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1090 lines
45 KiB
1090 lines
45 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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import numpy as np
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from .cell import Cell
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# from .. import synapses
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from ..util import nstomho
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from ..util import Params
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from .. import data
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__all__ = ["TStellate", "TStellateRothman", "TStellateNav11"]
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class TStellate(Cell):
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type = "tstellate"
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@classmethod
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def create(cls, model="RM03", **kwds):
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if model == "RM03": # original Rothman-Manis 2003, 22C, point cell, extendable
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return TStellateRothman(**kwds)
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elif model == "Nav11": # Xie-Manis, 2013, 37C, pointe cell, extendable
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return TStellateNav11(**kwds)
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else:
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raise ValueError("TStellate type %s is unknown", type)
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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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Scaling is corrected by initial release probability now.
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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.
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Available options:
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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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# print('cells/tstellaty.py psd type: ', psd_type)
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if psd_type == "simple":
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if terminal.cell.type in ["sgc", "dstellate", "tuberculoventral"]:
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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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# print('cells/tstellaty.py weight: ', weight)
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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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# old values:
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# AMPA_gmax = 0.22479596944138733*1e3 # factor of 1e3 scales to pS (.mod mechanisms) from nS.
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# NMDA_gmax = 0.12281291946623739*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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self.ds_gmax = (
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data.get(
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"dstellate_synapse",
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species=self.species,
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post_type=self.type,
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field="gly_gmax",
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)
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* 1e3
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)
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# print('ds max: ', self.ds_gmax)
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return self.make_gly_psd(
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post_sec, terminal, psdtype="glyfast", loc=loc, gmax=self.ds_gmax
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)
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elif terminal.cell.type == "tuberculoventral":
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self.tv_gmax = (
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data.get(
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"tuberculoventral_synapse",
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species=self.species,
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post_type=self.type,
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field="gly_gmax",
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)
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* 1e3
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)
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return self.make_gly_psd(
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post_sec, terminal, psdtype="glyfast", loc=loc, gmax=self.tv_gmax
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)
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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 TStellateRothman(TStellate):
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"""
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VCN T-stellate base model.
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Rothman and Manis, 2003abc (Type I-c, Type I-t)
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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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temperature=None,
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species="guineapig",
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modelType=None,
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modelName=None,
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debug=False,
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):
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"""
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Initialize a planar stellate (T-stellate) cell, using the default parameters for guinea pig from
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R&M2003, as a type I cell.
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Modifications to the cell can be made by calling methods below. These include:
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Converting to a type IA model (add transient K current) (species: guineapig-TypeIA).
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Changing "species" to mouse or cat (scales conductances)
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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. The default is 'nacn', from R&M2003.
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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., "I-c", "I-t").
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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(TStellateRothman, self).__init__()
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self.i_test_range = {"pulse": (-0.15, 0.15, 0.01)}
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if modelType is None:
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modelType = "I-c"
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if species == "guineapig":
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modelName = "RM03"
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temp = 22.0
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if nach == None:
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nach = "nacn"
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if species == "mouse":
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temp = 34.0
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if modelName is None:
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modelName = "XM13"
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if nach == None:
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nach = "nacn"
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self.i_test_range = {"pulse": (-1.0, 1.0, 0.05)}
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self.debug = debug
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self.status = {
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"species": species,
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"cellClass": self.type,
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"modelType": modelType,
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"modelName": modelName,
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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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"ttx": ttx,
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"name": self.type,
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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.c_m = 0.9e-6 # default in units of F/cm^2
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self.spike_threshold = (
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-40.0
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) # matches threshold in released CNModel (set in base cell class)
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self.vrange = [-70.0, -55.0]
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self._valid_temperatures = (temp,)
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if self.status["temperature"] == None:
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self.status["temperature"] = temp
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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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if self.debug:
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print(
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"<< TStellate model: Creating point cell, type={:s} >>".format(
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modelType
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)
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)
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soma = h.Section(
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name="TStellate_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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if self.debug:
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print("<< TStellate: Creating cell with morphology = %s>>" % morphology)
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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.mechanisms = ["kht", "ka", "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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self.soma().ihvcn.eh = self.e_h
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self.soma().leak.erev = self.e_leak
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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 self.debug:
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print("<< T-stellate: JSR Stellate Type 1 cell model created >>")
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def get_cellpars(self, dataset, species="guineapig", modelType="I-c"):
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cellcap = data.get(
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dataset, species=species, model_type=modelType, field="soma_Cap"
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)
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chtype = data.get(
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dataset, species=species, model_type=modelType, field="na_type"
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)
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pars = Params(cap=cellcap, natype=chtype)
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# pars.show()
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if self.status["modelName"] == "RM03":
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for g in [
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"%s_gbar" % pars.natype,
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"kht_gbar",
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"ka_gbar",
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"ih_gbar",
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"leak_gbar",
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"leak_erev",
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"ih_eh",
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"e_k",
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"e_na",
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]:
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pars.additem(
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g, data.get(dataset, species=species, model_type=modelType, field=g)
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)
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if self.status["modelName"] == "XM13":
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for g in [
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"%s_gbar" % pars.natype,
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"kht_gbar",
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"ka_gbar",
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"ihvcn_gbar",
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"leak_gbar",
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"leak_erev",
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"ih_eh",
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"e_k",
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"e_na",
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]:
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pars.additem(
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||
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g, data.get(dataset, species=species, model_type=modelType, field=g)
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||
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)
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||
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if self.status["modelName"] == "mGBC":
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for g in [
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|
|
"%s_gbar" % pars.natype,
|
||
|
|
"kht_gbar",
|
||
|
|
"ka_gbar",
|
||
|
|
"ihvcn_gbar",
|
||
|
|
"leak_gbar",
|
||
|
|
"leak_erev",
|
||
|
|
"ih_eh",
|
||
|
|
"e_k",
|
||
|
|
"e_na",
|
||
|
|
]:
|
||
|
|
pars.additem(
|
||
|
|
g, data.get(dataset, species=species, model_type=modelType, field=g)
|
||
|
|
)
|
||
|
|
return pars
|
||
|
|
|
||
|
|
def species_scaling(self, species="guineapig", modelType="I-c", silent=True):
|
||
|
|
"""
|
||
|
|
Adjust all of the conductances and the cell size according to the species requested.
|
||
|
|
Used ONLY for point models.
|
||
|
|
|
||
|
|
This scaling routine also sets the temperature for the model to a default value. Some models
|
||
|
|
can be run at multiple temperatures, and so a default from one of the temperatures is used.
|
||
|
|
The calling cell.set_temperature(newtemp) will change the conductances and reinitialize
|
||
|
|
the cell to the new temperature settings.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
species : string (default: 'guineapig')
|
||
|
|
name of the species to use for scaling the conductances in the base point model
|
||
|
|
Must be one of mouse, cat, guineapig
|
||
|
|
|
||
|
|
modelType: string (default: 'I-c')
|
||
|
|
definition of model type from RM03 models, type I-c or type I-t
|
||
|
|
|
||
|
|
silent : boolean (default: True)
|
||
|
|
run silently (True) or verbosely (False)
|
||
|
|
"""
|
||
|
|
soma = self.soma
|
||
|
|
if modelType == "I-c":
|
||
|
|
celltype = "tstellate"
|
||
|
|
elif modelType == "I-t":
|
||
|
|
celltype = "tstellate-t"
|
||
|
|
else:
|
||
|
|
raise ValueError("model type not recognized")
|
||
|
|
|
||
|
|
if species == "mouse": # and modelType == 'I-c':
|
||
|
|
# use conductance levels from Cao et al., J. Neurophys., 2007.
|
||
|
|
# model description in Xie and Manis 2013. Note that
|
||
|
|
# conductances were not scaled for temperature (rates were)
|
||
|
|
# so here we reset the default Q10's for conductance (g) to 1.0
|
||
|
|
if self.debug:
|
||
|
|
print(
|
||
|
|
" Setting Conductances for mouse I-c Tstellate cell, (modified from Xie and Manis, 2013)"
|
||
|
|
)
|
||
|
|
self.c_m = 0.9 # default in units of F/cm^2
|
||
|
|
dataset = "XM13_channels"
|
||
|
|
self.vrange = [-75.0, -55.0]
|
||
|
|
self.set_soma_size_from_Cm(25.0)
|
||
|
|
self._valid_temperatures = (34.0,)
|
||
|
|
if self.status["temperature"] is None:
|
||
|
|
self.set_temperature(34.0)
|
||
|
|
|
||
|
|
pars = self.get_cellpars(dataset, species=species, modelType=modelType)
|
||
|
|
# pars.show()
|
||
|
|
self.set_soma_size_from_Cm(pars.cap)
|
||
|
|
self.status["na"] = pars.natype
|
||
|
|
self.adjust_na_chans(soma, gbar=pars.nacn_gbar, sf=1.0)
|
||
|
|
soma().kht.gbar = nstomho(pars.kht_gbar, self.somaarea)
|
||
|
|
soma().ka.gbar = nstomho(pars.ka_gbar, self.somaarea)
|
||
|
|
soma().ihvcn.gbar = nstomho(pars.ihvcn_gbar, self.somaarea)
|
||
|
|
soma().ihvcn.eh = pars.ih_eh # Rodrigues and Oertel, 2006
|
||
|
|
soma().leak.gbar = nstomho(pars.leak_gbar, self.somaarea)
|
||
|
|
soma().leak.erev = pars.leak_erev
|
||
|
|
self.e_k = pars.e_k
|
||
|
|
self.e_na = pars.e_na
|
||
|
|
soma.ena = self.e_na
|
||
|
|
soma.ek = self.e_k
|
||
|
|
self.axonsf = 0.5
|
||
|
|
|
||
|
|
elif species == "guineapig":
|
||
|
|
# and modelType == 'I-c': # values from R&M 2003, Type I
|
||
|
|
if self.debug:
|
||
|
|
print(
|
||
|
|
" Setting Conductances for Guinea Pig I-c, Rothman and Manis, 2003"
|
||
|
|
)
|
||
|
|
dataset = "RM03_channels"
|
||
|
|
self.c_m = 0.9 # default in units of F/cm^2
|
||
|
|
self.vrange = [-75.0, -55.0]
|
||
|
|
self._valid_temperatures = (22.0, 38.0)
|
||
|
|
if self.status["temperature"] is None:
|
||
|
|
self.set_temperature(22.0)
|
||
|
|
sf = 1.0
|
||
|
|
if (
|
||
|
|
self.status["temperature"] == 38.0
|
||
|
|
): # adjust for 2003 model conductance levels at 38
|
||
|
|
sf = 3.03 # Q10 of 2, 22->38C. (p3106, R&M2003c)
|
||
|
|
# note that kinetics are scaled in the mod file.
|
||
|
|
pars = self.get_cellpars(dataset, species=species, modelType=modelType)
|
||
|
|
self.set_soma_size_from_Cm(pars.cap)
|
||
|
|
self.status["na"] = pars.natype
|
||
|
|
# pars.show()
|
||
|
|
self.adjust_na_chans(soma, gbar=pars.nacn_gbar, sf=sf)
|
||
|
|
soma().kht.gbar = nstomho(pars.kht_gbar, self.somaarea)
|
||
|
|
soma().ka.gbar = nstomho(pars.ka_gbar, self.somaarea)
|
||
|
|
soma().ihvcn.gbar = nstomho(pars.ih_gbar, self.somaarea)
|
||
|
|
soma().leak.gbar = nstomho(pars.leak_gbar, self.somaarea)
|
||
|
|
soma().leak.erev = pars.leak_erev
|
||
|
|
self.axonsf = 0.5
|
||
|
|
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
"Species %s or species-type %s is not recognized for T-stellate cells"
|
||
|
|
% (species, type)
|
||
|
|
)
|
||
|
|
|
||
|
|
self.status["species"] = species
|
||
|
|
self.status["modelType"] = modelType
|
||
|
|
self.check_temperature()
|
||
|
|
|
||
|
|
# def channel_manager(self, modelType='RM03'):
|
||
|
|
# """
|
||
|
|
# 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, called from it's private
|
||
|
|
# _biophys function) to decorate the cell membrane with channels.
|
||
|
|
#
|
||
|
|
# Parameters
|
||
|
|
# ----------
|
||
|
|
# modelType : string (default: 'RM03')
|
||
|
|
# A string that defines the type of the model. Currently, 3 types are implemented:
|
||
|
|
# RM03: Rothman and Manis, 2003 somatic densities for guinea pig
|
||
|
|
# XM13: Xie and Manis, 2013, somatic densities for mouse
|
||
|
|
# XM13PasDend: XM13, but with only passive dendrites, no channels.
|
||
|
|
#
|
||
|
|
# 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.
|
||
|
|
#
|
||
|
|
# """
|
||
|
|
# if modelType == 'RM03':
|
||
|
|
# totcap = 12.0E-12 # TStellate cell (type I) from Rothman and Manis, 2003, as base model
|
||
|
|
# refarea = totcap / self.c_m # see above for units
|
||
|
|
# # Type I stellate Rothman and Manis, 2003c
|
||
|
|
# self._valid_temperatures = (22., 38.)
|
||
|
|
# if self.status['temperature'] is None:
|
||
|
|
# self.set_temperature(22.)
|
||
|
|
# sf = 1.0
|
||
|
|
# if self.status['temperature'] == 38.: # adjust for 2003 model conductance levels at 38
|
||
|
|
# sf = 3.03 # Q10 of 2, 22->38C. (p3106, R&M2003c)
|
||
|
|
# self.gBar = Params(nabar=sf*1000.0E-9/refarea,
|
||
|
|
# khtbar=sf*150.0E-9/refarea,
|
||
|
|
# kltbar=sf*0.0E-9/refarea,
|
||
|
|
# ihbar=sf*0.5E-9/refarea,
|
||
|
|
# leakbar=sf*2.0E-9/refarea,
|
||
|
|
# )
|
||
|
|
#
|
||
|
|
# self.channelMap = {
|
||
|
|
# 'axon': {'nacn': 0.0, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': 0., 'leak': self.gBar.leakbar / 4.},
|
||
|
|
# 'hillock': {'nacn': self.gBar.nabar, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': 0., 'leak': self.gBar.leakbar, },
|
||
|
|
# 'initseg': {'nacn': self.gBar.nabar, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 2.,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'soma': {'nacn': self.gBar.nabar, 'klt': self.gBar.kltbar,
|
||
|
|
# 'kht': self.gBar.khtbar, 'ihvcn': self.gBar.ihbar,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'dend': {'nacn': self.gBar.nabar / 2.0, 'klt': 0., 'kht': self.gBar.khtbar * 0.5,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 3., 'leak': self.gBar.leakbar * 0.5, },
|
||
|
|
# 'apic': {'nacn': 0.0, 'klt': 0., 'kht': self.gBar.khtbar * 0.2,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 4.,
|
||
|
|
# 'leak': self.gBar.leakbar * 0.2, },
|
||
|
|
# }
|
||
|
|
# self.irange = np.linspace(-0.1, 0.1, 7)
|
||
|
|
# self.distMap = {'dend': {'klt': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'kht': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.}}, # linear with distance, gminf (factor) is multiplied by gbar
|
||
|
|
# 'apic': {'klt': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'kht': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.}}, # gradients are: flat, linear, exponential
|
||
|
|
# }
|
||
|
|
#
|
||
|
|
# elif modelType == 'XM13':
|
||
|
|
# totcap = 25.0E-12 # Base model from Xie and Manis, 2013 for type I stellate cell
|
||
|
|
# refarea = totcap / self.c_m # see above for units
|
||
|
|
# self._valid_temperatures = (34.,)
|
||
|
|
# if self.status['temperature'] is None:
|
||
|
|
# self.set_temperature(34.)
|
||
|
|
# self.gBar = Params(nabar=1800.0E-9/refarea,
|
||
|
|
# khtbar=250.0E-9/refarea,
|
||
|
|
# kltbar=0.0E-9/refarea,
|
||
|
|
# ihbar=18.0E-9/refarea,
|
||
|
|
# leakbar=8.0E-9/refarea,
|
||
|
|
# )
|
||
|
|
# self.channelMap = {
|
||
|
|
# 'axon': {'nav11': 0.0, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': 0., 'leak': self.gBar.leakbar / 4.},
|
||
|
|
# 'hillock': {'nav11': self.gBar.nabar, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': 0.,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'initseg': {'nav11': self.gBar.nabar, 'klt': 0., 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 2.,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'soma': {'nav11': self.gBar.nabar, 'klt': self.gBar.kltbar,
|
||
|
|
# 'kht': self.gBar.khtbar, 'ihvcn': self.gBar.ihbar,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'dend': {'nav11': self.gBar.nabar, 'klt': 0., 'kht': self.gBar.khtbar * 0.5,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 3., 'leak': self.gBar.leakbar * 0.5, },
|
||
|
|
# 'apic': {'nav11': 0.0, 'klt': 0., 'kht': self.gBar.khtbar * 0.2,
|
||
|
|
# 'ihvcn': self.gBar.ihbar / 4.,
|
||
|
|
# 'leak': self.gBar.leakbar * 0.2, },
|
||
|
|
# }
|
||
|
|
# self.irange = np.linspace(-0.5, 0.5, 9)
|
||
|
|
# self.distMap = {'dend': {'klt': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'kht': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'nav11': {'gradient': 'exp', 'gminf': 0., 'lambda': 100.}}, # linear with distance, gminf (factor) is multiplied by gbar
|
||
|
|
# 'apic': {'klt': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'kht': {'gradient': 'linear', 'gminf': 0., 'lambda': 100.},
|
||
|
|
# 'nav11': {'gradient': 'exp', 'gminf': 0., 'lambda': 100.}}, # gradients are: flat, linear, exponential
|
||
|
|
# }
|
||
|
|
#
|
||
|
|
# elif modelType == 'XM13PasDend':
|
||
|
|
# # bushy form Xie and Manis, 2013, based on Cao and Oertel mouse conductances
|
||
|
|
# # passive dendritestotcap = 26.0E-12 # uF/cm2
|
||
|
|
# totcap = 26.0E-12 # uF/cm2
|
||
|
|
# refarea = totcap / self.c_m # see above for units
|
||
|
|
# self._valid_temperatures = (34.,)
|
||
|
|
# if self.status['temperature'] is None:
|
||
|
|
# self.set_temperature(34.)
|
||
|
|
# self.gBar = Params(nabar=1000.0E-9/refarea,
|
||
|
|
# khtbar=150.0E-9/refarea,
|
||
|
|
# kltbar=0.0E-9/refarea,
|
||
|
|
# ihbar=0.5E-9/refarea,
|
||
|
|
# leakbar=2.0E-9/refarea,
|
||
|
|
# )
|
||
|
|
# self.channelMap = {
|
||
|
|
# 'axon': {'nav11': self.gBar.nabar*0, 'klt': self.gBar.kltbar * 0.25, 'kht': self.gBar.khtbar, 'ihvcn': 0.,
|
||
|
|
# 'leak': self.gBar.leakbar * 0.25},
|
||
|
|
# 'hillock': {'nav11': self.gBar.nabar, 'klt': self.gBar.kltbar, 'kht': self.gBar.khtbar, 'ihvcn': 0.,
|
||
|
|
# 'leak': self.gBar.leakbar, },
|
||
|
|
# 'initseg': {'nav11': self.gBar.nabar*3, 'klt': self.gBar.kltbar*2, 'kht': self.gBar.khtbar*2,
|
||
|
|
# 'ihvcn': self.gBar.ihbar * 0.5, 'leak': self.gBar.leakbar, },
|
||
|
|
# 'soma': {'nav11': self.gBar.nabar, 'klt': self.gBar.kltbar, 'kht': self.gBar.khtbar,
|
||
|
|
# 'ihvcn': self.gBar.ihbar, 'leak': self.gBar.leakbar, },
|
||
|
|
# 'dend': {'nav11': self.gBar.nabar * 0.0, 'klt': self.gBar.kltbar*0 , 'kht': self.gBar.khtbar*0,
|
||
|
|
# 'ihvcn': self.gBar.ihbar*0, 'leak': self.gBar.leakbar*0.5, },
|
||
|
|
# 'apic': {'nav11': self.gBar.nabar * 0.0, 'klt': self.gBar.kltbar * 0, 'kht': self.gBar.khtbar * 0.,
|
||
|
|
# 'ihvcn': self.gBar.ihbar *0., 'leak': self.gBar.leakbar * 0.25, },
|
||
|
|
# }
|
||
|
|
# self.irange = np.linspace(-1, 1, 21)
|
||
|
|
def get_distancemap(self):
|
||
|
|
return {
|
||
|
|
"dend": {
|
||
|
|
"klt": {"gradient": "linear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
"kht": {"gradient": "llinear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
"nav11": {"gradient": "linear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
}, # linear with distance, gminf (factor) is multiplied by gbar
|
||
|
|
"apic": {
|
||
|
|
"klt": {"gradient": "linear", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"kht": {"gradient": "linear", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"nav11": {"gradient": "exp", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
}, # gradients are: flat, linear, exponential
|
||
|
|
}
|
||
|
|
# else:
|
||
|
|
# raise ValueError('model type %s is not implemented' % modelType)
|
||
|
|
# self.check_temperature()
|
||
|
|
|
||
|
|
def adjust_na_chans(self, soma, sf=1.0, gbar=1000.0):
|
||
|
|
"""
|
||
|
|
Adjust the sodium channel conductance, depending on the type of conductance
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
soma : NEURON section object (required)
|
||
|
|
This identifies the soma object whose sodium channel complement will have it's
|
||
|
|
conductances adjusted depending on the sodium channel type
|
||
|
|
gbar : float (default: 1000.)
|
||
|
|
The "maximal" conductance to be set in the model.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Nothing
|
||
|
|
"""
|
||
|
|
if self.status["ttx"]:
|
||
|
|
gnabar = 0.0
|
||
|
|
else:
|
||
|
|
gnabar = nstomho(gbar, self.somaarea) * sf
|
||
|
|
nach = self.status["na"]
|
||
|
|
if nach == "jsrna":
|
||
|
|
soma().jsrna.gbar = gnabar * sf
|
||
|
|
soma.ena = self.e_na
|
||
|
|
if self.debug:
|
||
|
|
print("jsrna gbar: ", soma().jsrna.gbar)
|
||
|
|
elif nach == "nav11":
|
||
|
|
soma().nav11.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
soma().nav11.vsna = 4.3
|
||
|
|
if self.debug:
|
||
|
|
print("tstellate using inva11")
|
||
|
|
print("nav11 gbar: ", soma().nav11.gbar)
|
||
|
|
print("nav11 vsna: ", soma().nav11.vsna)
|
||
|
|
elif nach == "na":
|
||
|
|
soma().nacn.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
if self.debug:
|
||
|
|
print("na gbar: ", soma().na.gbar)
|
||
|
|
elif nach == "nacn":
|
||
|
|
soma().nacn.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
if self.debug:
|
||
|
|
print("nacn gbar: ", soma().nacn.gbar)
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
"tstellate setting Na channels: channel %s not known" % nach
|
||
|
|
)
|
||
|
|
|
||
|
|
def add_axon(self):
|
||
|
|
Cell.add_axon(self, self.soma, self.somaarea, self.c_m, self.R_a, self.axonsf)
|
||
|
|
|
||
|
|
def add_dendrites(self):
|
||
|
|
"""
|
||
|
|
Add simple unbranched dendrites to basic Rothman Type I models.
|
||
|
|
The dendrites have some kht and ih current
|
||
|
|
"""
|
||
|
|
cs = False # not implemented outside here - internal Cesium.
|
||
|
|
nDend = range(4) # these will be simple, unbranced, N=4 dendrites
|
||
|
|
dendrites = []
|
||
|
|
for i in nDend:
|
||
|
|
dendrites.append(h.Section(cell=self.soma))
|
||
|
|
for i in nDend:
|
||
|
|
dendrites[i].connect(self.soma)
|
||
|
|
dendrites[i].L = 200 # length of the dendrite (not tapered)
|
||
|
|
dendrites[i].diam = 1.5 # dendrite diameter
|
||
|
|
dendrites[i].nseg = 21 # # segments in dendrites
|
||
|
|
dendrites[i].Ra = 150 # ohm.cm
|
||
|
|
dendrites[i].insert("kht")
|
||
|
|
if cs is False:
|
||
|
|
dendrites[i]().kht.gbar = 0.005 # a little Ht
|
||
|
|
else:
|
||
|
|
dendrites[i]().kht.gbar = 0.0
|
||
|
|
dendrites[i].insert("leak") # leak
|
||
|
|
dendrites[i]().leak.gbar = 0.0001
|
||
|
|
dendrites[i].insert("ihvcn") # some H current
|
||
|
|
dendrites[i]().ihvcn.gbar = 0.0 # 0.001
|
||
|
|
dendrites[i]().ihvcn.eh = -43.0
|
||
|
|
self.maindend = dendrites
|
||
|
|
self.status["dendrites"] = True
|
||
|
|
self.add_section(self.maindend, "maindend")
|
||
|
|
|
||
|
|
|
||
|
|
class TStellateNav11(TStellate):
|
||
|
|
"""
|
||
|
|
VCN T-stellate cell (Mouse) from Xie and Manis, 2013.
|
||
|
|
Using nav11 sodium channel model.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(
|
||
|
|
self,
|
||
|
|
morphology=None,
|
||
|
|
decorator=None,
|
||
|
|
nach="nav11",
|
||
|
|
ttx=False,
|
||
|
|
species="mouse",
|
||
|
|
modelType=None,
|
||
|
|
debug=False,
|
||
|
|
):
|
||
|
|
"""
|
||
|
|
Initialize a planar stellate (T-stellate) cell as a point model, using the default parameters for
|
||
|
|
mouse from Xie and Manis, 2013.
|
||
|
|
Modifications to the cell can be made by calling methods below.
|
||
|
|
Changing "species": This routine only supports "mouse"
|
||
|
|
*Note:* in the original model, the temperature scaling applied only to the rate constants, and not
|
||
|
|
to the conductance. Therefore, the conductances here need to be adjusted to compensate for the
|
||
|
|
way the mechanisms are currently implemented (so that they scale correctly to the values
|
||
|
|
used in Xie and Manis, 2013). This is done by setting q10g (the q10 for conductances) to 1
|
||
|
|
before setting up the rest of the model parameters. For those conducantances in which a Q10 for
|
||
|
|
conductance is implemented, the value is typically 2.
|
||
|
|
|
||
|
|
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: 'nav11')
|
||
|
|
nach selects the type of sodium channel that will be used in the model. A channel mechanims
|
||
|
|
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 'mouse')
|
||
|
|
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(TStellateNav11, self).__init__()
|
||
|
|
if modelType == None:
|
||
|
|
modelType = "XM13"
|
||
|
|
self.status = {
|
||
|
|
"soma": True,
|
||
|
|
"axon": False,
|
||
|
|
"dendrites": False,
|
||
|
|
"pumps": False,
|
||
|
|
"na": nach,
|
||
|
|
"species": species,
|
||
|
|
"modelType": modelType,
|
||
|
|
"ttx": ttx,
|
||
|
|
"name": "TStellate",
|
||
|
|
"morphology": morphology,
|
||
|
|
"decorator": decorator,
|
||
|
|
}
|
||
|
|
|
||
|
|
self.i_test_range = (-1, 1.0, 0.05)
|
||
|
|
|
||
|
|
if morphology is None:
|
||
|
|
"""
|
||
|
|
instantiate a basic soma-only ("point") model
|
||
|
|
"""
|
||
|
|
print(
|
||
|
|
"<< TStellate Xie&Manis 2013 model: Creating point cell, type={:s} >>".format(
|
||
|
|
modelType
|
||
|
|
)
|
||
|
|
)
|
||
|
|
soma = h.Section(
|
||
|
|
name="TStellate_Soma_%x" % id(self)
|
||
|
|
) # one compartment of about 29000 um2
|
||
|
|
soma.nseg = 1
|
||
|
|
self.add_section(soma, "soma")
|
||
|
|
else:
|
||
|
|
"""
|
||
|
|
instantiate a structured model with the morphology as specified by
|
||
|
|
the morphology file
|
||
|
|
"""
|
||
|
|
print("<< TStellate Xie&Manis 2013 model: Creating structured cell >>")
|
||
|
|
self.set_morphology(morphology_file=morphology)
|
||
|
|
|
||
|
|
# decorate the morphology with ion channels
|
||
|
|
if decorator is None: # basic model, only on the soma
|
||
|
|
self.mechanisms = ["kht", "ka", "ihvcn", "leak", nach]
|
||
|
|
for mech in self.mechanisms:
|
||
|
|
self.soma.insert(mech)
|
||
|
|
self.soma.ek = self.e_k
|
||
|
|
self.soma.ena = self.e_na
|
||
|
|
self.soma().ihvcn.eh = self.e_h
|
||
|
|
self.soma().leak.erev = self.e_leak
|
||
|
|
self.soma().cm = 1.0
|
||
|
|
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.get_mechs(self.soma)
|
||
|
|
self.cell_initialize(vrange=self.vrange)
|
||
|
|
# self.print_mechs(self.soma)
|
||
|
|
if self.debug:
|
||
|
|
print("<< T-stellate: Xie&Manis 2013 cell model created >>")
|
||
|
|
|
||
|
|
def species_scaling(self, species="mouse", modelType="I-c", 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 one of mouse, cat, guineapig
|
||
|
|
|
||
|
|
modelType: string (default: 'I-c')
|
||
|
|
definition of model type from RM03 models, type I-c or type I-t
|
||
|
|
|
||
|
|
silent : boolean (default: True)
|
||
|
|
run silently (True) or verbosely (False)
|
||
|
|
"""
|
||
|
|
soma = self.soma
|
||
|
|
if species == "mouse" and modelType == "XM13":
|
||
|
|
# use conductance levels from Cao et al., J. Neurophys., 2007.
|
||
|
|
# original temp for model: 32 C
|
||
|
|
print("Mouse Tstellate cell, Xie and Manis, 2013")
|
||
|
|
self.set_soma_size_from_Cm(25.0)
|
||
|
|
self.adjust_na_chans(soma, gbar=800.0) # inav11 does not scale conductance
|
||
|
|
self.e_k = -84.0
|
||
|
|
self.e_na = 50.0
|
||
|
|
soma.ek = self.e_k
|
||
|
|
soma.ena = self.e_na
|
||
|
|
soma().kht.gbar = nstomho(250.0, self.somaarea)
|
||
|
|
soma().ka.gbar = nstomho(0.0, self.somaarea)
|
||
|
|
soma().ihvcn.gbar = nstomho(18.0, self.somaarea)
|
||
|
|
soma().ihvcn.eh = -43 # Rodrigues and Oertel, 2006
|
||
|
|
soma().leak.gbar = nstomho(8.0, self.somaarea)
|
||
|
|
soma().leak.erev = -65.0
|
||
|
|
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
"Species %s or species-type %s is not recognized for T-stellate XM13 cells"
|
||
|
|
% (species, type)
|
||
|
|
)
|
||
|
|
|
||
|
|
self.status["species"] = species
|
||
|
|
self.status["modelType"] = modelType
|
||
|
|
# self.cell_initialize(showinfo=False)
|
||
|
|
# if not silent:
|
||
|
|
# print 'set cell as: ', species
|
||
|
|
# print ' with Vm rest = %f' % self.vm0
|
||
|
|
|
||
|
|
def channel_manager(self, modelType="XM13"):
|
||
|
|
"""
|
||
|
|
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, called from it's private
|
||
|
|
_biophys function) to decorate the cell membrane with channels.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
modelType : string (default: 'XM13')
|
||
|
|
A string that defines the type of the model. Currently, 3 types are implemented:
|
||
|
|
XM13: Xie and Manis, 2013, somatic densities for mouse
|
||
|
|
XM13PasDend: XM13, but with only passive dendrites, no channels.
|
||
|
|
|
||
|
|
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.
|
||
|
|
|
||
|
|
"""
|
||
|
|
if modelType == "XM13":
|
||
|
|
totcap = (
|
||
|
|
25.0e-12
|
||
|
|
) # Base model from Xie and Manis, 2013 for type I stellate cell
|
||
|
|
refarea = totcap / self.c_m # see above for units
|
||
|
|
self.gBar = Params(
|
||
|
|
nabar=800.0e-9 / refarea,
|
||
|
|
khtbar=250.0e-9 / refarea,
|
||
|
|
kltbar=0.0e-9 / refarea,
|
||
|
|
ihbar=18.0e-9 / refarea,
|
||
|
|
leakbar=8.0e-9 / refarea,
|
||
|
|
)
|
||
|
|
self.channelMap = {
|
||
|
|
"axon": {
|
||
|
|
"nav11": 0.0,
|
||
|
|
"klt": 0.0,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": 0.0,
|
||
|
|
"leak": self.gBar.leakbar / 4.0,
|
||
|
|
},
|
||
|
|
"hillock": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": 0.0,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": 0.0,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"initseg": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": 0.0,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": self.gBar.ihbar / 2.0,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"soma": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": self.gBar.kltbar,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": self.gBar.ihbar,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"dend": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": 0.0,
|
||
|
|
"kht": self.gBar.khtbar * 0.5,
|
||
|
|
"ihvcn": self.gBar.ihbar / 3.0,
|
||
|
|
"leak": self.gBar.leakbar * 0.5,
|
||
|
|
},
|
||
|
|
}
|
||
|
|
self.irange = np.linspace(-1.0, 1.0, 21)
|
||
|
|
self.distMap = {
|
||
|
|
"dend": {
|
||
|
|
"klt": {"gradient": "linear", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"kht": {"gradient": "linear", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
"nav11": {"gradient": "exp", "gminf": 0.0, "lambda": 100.0},
|
||
|
|
} # linear with distance, gminf (factor) is multiplied by gbar
|
||
|
|
}
|
||
|
|
|
||
|
|
elif modelType == "XM13PasDend":
|
||
|
|
# bushy form Xie and Manis, 2013, based on Cao and Oertel mouse conductances
|
||
|
|
# passive dendrites
|
||
|
|
totcap = 26.0e-12 # uF/cm2
|
||
|
|
refarea = totcap / self.c_m # see above for units
|
||
|
|
self.gBar = Params(
|
||
|
|
nabar=1000.0e-9 / refarea,
|
||
|
|
khtbar=150.0e-9 / refarea,
|
||
|
|
kltbar=0.0e-9 / refarea,
|
||
|
|
ihbar=0.5e-9 / refarea,
|
||
|
|
leakbar=2.0e-9 / refarea,
|
||
|
|
)
|
||
|
|
self.channelMap = {
|
||
|
|
"axon": {
|
||
|
|
"nav11": self.gBar.nabar * 0,
|
||
|
|
"klt": self.gBar.kltbar * 0.25,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": 0.0,
|
||
|
|
"leak": self.gBar.leakbar * 0.25,
|
||
|
|
},
|
||
|
|
"hillock": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": self.gBar.kltbar,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": 0.0,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"initseg": {
|
||
|
|
"nav11": self.gBar.nabar * 3,
|
||
|
|
"klt": self.gBar.kltbar * 2,
|
||
|
|
"kht": self.gBar.khtbar * 2,
|
||
|
|
"ihvcn": self.gBar.ihbar * 0.5,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"soma": {
|
||
|
|
"nav11": self.gBar.nabar,
|
||
|
|
"klt": self.gBar.kltbar,
|
||
|
|
"kht": self.gBar.khtbar,
|
||
|
|
"ihvcn": self.gBar.ihbar,
|
||
|
|
"leak": self.gBar.leakbar,
|
||
|
|
},
|
||
|
|
"dend": {
|
||
|
|
"nav11": self.gBar.nabar * 0.0,
|
||
|
|
"klt": self.gBar.kltbar * 0,
|
||
|
|
"kht": self.gBar.khtbar * 0,
|
||
|
|
"ihvcn": self.gBar.ihbar * 0,
|
||
|
|
"leak": self.gBar.leakbar * 0.5,
|
||
|
|
},
|
||
|
|
}
|
||
|
|
self.irange = np.linspace(-1, 1, 21)
|
||
|
|
self.distMap = {
|
||
|
|
"dend": {
|
||
|
|
"klt": {"gradient": "linear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
"kht": {"gradient": "llinear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
"nav11": {"gradient": "linear", "gminf": 0.0, "lambda": 200.0},
|
||
|
|
} # linear with distance, gminf (factor) is multiplied by gbar
|
||
|
|
}
|
||
|
|
else:
|
||
|
|
raise ValueError("model type %s is not implemented" % modelType)
|
||
|
|
|
||
|
|
def adjust_na_chans(self, soma, gbar=800.0):
|
||
|
|
"""
|
||
|
|
Adjust the sodium channel conductance, depending on the type of conductance
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
soma : NEURON section object (required)
|
||
|
|
This identifies the soma object whose sodium channel complement will have it's
|
||
|
|
conductances adjusted depending on the sodium channel type
|
||
|
|
gbar : float (default: 800.)
|
||
|
|
The "maximal" conductance to be set in the model.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
Nothing
|
||
|
|
"""
|
||
|
|
if self.status["ttx"]:
|
||
|
|
gnabar = 0.0
|
||
|
|
else:
|
||
|
|
gnabar = nstomho(gbar, self.somaarea)
|
||
|
|
nach = self.status["na"]
|
||
|
|
if nach == "nav11":
|
||
|
|
soma().nav11.gbar = gnabar
|
||
|
|
soma.ena = self.e_na
|
||
|
|
soma().nav11.vsna = 4.3
|
||
|
|
if self.debug:
|
||
|
|
print("tstellate using inva11")
|
||
|
|
else:
|
||
|
|
raise ValueError(
|
||
|
|
"tstellate setting Na channels only supporting nav11: channel %s not known"
|
||
|
|
% nach
|
||
|
|
)
|