperature": None, |
|
} |
|
self.i_test_range = (-4.0, 6.0, 0.25) |
|
self.spike_threshold = -50 |
|
self.vrange = [-75.0, -63.0] # set a default vrange for searching for rmp |
|
|
|
if morphology is None: |
|
""" |
|
instantiate a basic soma-only ("point") model |
|
""" |
|
soma = h.Section( |
|
name="Octopus_Soma_%x" % id(self) |
|
) # one compartment of about 29000 um2 |
|
soma.nseg = 1 |
|
self.add_section(soma, "soma") |
|
self.set_soma_size_from_Section(self.soma) |
|
|
|
else: |
|
""" |
|
instantiate a structured model with the morphology as specified by |
|
the morphology file |
|
""" |
|
self.set_morphology(morphology_file=morphology) |
|
|
|
# decorate the morphology with ion channels |
|
if decorator is None: # basic model, only on the soma |
|
self.e_leak = -62.0 # from Spencer et al., 2012 |
|
self.e_h = -38.0 ## from Spencer et al., 2012 |
|
self.R_a = 100.0 # from Spencer et al., 2012 |
|
self.mechanisms = ["klt", "kht", "hcnobo", "leak", nach] |
|
for mech in self.mechanisms: |
|
self.soma.insert(mech) |
|
self.soma.ek = -70.0 # self.e_k |
|
self.soma.ena = 55.0 # self.e_na |
|
self.soma().hcnobo.eh = self.e_h |
|
self.soma().leak.erev = self.e_leak |
|
self.soma.Ra = self.R_a |
|
self.species_scaling( |
|
silent=True, species=species, modelType=modelType |
|
) # set the default type II cell parameters |
|
else: # decorate according to a defined set of rules on all cell compartments |
|
self.decorate() |
|
self.decorated.channelValidate(self, verify=True) |
|
# print 'Mechanisms inserted: ', self.mechanisms |
|
self.get_mechs(self.soma) |
|
# self.cell_initialize(vrange=self.vrange) |
|
|
|
if debug: |
|
print("<< octopus: octopus cell model created >>") |
|
# print 'Cell created: ', self.status |
|
|
|
def channel_manager(self, modelType="Spencer"): |
|
""" |
|
This routine defines channel density maps and distance map patterns |
|
for each type of compartment in the cell. The maps |
|
are used by the ChannelDecorator class (specifically, it's private |
|
\_biophys function) to decorate the cell membrane. |
|
|
|
Parameters |
|
---------- |
|
modelType : string (default: 'Spencer') |
|
A string that defines the type of the model. Currently, 1 type is implemented: |
|
Spencer : Spencer et al Front. Comput. Neurosci. 2012 |
|
|
|
Returns |
|
------- |
|
Nothing |
|
|
|
Notes |
|
----- |
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This routine defines the following variables for the class: |
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# conductances (gBar) |
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# a channelMap (dictonary of channel densities in defined anatomical compartments) |
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# a current injection range for IV's (when testing) |
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# a distance map, which defines how selected conductances in selected compartments |
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will change with distance. This includes both linear and exponential gradients, |
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the minimum conductance at the end of the gradient, and the space constant or |
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slope for the gradient. |
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""" |
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|
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# |
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# Create a model based on the Spencer model |
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# Channel decoration and stick model from Figure 2 |
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# densities from Tables 2 and 3 |
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if modelType == "Spencer": |
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# print self.c_m |
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self.c_m = 0.9 |
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# self.set_soma_size_from_Section(self.soma) |
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totcap = self.totcap |
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refarea = self.somaarea # totcap / self.c_m # see above for units |
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# self.print_soma_info() |
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self._valid_temperatures = ( |
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34.0, |
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) # 34 for consistency with other mouse models, but |
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# Spencer data used "33". This affects very slightly |
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# the HCN channel conductance. |
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if self.status["temperature"] is None: |
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self.set_temperature(34.0) |
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self.gBar = Params( |
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nabar=0.0, # 0.0407, # S/cm2 |
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nabar_ais=0.42441, |
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kltbar_ais=0.0, |
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khtbar_ais=0.0, |
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ihbar_ais=0.0, |
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kltbar_soma=0.0407, |
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khtbar_soma=0.0061, |
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ihbar_soma=0.0076, |
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kltbar_dend=0.0027, |
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khtbar_dend=0.0, |
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ihbar_dend=0.0006, |
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khtbar_hillock=0.0, |
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kltbar_hillock=0.0, |
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ihbar_hillock=0.0, |
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leakbar=0.0020, |
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) |
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self.channelMap = { |
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"soma": { |
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"jsrna": self.gBar.nabar, |
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"klt": self.gBar.kltbar_soma, |
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"kht": self.gBar.khtbar_soma, |
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"hcnobo": self.gBar.ihbar_soma, |
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"leak": self.gBar.leakbar, |
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}, |
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"hillock": { |
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"jsrna": 0.0, |
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"klt": self.gBar.kltbar_hillock, |
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"kht": self.gBar.khtbar_hillock, |
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"hcnobo": self.gBar.ihbar_hillock, |
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"leak": self.gBar.leakbar, |
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}, |
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# axon initial segment: |
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"unmyelinatedaxon": { |
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"jsrna": self.gBar.nabar_ais, |
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"klt": self.gBar.kltbar_ais, |
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"kht": self.gBar.khtbar_ais, |
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"hcnobo": self.gBar.ihbar_ais, |
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"leak": self.gBar.leakbar, |
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}, |
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"primarydendrite": { |
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"jsrna": 0.0, |
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"klt": self.gBar.kltbar_dend, |
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"kht": self.gBar.khtbar_dend, |
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"hcnobo": self.gBar.ihbar_dend, |
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"leak": self.gBar.leakbar, |
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}, |
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} |
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self.distMap = { |
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"primarydendrite": { |
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"klt": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0}, |
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"kht": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0}, |
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"hcnobo": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0}, |
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} # all flat with distance |
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} |
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# reversal potential map |
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self.channelErevMap = { |
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"soma": { |
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"jsrna": 55.0, |
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"klt": -70, |
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"kht": -70, |
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"hcnobo": -38, |
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"leak": -62.0, |
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}, |
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"hillock": { |
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"jsrna": 55.0, |
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"klt": -70, |
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"kht": -70, |
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"hcnobo": -38, |
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"leak": -62.0, |
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}, |
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"unmyelinatedaxon": { |
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"jsrna": 55.0, |
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"klt": -70, |
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"kht": -70, |
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"hcnobo": -38, |
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"leak": -62.0, |
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}, |
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"primarydendrite": { |
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"jsrna": 55.0, |
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"klt": -70, |
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"kht": -70, |
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"hcnobo": -38, |
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"leak": -62.0, |
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}, |
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} |
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else: |
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raise ValueError("model type %s is not implemented" % modelType) |
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self.check_temperature() |
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|
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def species_scaling(self, species="mouse", modelType="Spencer", silent=True): |
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""" |
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Adjust all of the conductances and the cell size according to the species requested. |
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Used ONLY for point models. |
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Parameters |
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---------- |
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species : string (default: 'guineapig') |
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name of the species to use for scaling the conductances in the base point model |
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Must be guineapig |
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modelType: string (default: 'II-o') |
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definition of model type from RM03 models, currently limited to type II-o |
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silent : boolean (default: True) |
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run silently (True) or verbosely (False) |
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""" |
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soma = self.soma |
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if species == "mouse" and modelType == "Spencer": |
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print("Octopus: Mouse, Spencer point model - not a valid model") |
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self.set_soma_size_from_Cm(25.0) |
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self._valid_temperatures = (34.0,) |
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if self.status["temperature"] is None: |
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self.set_temperature(34.0) |
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self.print_soma_info() |
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# self.adjust_na_chans(soma) |
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# soma().kht.gbar = 0.0061 # nstomho(150.0, self.somaarea) # 6.1 mmho/cm2 |
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# soma().klt.gbar = 0.0407 # nstomho(3196.0, self.somaarea) # 40.7 mmho/cm2 |
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# soma().hcnobo.gbar = 0.0076 #nstomho(40.0, self.somaarea) # 7.6 mmho/cm2, cf. Bal and Oertel, Spencer et al. 25 u dia cell |
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# soma().leak.gbar = 0.0005 # nstomho(2.0, self.somaarea) |
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self.axonsf = 1.0 |
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else: |
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raise ValueError( |
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'Species "%s" or species-type "%s" is not recognized for octopus cells' |
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% (species, type) |
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) |
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self.status["species"] = species |
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self.status["modelType"] = modelType |
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self.cell_initialize(showinfo=True) |
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if not silent: |
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print("set cell as: ", species) |
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print(" with Vm rest = %6.3f" % self.vm0)
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