NeuroML core classes¶
nml Module¶
Note: This module is included in the top level of the neuroml package, so you can use these classes by importing neuroml:
from neuroml import AdExIaFCell
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class
neuroml.nml.nml.AdExIaFCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, C=None, g_l=None, EL=None, reset=None, VT=None, thresh=None, del_t=None, tauw=None, refract=None, a=None, b=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCellMembPotCap-
superclass¶ alias of
BaseCellMembPotCap
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class
neuroml.nml.nml.AlphaCondSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, e_rev=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BasePynnSynapse-
superclass¶ alias of
BasePynnSynapse
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class
neuroml.nml.nml.AlphaCurrSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BasePynnSynapse-
superclass¶ alias of
BasePynnSynapse
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class
neuroml.nml.nml.AlphaCurrentSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau=None, ibase=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCurrentBasedSynapse-
superclass¶ alias of
BaseCurrentBasedSynapse
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class
neuroml.nml.nml.AlphaSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase=None, erev=None, tau=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConductanceBasedSynapse-
superclass¶ alias of
BaseConductanceBasedSynapse
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class
neuroml.nml.nml.Annotation(anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperPlaceholder for MIRIAM related metadata, among others.
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class
neuroml.nml.nml.Base(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseWithoutIdAnything which can have a unique (within its parent) id of the form NmlId (spaceless combination of letters, numbers and underscore).
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superclass¶ alias of
BaseWithoutId
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class
neuroml.nml.nml.BaseCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.BaseCellMembPotCap(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, C=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCellThis is to prevent it conflicting with attribute c (lowercase) e.g. in izhikevichCell2007
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class
neuroml.nml.nml.BaseConductanceBasedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase=None, erev=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseVoltageDepSynapse-
superclass¶ alias of
BaseVoltageDepSynapse
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class
neuroml.nml.nml.BaseConductanceBasedSynapseTwo(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase1=None, gbase2=None, erev=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseVoltageDepSynapse-
superclass¶ alias of
BaseVoltageDepSynapse
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class
neuroml.nml.nml.BaseConnection(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseNonNegativeIntegerIdBase of all synaptic connections (chemical/electrical/analog, etc.) inside projections
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superclass¶ alias of
BaseNonNegativeIntegerId
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class
neuroml.nml.nml.BaseConnectionNewFormat(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionBase of all synaptic connections with preCell, postSegment, etc. See BaseConnectionOldFormat
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superclass¶ alias of
BaseConnection
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class
neuroml.nml.nml.BaseConnectionOldFormat(neuro_lex_id=None, id=None, pre_cell_id=None, pre_segment_id='0', pre_fraction_along='0.5', post_cell_id=None, post_segment_id='0', post_fraction_along='0.5', extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionBase of all synaptic connections with preCellId, postSegmentId, etc. Note: this is not the best name for these attributes, since Id is superfluous, hence BaseConnectionNewFormat
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superclass¶ alias of
BaseConnection
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class
neuroml.nml.nml.BaseCurrentBasedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapse-
superclass¶ alias of
BaseSynapse
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class
neuroml.nml.nml.BaseNonNegativeIntegerId(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseWithoutIdAnything which can have a unique (within its parent) id, which must be an integer zero or greater.
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superclass¶ alias of
BaseWithoutId
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class
neuroml.nml.nml.BaseProjection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseBase for projection (set of synaptic connections) between two populations
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class
neuroml.nml.nml.BasePynnSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapse-
superclass¶ alias of
BaseSynapse
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class
neuroml.nml.nml.BaseSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.BaseVoltageDepSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapse-
superclass¶ alias of
BaseSynapse
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class
neuroml.nml.nml.BaseWithoutId(neuro_lex_id=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperBase element without ID specified yet, e.g. for an element with a particular requirement on its id which does not comply with NmlId (e.g. Segment needs nonNegativeInteger).
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class
neuroml.nml.nml.BiophysicalProperties(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, membrane_properties=None, intracellular_properties=None, extracellular_properties=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneStandalone element which is usually inside a single cell, but could be outside and referenced by id.
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superclass¶ alias of
Standalone
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class
neuroml.nml.nml.BiophysicalProperties2CaPools(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, membrane_properties2_ca_pools=None, intracellular_properties2_ca_pools=None, extracellular_properties=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneStandalone element which is usually inside a single cell, but could be outside and referenced by id.
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superclass¶ alias of
Standalone
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class
neuroml.nml.nml.BlockingPlasticSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase=None, erev=None, tau_decay=None, tau_rise=None, plasticity_mechanism=None, block_mechanism=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ExpTwoSynapse-
superclass¶ alias of
ExpTwoSynapse
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class
neuroml.nml.nml.Cell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, morphology_attr=None, biophysical_properties_attr=None, morphology=None, biophysical_properties=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCellShould only be used if morphology element is outside the cell. This points to the id of the morphology Should only be used if biophysicalProperties element is outside the cell. This points to the id of the biophysicalProperties
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class
neuroml.nml.nml.Cell2CaPools(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, morphology_attr=None, biophysical_properties_attr=None, morphology=None, biophysical_properties=None, biophysical_properties2_ca_pools=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Cell
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class
neuroml.nml.nml.CellSet(neuro_lex_id=None, id=None, select=None, anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
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class
neuroml.nml.nml.ChannelDensity(neuro_lex_id=None, id=None, ion_channel=None, cond_density=None, erev=None, segment_groups='all', segments=None, ion=None, variable_parameters=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityGHK(neuro_lex_id=None, id=None, ion_channel=None, permeability=None, segment_groups='all', segments=None, ion=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityGHK2(neuro_lex_id=None, id=None, ion_channel=None, cond_density=None, segment_groups='all', segments=None, ion=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityNernst(neuro_lex_id=None, id=None, ion_channel=None, cond_density=None, segment_groups='all', segments=None, ion=None, variable_parameters=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityNernstCa2(neuro_lex_id=None, id=None, ion_channel=None, cond_density=None, segment_groups='all', segments=None, ion=None, variable_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ChannelDensityNernst-
superclass¶ alias of
ChannelDensityNernst
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class
neuroml.nml.nml.ChannelDensityNonUniform(neuro_lex_id=None, id=None, ion_channel=None, erev=None, ion=None, variable_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityNonUniformGHK(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityNonUniformNernst(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ChannelDensityVShift(neuro_lex_id=None, id=None, ion_channel=None, cond_density=None, erev=None, segment_groups='all', segments=None, ion=None, variable_parameters=None, v_shift=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ChannelDensity-
superclass¶ alias of
ChannelDensity
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class
neuroml.nml.nml.ChannelPopulation(neuro_lex_id=None, id=None, ion_channel=None, number=None, erev=None, segment_groups='all', segments=None, ion=None, variable_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSpecifying the ion here again is redundant, this will be set in ionChannel definition. It is added here TEMPORARILY since selecting all ca or na conducting channel populations/densities in a cell would be difficult otherwise. Also, it will make it easier to set the correct native simulator value for erev (e.g. ek for ion = k in NEURON). Currently a required attribute. It should be removed in the longer term, due to possible inconsistencies in this value and that in the ionChannel element. TODO: remove.
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class
neuroml.nml.nml.ClosedState(neuro_lex_id=None, id=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
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class
neuroml.nml.nml.ComponentType(name=None, extends=None, description=None, Property=None, Parameter=None, Constant=None, Exposure=None, Requirement=None, InstanceRequirement=None, Dynamics=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperContains an extension to NeuroML by creating custom LEMS ComponentType.
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class
neuroml.nml.nml.CompoundInput(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, pulse_generators=None, sine_generators=None, ramp_generators=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.CompoundInputDL(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, pulse_generator_dls=None, sine_generator_dls=None, ramp_generator_dls=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.ConcentrationModel_D(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, ion=None, resting_conc=None, decay_constant=None, shell_thickness=None, type='decayingPoolConcentrationModel', **kwargs_)¶ Bases:
neuroml.nml.nml.DecayingPoolConcentrationModel-
superclass¶ alias of
DecayingPoolConcentrationModel
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class
neuroml.nml.nml.ConditionalDerivedVariable(name=None, dimension=None, description=None, exposure=None, Case=None, **kwargs_)¶ Bases:
neuroml.nml.nml.NamedDimensionalVariableLEMS ComponentType for ConditionalDerivedVariable
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class
neuroml.nml.nml.Connection(neuro_lex_id=None, id=None, pre_cell_id=None, pre_segment_id='0', pre_fraction_along='0.5', post_cell_id=None, post_segment_id='0', post_fraction_along='0.5', **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionOldFormatIndividual chemical (event based) synaptic connection, weight==1 and no delay
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superclass¶ alias of
BaseConnectionOldFormat
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class
neuroml.nml.nml.ConnectionWD(neuro_lex_id=None, id=None, pre_cell_id=None, pre_segment_id='0', pre_fraction_along='0.5', post_cell_id=None, post_segment_id='0', post_fraction_along='0.5', weight=None, delay=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionOldFormatIndividual synaptic connection with weight and delay
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superclass¶ alias of
BaseConnectionOldFormat
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class
neuroml.nml.nml.Constant(name=None, dimension=None, value=None, description=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperLEMS ComponentType for Constant.
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class
neuroml.nml.nml.ContinuousConnection(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', pre_component=None, post_component=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionNewFormatIndividual continuous/analog synaptic connection
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superclass¶ alias of
BaseConnectionNewFormat
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class
neuroml.nml.nml.ContinuousConnectionInstance(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', pre_component=None, post_component=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ContinuousConnectionIndividual continuous/analog synaptic connection - instance based
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superclass¶ alias of
ContinuousConnection
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class
neuroml.nml.nml.ContinuousConnectionInstanceW(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', pre_component=None, post_component=None, weight=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ContinuousConnectionInstanceIndividual continuous/analog synaptic connection - instance based. Includes setting of _weight for the connection
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superclass¶ alias of
ContinuousConnectionInstance
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class
neuroml.nml.nml.ContinuousProjection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, continuous_connections=None, continuous_connection_instances=None, continuous_connection_instance_ws=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseProjectionProjection between two populations consisting of analog connections (e.g. graded synapses)
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superclass¶ alias of
BaseProjection
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class
neuroml.nml.nml.DecayingPoolConcentrationModel(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, ion=None, resting_conc=None, decay_constant=None, shell_thickness=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneShould not be required, as it’s present on the species element!
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superclass¶ alias of
Standalone
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class
neuroml.nml.nml.DerivedVariable(name=None, dimension=None, description=None, exposure=None, value=None, select=None, **kwargs_)¶ Bases:
neuroml.nml.nml.NamedDimensionalVariableLEMS ComponentType for DerivedVariable
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class
neuroml.nml.nml.DoubleSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, synapse1=None, synapse2=None, synapse1_path=None, synapse2_path=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseVoltageDepSynapse-
superclass¶ alias of
BaseVoltageDepSynapse
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class
neuroml.nml.nml.Dynamics(StateVariable=None, DerivedVariable=None, ConditionalDerivedVariable=None, TimeDerivative=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperLEMS ComponentType for Dynamics
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class
neuroml.nml.nml.EIF_cond_alpha_isfa_ista(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, e_rev_E=None, e_rev_I=None, a=None, b=None, delta_T=None, tau_w=None, v_spike=None, **kwargs_)¶ Bases:
neuroml.nml.nml.EIF_cond_exp_isfa_ista-
superclass¶ alias of
EIF_cond_exp_isfa_ista
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class
neuroml.nml.nml.EIF_cond_exp_isfa_ista(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, e_rev_E=None, e_rev_I=None, a=None, b=None, delta_T=None, tau_w=None, v_spike=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCondCell-
superclass¶ alias of
basePyNNIaFCondCell
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class
neuroml.nml.nml.ElectricalConnection(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', synapse=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConnectionNewFormatIndividual electrical synaptic connection
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superclass¶ alias of
BaseConnectionNewFormat
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class
neuroml.nml.nml.ElectricalConnectionInstance(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', synapse=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ElectricalConnectionProjection between two populations consisting of analog connections (e.g. graded synapses)
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superclass¶ alias of
ElectricalConnection
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class
neuroml.nml.nml.ElectricalConnectionInstanceW(neuro_lex_id=None, id=None, pre_cell=None, pre_segment='0', pre_fraction_along='0.5', post_cell=None, post_segment='0', post_fraction_along='0.5', synapse=None, weight=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ElectricalConnectionInstanceProjection between two populations consisting of analog connections (e.g. graded synapses). Includes setting of weight for the connection
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superclass¶ alias of
ElectricalConnectionInstance
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class
neuroml.nml.nml.ElectricalProjection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, electrical_connections=None, electrical_connection_instances=None, electrical_connection_instance_ws=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseProjectionProjection between two populations consisting of electrical connections (gap junctions)
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superclass¶ alias of
BaseProjection
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class
neuroml.nml.nml.ExpCondSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, e_rev=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BasePynnSynapse-
superclass¶ alias of
BasePynnSynapse
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class
neuroml.nml.nml.ExpCurrSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BasePynnSynapse-
superclass¶ alias of
BasePynnSynapse
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class
neuroml.nml.nml.ExpOneSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase=None, erev=None, tau_decay=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConductanceBasedSynapse-
superclass¶ alias of
BaseConductanceBasedSynapse
-
-
class
neuroml.nml.nml.ExpThreeSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase1=None, gbase2=None, erev=None, tau_decay1=None, tau_decay2=None, tau_rise=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConductanceBasedSynapseTwo-
superclass¶ alias of
BaseConductanceBasedSynapseTwo
-
-
class
neuroml.nml.nml.ExpTwoSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, gbase=None, erev=None, tau_decay=None, tau_rise=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseConductanceBasedSynapse-
superclass¶ alias of
BaseConductanceBasedSynapse
-
-
class
neuroml.nml.nml.ExplicitInput(target=None, input=None, destination=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperSingle explicit input. Introduced to test inputs in LEMS. Will probably be removed in favour of inputs wrapped in inputList element
-
class
neuroml.nml.nml.Exposure(name=None, dimension=None, description=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperLEMS Exposure (ComponentType property)
-
class
neuroml.nml.nml.ExtracellularProperties(neuro_lex_id=None, id=None, species=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.FitzHughNagumo1969Cell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, a=None, b=None, I=None, phi=None, V0=None, W0=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.FitzHughNagumoCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, I=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.FixedFactorConcentrationModel(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, ion=None, resting_conc=None, decay_constant=None, rho=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneShould not be required, as it’s present on the species element!
-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.ForwardTransition(neuro_lex_id=None, id=None, from_=None, to=None, anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GapJunction(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, conductance=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapseGap junction/single electrical connection
-
superclass¶ alias of
BaseSynapse
-
-
class
neuroml.nml.nml.GateFractional(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, sub_gates=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateFractionalSubgate(neuro_lex_id=None, id=None, fractional_conductance=None, notes=None, q10_settings=None, steady_state=None, time_course=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHInstantaneous(neuro_lex_id=None, id=None, instances=None, notes=None, steady_state=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHRates(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, forward_rate=None, reverse_rate=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHRatesInf(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, forward_rate=None, reverse_rate=None, steady_state=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHRatesTau(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, forward_rate=None, reverse_rate=None, time_course=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHRatesTauInf(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, forward_rate=None, reverse_rate=None, time_course=None, steady_state=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHTauInf(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, time_course=None, steady_state=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GateHHUndetermined(neuro_lex_id=None, id=None, instances=None, type=None, notes=None, q10_settings=None, forward_rate=None, reverse_rate=None, time_course=None, steady_state=None, sub_gates=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseNote all sub elements for gateHHrates, gateHHratesTau, gateFractional etc. allowed here. Which are valid should be constrained by what type is set
-
class
neuroml.nml.nml.GateKS(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, closed_states=None, open_states=None, forward_transition=None, reverse_transition=None, tau_inf_transition=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.GradedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, conductance=None, delta=None, Vth=None, k=None, erev=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapseBased on synapse in Methods of http://www.nature.com/neuro/journal/v7/n12/abs/nn1352.html.
-
superclass¶ alias of
BaseSynapse
-
-
class
neuroml.nml.nml.HH_cond_exp(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, v_offset=None, e_rev_E=None, e_rev_I=None, e_rev_K=None, e_rev_Na=None, e_rev_leak=None, g_leak=None, gbar_K=None, gbar_Na=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNCell-
superclass¶ alias of
basePyNNCell
-
-
class
neuroml.nml.nml.IF_cond_alpha(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, e_rev_E=None, e_rev_I=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCondCell-
superclass¶ alias of
basePyNNIaFCondCell
-
-
class
neuroml.nml.nml.IF_cond_exp(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, e_rev_E=None, e_rev_I=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCondCell-
superclass¶ alias of
basePyNNIaFCondCell
-
-
class
neuroml.nml.nml.IF_curr_alpha(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCell-
superclass¶ alias of
basePyNNIaFCell
-
-
class
neuroml.nml.nml.IF_curr_exp(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCell-
superclass¶ alias of
basePyNNIaFCell
-
-
class
neuroml.nml.nml.IafCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, leak_reversal=None, thresh=None, reset=None, C=None, leak_conductance=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.IafRefCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, leak_reversal=None, thresh=None, reset=None, C=None, leak_conductance=None, refract=None, **kwargs_)¶ Bases:
neuroml.nml.nml.IafCell
-
class
neuroml.nml.nml.IafTauCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, leak_reversal=None, thresh=None, reset=None, tau=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.IafTauRefCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, leak_reversal=None, thresh=None, reset=None, tau=None, refract=None, **kwargs_)¶ Bases:
neuroml.nml.nml.IafTauCell-
superclass¶ alias of
IafTauCell
-
-
class
neuroml.nml.nml.InhomogeneousParameter(neuro_lex_id=None, id=None, variable=None, metric=None, proximal=None, distal=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.InitMembPotential(value=None, segment_groups='all', segments=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroupUsing a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
-
class
neuroml.nml.nml.Input(id=None, target=None, destination=None, segment_id=None, fraction_along=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperIndividual input to the cell specified by target
-
class
neuroml.nml.nml.InputList(neuro_lex_id=None, id=None, populations=None, component=None, input=None, input_ws=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseList of inputs to a population. Currents will be provided by the specified component.
-
class
neuroml.nml.nml.InputW(id=None, target=None, destination=None, segment_id=None, fraction_along=None, weight=None, **kwargs_)¶ Bases:
neuroml.nml.nml.InputIndividual input to the cell specified by target. Includes setting of _weight for the connection
-
class
neuroml.nml.nml.IonChannel(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, q10_conductance_scalings=None, species=None, type=None, conductance=None, gates=None, gate_hh_rates=None, gate_h_hrates_taus=None, gate_hh_tau_infs=None, gate_h_hrates_infs=None, gate_h_hrates_tau_infs=None, gate_hh_instantaneouses=None, gate_fractionals=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.IonChannelScalableNote ionChannel and ionChannelHH are currently functionally identical. This is needed since many existing examples use ionChannel, some use ionChannelHH. NeuroML v2beta4 should remove one of these, probably ionChannelHH.
-
superclass¶ alias of
IonChannelScalable
-
-
class
neuroml.nml.nml.IonChannelHH(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, q10_conductance_scalings=None, species=None, type=None, conductance=None, gates=None, gate_hh_rates=None, gate_h_hrates_taus=None, gate_hh_tau_infs=None, gate_h_hrates_infs=None, gate_h_hrates_tau_infs=None, gate_hh_instantaneouses=None, gate_fractionals=None, **kwargs_)¶ Bases:
neuroml.nml.nml.IonChannelNote ionChannel and ionChannelHH are currently functionally identical. This is needed since many existing examples use ionChannel, some use ionChannelHH. NeuroML v2beta4 should remove one of these, probably ionChannelHH.
-
superclass¶ alias of
IonChannel
-
-
class
neuroml.nml.nml.IonChannelKS(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, species=None, conductance=None, gate_kses=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneKinetic scheme based ion channel.
-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.IonChannelScalable(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, q10_conductance_scalings=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.IonChannelVShift(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, q10_conductance_scalings=None, species=None, type=None, conductance=None, gates=None, gate_hh_rates=None, gate_h_hrates_taus=None, gate_hh_tau_infs=None, gate_h_hrates_infs=None, gate_h_hrates_tau_infs=None, gate_hh_instantaneouses=None, gate_fractionals=None, v_shift=None, **kwargs_)¶ Bases:
neuroml.nml.nml.IonChannelSame as ionChannel, but with a vShift parameter to change voltage activation of gates. The exact usage of vShift in expressions for rates is determined by the individual gates.
-
superclass¶ alias of
IonChannel
-
-
class
neuroml.nml.nml.Izhikevich2007Cell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, C=None, v0=None, k=None, vr=None, vt=None, vpeak=None, a=None, b=None, c=None, d=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCellMembPotCap-
superclass¶ alias of
BaseCellMembPotCap
-
-
class
neuroml.nml.nml.IzhikevichCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, v0=None, thresh=None, a=None, b=None, c=None, d=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.LinearGradedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, conductance=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapseBehaves just like a one way gap junction.
-
superclass¶ alias of
BaseSynapse
-
-
class
neuroml.nml.nml.Morphology(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, segments=None, segment_groups=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneStandalone element which is usually inside a single cell, but could be outside and referenced by id.
-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.Network(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, type=None, temperature=None, spaces=None, regions=None, extracellular_properties=None, populations=None, cell_sets=None, synaptic_connections=None, projections=None, electrical_projections=None, continuous_projections=None, explicit_inputs=None, input_lists=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.NeuroMLDocument(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, includes=None, extracellular_properties=None, intracellular_properties=None, morphology=None, ion_channel=None, ion_channel_hhs=None, ion_channel_v_shifts=None, ion_channel_kses=None, decaying_pool_concentration_models=None, fixed_factor_concentration_models=None, alpha_current_synapses=None, alpha_synapses=None, exp_one_synapses=None, exp_two_synapses=None, exp_three_synapses=None, blocking_plastic_synapses=None, double_synapses=None, gap_junctions=None, silent_synapses=None, linear_graded_synapses=None, graded_synapses=None, biophysical_properties=None, cells=None, cell2_ca_poolses=None, base_cells=None, iaf_tau_cells=None, iaf_tau_ref_cells=None, iaf_cells=None, iaf_ref_cells=None, izhikevich_cells=None, izhikevich2007_cells=None, ad_ex_ia_f_cells=None, fitz_hugh_nagumo_cells=None, fitz_hugh_nagumo1969_cells=None, pinsky_rinzel_ca3_cells=None, pulse_generators=None, pulse_generator_dls=None, sine_generators=None, sine_generator_dls=None, ramp_generators=None, ramp_generator_dls=None, compound_inputs=None, compound_input_dls=None, voltage_clamps=None, voltage_clamp_triples=None, spike_arrays=None, timed_synaptic_inputs=None, spike_generators=None, spike_generator_randoms=None, spike_generator_poissons=None, spike_generator_ref_poissons=None, poisson_firing_synapses=None, transient_poisson_firing_synapses=None, IF_curr_alpha=None, IF_curr_exp=None, IF_cond_alpha=None, IF_cond_exp=None, EIF_cond_exp_isfa_ista=None, EIF_cond_alpha_isfa_ista=None, HH_cond_exp=None, exp_cond_synapses=None, alpha_cond_synapses=None, exp_curr_synapses=None, alpha_curr_synapses=None, SpikeSourcePoisson=None, networks=None, ComponentType=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.OpenState(neuro_lex_id=None, id=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.PinskyRinzelCA3Cell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, i_soma=None, i_dend=None, gc=None, g_ls=None, g_ld=None, g_na=None, g_kdr=None, g_ca=None, g_kahp=None, g_kc=None, g_nmda=None, g_ampa=None, e_na=None, e_ca=None, e_k=None, e_l=None, qd0=None, pp=None, alphac=None, betac=None, cm=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
-
class
neuroml.nml.nml.Point3DWithDiam(x=None, y=None, z=None, diameter=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperA 3D point with diameter.
-
class
neuroml.nml.nml.PoissonFiringSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, average_rate=None, synapse=None, spike_target=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.Population(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, component=None, size=None, type=None, extracellular_properties=None, layout=None, instances=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.Projection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, synapse=None, connections=None, connection_wds=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseProjectionProjection (set of synaptic connections) between two populations. Chemical/event based synaptic transmission
-
superclass¶ alias of
BaseProjection
-
-
class
neuroml.nml.nml.Property(tag=None, value=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperGeneric property with a tag and value
-
class
neuroml.nml.nml.PulseGenerator(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, duration=None, amplitude=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneGenerates a constant current pulse of a certain amplitude (with dimensions for current) for a specified duration after a delay.
-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.PulseGeneratorDL(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, duration=None, amplitude=None, **kwargs_)¶ Bases:
neuroml.nml.nml.StandaloneGenerates a constant current pulse of a certain amplitude (non dimensional) for a specified duration after a delay.
-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.RampGenerator(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, duration=None, start_amplitude=None, finish_amplitude=None, baseline_amplitude=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.RampGeneratorDL(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, duration=None, start_amplitude=None, finish_amplitude=None, baseline_amplitude=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
-
-
class
neuroml.nml.nml.ReactionScheme(neuro_lex_id=None, id=None, source=None, type=None, anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.Region(neuro_lex_id=None, id=None, spaces=None, anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.Resistivity(value=None, segment_groups='all', segments=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroupUsing a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
-
class
neuroml.nml.nml.ReverseTransition(neuro_lex_id=None, id=None, from_=None, to=None, anytypeobjs_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.Segment(neuro_lex_id=None, id=None, name=None, parent=None, proximal=None, distal=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseNonNegativeIntegerId-
superclass¶ alias of
BaseNonNegativeIntegerId
-
-
class
neuroml.nml.nml.SegmentGroup(neuro_lex_id=None, id=None, notes=None, properties=None, annotation=None, members=None, includes=None, paths=None, sub_trees=None, inhomogeneous_parameters=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
-
class
neuroml.nml.nml.SilentSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseSynapseDummy synapse which emits no current. Used as presynaptic endpoint for analog synaptic connection (continuousConnection).
-
superclass¶ alias of
BaseSynapse
-
-
class
neuroml.nml.nml.SineGenerator(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, phase=None, duration=None, amplitude=None, period=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SineGeneratorDL(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, phase=None, duration=None, amplitude=None, period=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.Space(neuro_lex_id=None, id=None, based_on=None, structure=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
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class
neuroml.nml.nml.Species(value=None, segment_groups='all', segments=None, id=None, concentration_model=None, ion=None, initial_concentration=None, initial_ext_concentration=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroupSpecifying the ion here again is redundant, the ion name should be the same as id. Kept for now until LEMS implementation can select by id. TODO: remove.
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class
neuroml.nml.nml.SpecificCapacitance(value=None, segment_groups='all', segments=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroupUsing a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
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class
neuroml.nml.nml.Spike(neuro_lex_id=None, id=None, time=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseNonNegativeIntegerId-
superclass¶ alias of
BaseNonNegativeIntegerId
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class
neuroml.nml.nml.SpikeArray(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, spikes=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SpikeGenerator(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, period=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SpikeGeneratorPoisson(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, average_rate=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SpikeGeneratorRandom(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, max_isi=None, min_isi=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SpikeGeneratorRefPoisson(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, average_rate=None, minimum_isi=None, **kwargs_)¶ Bases:
neuroml.nml.nml.SpikeGeneratorPoisson-
superclass¶ alias of
SpikeGeneratorPoisson
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class
neuroml.nml.nml.SpikeSourcePoisson(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, start=None, duration=None, rate=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.SpikeThresh(value=None, segment_groups='all', segments=None, **kwargs_)¶ Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroupUsing a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
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class
neuroml.nml.nml.Standalone(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseElements which can stand alone and be referenced by id, e.g. cell, morphology.
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class
neuroml.nml.nml.SynapticConnection(from_=None, to=None, synapse=None, destination=None, **kwargs_)¶ Bases:
neuroml.nml.nml.GeneratedsSuperSingle explicit connection. Introduced to test connections in LEMS. Will probably be removed in favour of connections wrapped in projection element
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class
neuroml.nml.nml.TauInfTransition(neuro_lex_id=None, id=None, from_=None, to=None, steady_state=None, time_course=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Base
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class
neuroml.nml.nml.TimedSynapticInput(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, synapse=None, spike_target=None, spikes=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.TransientPoissonFiringSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, average_rate=None, delay=None, duration=None, synapse=None, spike_target=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.VoltageClamp(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, delay=None, duration=None, target_voltage=None, simple_series_resistance=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.VoltageClampTriple(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, active=None, delay=None, duration=None, conditioning_voltage=None, testing_voltage=None, return_voltage=None, simple_series_resistance=None, **kwargs_)¶ Bases:
neuroml.nml.nml.Standalone-
superclass¶ alias of
Standalone
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class
neuroml.nml.nml.basePyNNCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.BaseCell
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class
neuroml.nml.nml.basePyNNIaFCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNCell-
superclass¶ alias of
basePyNNCell
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class
neuroml.nml.nml.basePyNNIaFCondCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, cm=None, i_offset=None, tau_syn_E=None, tau_syn_I=None, v_init=None, tau_m=None, tau_refrac=None, v_reset=None, v_rest=None, v_thresh=None, e_rev_E=None, e_rev_I=None, extensiontype_=None, **kwargs_)¶ Bases:
neuroml.nml.nml.basePyNNIaFCell-
superclass¶ alias of
basePyNNIaFCell
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