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719 lines
27 KiB
719 lines
27 KiB
2 years ago
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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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__all__ = ["Octopus", "OctopusRothman", "OctopusSpencer"]
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class Octopus(Cell):
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type = "octopus"
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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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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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Parameters
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----------
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terminal : Presynaptic terminal (NEURON object)
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psd_type : either simple or multisite PSD for bushy cell
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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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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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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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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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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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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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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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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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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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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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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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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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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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Returns
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-------
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Nothing
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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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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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# 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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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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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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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 == "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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|
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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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|
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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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|
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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(
|
||
|
|
'Species "%s" or species-type "%s" is not recognized for octopus cells'
|
||
|
|
% (species, type)
|
||
|
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)
|
||
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self.status["species"] = species
|
||
|
|
self.status["modelType"] = modelType
|
||
|
|
# self.cell_initialize(showinfo=True)
|
||
|
|
self.check_temperature()
|
||
|
|
if not silent:
|
||
|
|
print("set cell as: ", species)
|
||
|
|
print(" with Vm rest = %6.3f" % self.vm0)
|
||
|
|
|
||
|
|
def adjust_na_chans(self, soma, sf=1.0, gbar=1000.0, debug=False):
|
||
|
|
"""
|
||
|
|
adjust the sodium channel conductance
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
soma : neuron section object
|
||
|
|
a soma object whose sodium channel complement will have it's
|
||
|
|
conductances adjusted depending on the channel type
|
||
|
|
|
||
|
|
gbar : float (default: 1000.)
|
||
|
|
the maximal conductance for the sodium channel
|
||
|
|
|
||
|
|
debug : boolean (false):
|
||
|
|
verbose printing
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Nothing
|
||
|
|
"""
|
||
|
|
|
||
|
|
if self.status["ttx"]:
|
||
|
|
gnabar = 0.0
|
||
|
|
else:
|
||
|
|
gnabar = sf * nstomho(gbar, self.somaarea) # mmho/cm2 - 4244.1 moh - 4.2441
|
||
|
|
nach = self.status["na"]
|
||
|
|
if nach == "jsrna":
|
||
|
|
soma().jsrna.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
if debug:
|
||
|
|
print("octopus using jsrna, gbar: ", soma().jsrna.gbar)
|
||
|
|
elif nach == "nav11":
|
||
|
|
soma().nav11.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
soma().nav11.vsna = 4.3
|
||
|
|
if debug:
|
||
|
|
print("octopus using inva11, gbar:", soma().nav11.gbar)
|
||
|
|
elif nach in ["na", "nacn"]:
|
||
|
|
soma().nacn.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
if debug:
|
||
|
|
print("octopus cell using na/nacn, gbar: ", soma().na.gbar)
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
"Sodium channel %s is not recognized for octopus cells", nach
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
class OctopusSpencer(Octopus, Cell):
|
||
|
|
"""
|
||
|
|
VCN octopus cell model (with dendrites).
|
||
|
|
Based on Spencer et al Front. Comput. Neurosci., 22 October 2012
|
||
|
|
https://doi.org/10.3389/fncom.2012.00083
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
morphology=None,
|
||
|
|
decorator=None,
|
||
|
|
nach="jsrna",
|
||
|
|
ttx=False,
|
||
|
|
species="guineapig",
|
||
|
|
modelType=None,
|
||
|
|
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
|
||
|
|
-----
|
||
|
|
This routine defines the following variables for the class:
|
||
|
|
# conductances (gBar)
|
||
|
|
# a channelMap (dictonary of channel densities in defined anatomical compartments)
|
||
|
|
# a current injection range for IV's (when testing)
|
||
|
|
# a distance map, which defines how selected conductances in selected compartments
|
||
|
|
will change with distance. This includes both linear and exponential gradients,
|
||
|
|
the minimum conductance at the end of the gradient, and the space constant or
|
||
|
|
slope for the gradient.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
#
|
||
|
|
# Create a model based on the Spencer model
|
||
|
|
# Channel decoration and stick model from Figure 2
|
||
|
|
# densities from Tables 2 and 3
|
||
|
|
if modelType == "Spencer":
|
||
|
|
# print self.c_m
|
||
|
|
self.c_m = 0.9
|
||
|
|
# self.set_soma_size_from_Section(self.soma)
|
||
|
|
totcap = self.totcap
|
||
|
|
refarea = self.somaarea # totcap / self.c_m # see above for units
|
||
|
|
# self.print_soma_info()
|
||
|
|
self._valid_temperatures = (
|
||
|
|
34.0,
|
||
|
|
) # 34 for consistency with other mouse models, but
|
||
|
|
# Spencer data used "33". This affects very slightly
|
||
|
|
# the HCN channel conductance.
|
||
|
|
if self.status["temperature"] is None:
|
||
|
|
self.set_temperature(34.0)
|
||
|
|
self.gBar = Params(
|
||
|
|
nabar=0.0, # 0.0407, # S/cm2
|
||
|
|
nabar_ais=0.42441,
|
||
|
|
kltbar_ais=0.0,
|
||
|
|
khtbar_ais=0.0,
|
||
|
|
ihbar_ais=0.0,
|
||
|
|
kltbar_soma=0.0407,
|
||
|
|
khtbar_soma=0.0061,
|
||
|
|
ihbar_soma=0.0076,
|
||
|
|
kltbar_dend=0.0027,
|
||
|
|
khtbar_dend=0.0,
|
||
|
|
ihbar_dend=0.0006,
|
||
|
|
khtbar_hillock=0.0,
|
||
|
|
kltbar_hillock=0.0,
|
||
|
|
ihbar_hillock=0.0,
|
||
|
|
leakbar=0.0020,
|
||
|
|
)
|
||
|
|
|
||
|
|
self.channelMap = {
|
||
|
|
"soma": {
|
||
|
|
"jsrna": self.gBar.nabar,
|
||
|
|
"klt": self.gBar.kltbar_soma,
|
||
|
|
"kht": self.gBar.khtbar_soma,
|
||
|
|
"hcnobo": self.gBar.ihbar_soma,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"hillock": {
|
||
|
|
"jsrna": 0.0,
|
||
|
|
"klt": self.gBar.kltbar_hillock,
|
||
|
|
"kht": self.gBar.khtbar_hillock,
|
||
|
|
"hcnobo": self.gBar.ihbar_hillock,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
# axon initial segment:
|
||
|
|
"unmyelinatedaxon": {
|
||
|
|
"jsrna": self.gBar.nabar_ais,
|
||
|
|
"klt": self.gBar.kltbar_ais,
|
||
|
|
"kht": self.gBar.khtbar_ais,
|
||
|
|
"hcnobo": self.gBar.ihbar_ais,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"primarydendrite": {
|
||
|
|
"jsrna": 0.0,
|
||
|
|
"klt": self.gBar.kltbar_dend,
|
||
|
|
"kht": self.gBar.khtbar_dend,
|
||
|
|
"hcnobo": self.gBar.ihbar_dend,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
}
|
||
|
|
|
||
|
|
self.distMap = {
|
||
|
|
"primarydendrite": {
|
||
|
|
"klt": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"kht": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"hcnobo": {"gradient": "flat", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
} # all flat with distance
|
||
|
|
}
|
||
|
|
# reversal potential map
|
||
|
|
self.channelErevMap = {
|
||
|
|
"soma": {
|
||
|
|
"jsrna": 55.0,
|
||
|
|
"klt": -70,
|
||
|
|
"kht": -70,
|
||
|
|
"hcnobo": -38,
|
||
|
|
"leak": -62.0,
|
||
|
|
},
|
||
|
|
"hillock": {
|
||
|
|
"jsrna": 55.0,
|
||
|
|
"klt": -70,
|
||
|
|
"kht": -70,
|
||
|
|
"hcnobo": -38,
|
||
|
|
"leak": -62.0,
|
||
|
|
},
|
||
|
|
"unmyelinatedaxon": {
|
||
|
|
"jsrna": 55.0,
|
||
|
|
"klt": -70,
|
||
|
|
"kht": -70,
|
||
|
|
"hcnobo": -38,
|
||
|
|
"leak": -62.0,
|
||
|
|
},
|
||
|
|
"primarydendrite": {
|
||
|
|
"jsrna": 55.0,
|
||
|
|
"klt": -70,
|
||
|
|
"kht": -70,
|
||
|
|
"hcnobo": -38,
|
||
|
|
"leak": -62.0,
|
||
|
|
},
|
||
|
|
}
|
||
|
|
|
||
|
|
else:
|
||
|
|
raise ValueError("model type %s is not implemented" % modelType)
|
||
|
|
self.check_temperature()
|
||
|
|
|
||
|
|
def species_scaling(self, species="mouse", modelType="Spencer", silent=True):
|
||
|
|
"""
|
||
|
|
Adjust all of the conductances and the cell size according to the species requested.
|
||
|
|
Used ONLY for point models.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
species : string (default: 'guineapig')
|
||
|
|
name of the species to use for scaling the conductances in the base point model
|
||
|
|
Must be guineapig
|
||
|
|
|
||
|
|
modelType: string (default: 'II-o')
|
||
|
|
definition of model type from RM03 models, currently limited to type II-o
|
||
|
|
|
||
|
|
silent : boolean (default: True)
|
||
|
|
run silently (True) or verbosely (False)
|
||
|
|
"""
|
||
|
|
soma = self.soma
|
||
|
|
|
||
|
|
if species == "mouse" and modelType == "Spencer":
|
||
|
|
print("Octopus: Mouse, Spencer point model - not a valid model")
|
||
|
|
self.set_soma_size_from_Cm(25.0)
|
||
|
|
self._valid_temperatures = (34.0,)
|
||
|
|
if self.status["temperature"] is None:
|
||
|
|
self.set_temperature(34.0)
|
||
|
|
self.print_soma_info()
|
||
|
|
# self.adjust_na_chans(soma)
|
||
|
|
# soma().kht.gbar = 0.0061 # nstomho(150.0, self.somaarea) # 6.1 mmho/cm2
|
||
|
|
# soma().klt.gbar = 0.0407 # nstomho(3196.0, self.somaarea) # 40.7 mmho/cm2
|
||
|
|
# 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
|
||
|
|
# soma().leak.gbar = 0.0005 # nstomho(2.0, self.somaarea)
|
||
|
|
self.axonsf = 1.0
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
'Species "%s" or species-type "%s" is not recognized for octopus cells'
|
||
|
|
% (species, type)
|
||
|
|
)
|
||
|
|
self.status["species"] = species
|
||
|
|
self.status["modelType"] = modelType
|
||
|
|
self.cell_initialize(showinfo=True)
|
||
|
|
if not silent:
|
||
|
|
print("set cell as: ", species)
|
||
|
|
print(" with Vm rest = %6.3f" % self.vm0)
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