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
- 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
neuroml.nml.nml.BaseCellMembPotCap
- 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
neuroml.nml.nml.BasePynnSynapse
- 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
neuroml.nml.nml.BasePynnSynapse
- 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¶
- 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¶
- class neuroml.nml.nml.Annotation(anytypeobjs_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
Placeholder for MIRIAM related metadata, among others.
- class neuroml.nml.nml.Base(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.BaseWithoutId
Anything which can have a unique (within its parent) id of the form NmlId (spaceless combination of letters, numbers and underscore).
- superclass¶
alias of
neuroml.nml.nml.BaseWithoutId
- 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
neuroml.nml.nml.Standalone
- 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.BaseCell
This is to prevent it conflicting with attribute c (lowercase) e.g. in izhikevichCell2007
- superclass¶
alias of
neuroml.nml.nml.BaseCell
- 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¶
- 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¶
- class neuroml.nml.nml.BaseConnection(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.BaseNonNegativeIntegerId
Base of all synaptic connections (chemical/electrical/analog, etc.) inside projections
- superclass¶
- 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.BaseConnection
Base of all synaptic connections with preCell, postSegment, etc. See BaseConnectionOldFormat
- superclass¶
alias of
neuroml.nml.nml.BaseConnection
- 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.BaseConnection
Base of all synaptic connections with preCellId, postSegmentId, etc. Note: this is not the best name for these attributes, since Id is superfluous, hence BaseConnectionNewFormat
- superclass¶
alias of
neuroml.nml.nml.BaseConnection
- 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
neuroml.nml.nml.BaseSynapse
- class neuroml.nml.nml.BaseNonNegativeIntegerId(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.BaseWithoutId
Anything which can have a unique (within its parent) id, which must be an integer zero or greater.
- superclass¶
alias of
neuroml.nml.nml.BaseWithoutId
- class neuroml.nml.nml.BaseProjection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, extensiontype_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
Base for projection (set of synaptic connections) between two populations
- superclass¶
alias of
neuroml.nml.nml.Base
- 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
neuroml.nml.nml.BaseSynapse
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.BaseSynapse
- class neuroml.nml.nml.BaseWithoutId(neuro_lex_id=None, extensiontype_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
Base 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).
- 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.Standalone
Standalone element which is usually inside a single cell, but could be outside and referenced by id.
- superclass¶
alias of
neuroml.nml.nml.Standalone
- 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.Standalone
Standalone element which is usually inside a single cell, but could be outside and referenced by id.
- superclass¶
alias of
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.ExpTwoSynapse
- 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.BaseCell
Should 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
- superclass¶
alias of
neuroml.nml.nml.BaseCell
- 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
- superclass¶
alias of
neuroml.nml.nml.Cell
- class neuroml.nml.nml.CellSet(neuro_lex_id=None, id=None, select=None, anytypeobjs_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- 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
neuroml.nml.nml.ChannelDensityNernst
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.ChannelDensityNonUniformGHK(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.ChannelDensityNonUniformNernst(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- 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
neuroml.nml.nml.ChannelDensity
- 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.Base
Specifying 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.
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.ClosedState(neuro_lex_id=None, id=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.GeneratedsSuper
Contains an extension to NeuroML by creating custom LEMS ComponentType.
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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¶
- class neuroml.nml.nml.ConditionalDerivedVariable(name=None, dimension=None, description=None, exposure=None, Case=None, **kwargs_)¶
Bases:
neuroml.nml.nml.NamedDimensionalVariable
LEMS ComponentType for ConditionalDerivedVariable
- 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.BaseConnectionOldFormat
Individual chemical (event based) synaptic connection, weight==1 and no delay
- superclass¶
- 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.BaseConnectionOldFormat
Individual synaptic connection with weight and delay
- superclass¶
- class neuroml.nml.nml.Constant(name=None, dimension=None, value=None, description=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
LEMS ComponentType for Constant.
- 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.BaseConnectionNewFormat
Individual continuous/analog synaptic connection
- superclass¶
- 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.ContinuousConnection
Individual continuous/analog synaptic connection - instance based
- superclass¶
alias of
neuroml.nml.nml.ContinuousConnection
- 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.ContinuousConnectionInstance
Individual continuous/analog synaptic connection - instance based. Includes setting of _weight for the connection
- superclass¶
- 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.BaseProjection
Projection between two populations consisting of analog connections (e.g. graded synapses)
- superclass¶
alias of
neuroml.nml.nml.BaseProjection
- 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.Standalone
Should not be required, as it’s present on the species element!
- superclass¶
alias of
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.DerivedVariable(name=None, dimension=None, description=None, exposure=None, value=None, select=None, **kwargs_)¶
Bases:
neuroml.nml.nml.NamedDimensionalVariable
LEMS ComponentType for DerivedVariable
- 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¶
- class neuroml.nml.nml.Dynamics(StateVariable=None, DerivedVariable=None, ConditionalDerivedVariable=None, TimeDerivative=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
LEMS ComponentType for Dynamics
- 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¶
- 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
neuroml.nml.nml.basePyNNIaFCondCell
- 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.BaseConnectionNewFormat
Individual electrical synaptic connection
- superclass¶
- 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.ElectricalConnection
Projection between two populations consisting of analog connections (e.g. graded synapses)
- superclass¶
alias of
neuroml.nml.nml.ElectricalConnection
- 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.ElectricalConnectionInstance
Projection between two populations consisting of analog connections (e.g. graded synapses). Includes setting of weight for the connection
- superclass¶
- 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.BaseProjection
Projection between two populations consisting of electrical connections (gap junctions)
- superclass¶
alias of
neuroml.nml.nml.BaseProjection
- 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
neuroml.nml.nml.BasePynnSynapse
- 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
neuroml.nml.nml.BasePynnSynapse
- 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¶
- 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¶
- 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¶
- class neuroml.nml.nml.ExplicitInput(target=None, input=None, destination=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
Single 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.GeneratedsSuper
LEMS Exposure (ComponentType property)
- class neuroml.nml.nml.ExtracellularProperties(neuro_lex_id=None, id=None, species=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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.Standalone
Should not be required, as it’s present on the species element!
- superclass¶
alias of
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.ForwardTransition(neuro_lex_id=None, id=None, from_=None, to=None, anytypeobjs_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
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.BaseSynapse
Gap junction/single electrical connection
- superclass¶
alias of
neuroml.nml.nml.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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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.Base
Note all sub elements for gateHHrates, gateHHratesTau, gateFractional etc. allowed here. Which are valid should be constrained by what type is set
- superclass¶
alias of
neuroml.nml.nml.Base
- 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
- superclass¶
alias of
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.BaseSynapse
Based on synapse in Methods of http://www.nature.com/neuro/journal/v7/n12/abs/nn1352.html.
- superclass¶
alias of
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.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
- superclass¶
alias of
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
- superclass¶
alias of
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
- superclass¶
alias of
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
neuroml.nml.nml.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
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.InitMembPotential(value=None, segment_groups='all', segments=None, **kwargs_)¶
Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroup
Using 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.GeneratedsSuper
Individual 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.Base
List of inputs to a population. Currents will be provided by the specified component.
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.InputW(id=None, target=None, destination=None, segment_id=None, fraction_along=None, weight=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Input
Individual input to the cell specified by target. Includes setting of _weight for the connection
- superclass¶
alias of
neuroml.nml.nml.Input
- 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.IonChannelScalable
Note 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
neuroml.nml.nml.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.IonChannel
Note 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
neuroml.nml.nml.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.Standalone
Kinetic scheme based ion channel.
- superclass¶
alias of
neuroml.nml.nml.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
neuroml.nml.nml.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.IonChannel
Same 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
neuroml.nml.nml.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
neuroml.nml.nml.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
- superclass¶
alias of
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.BaseSynapse
Behaves just like a one way gap junction.
- superclass¶
alias of
neuroml.nml.nml.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.Standalone
Standalone element which is usually inside a single cell, but could be outside and referenced by id.
- superclass¶
alias of
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.OpenState(neuro_lex_id=None, id=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
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
- superclass¶
alias of
neuroml.nml.nml.BaseCell
- class neuroml.nml.nml.Point3DWithDiam(x=None, y=None, z=None, diameter=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
A 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
neuroml.nml.nml.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
neuroml.nml.nml.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.BaseProjection
Projection (set of synaptic connections) between two populations. Chemical/event based synaptic transmission
- superclass¶
alias of
neuroml.nml.nml.BaseProjection
- class neuroml.nml.nml.Property(tag=None, value=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
Generic 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.Standalone
Generates a constant current pulse of a certain amplitude (with dimensions for current) for a specified duration after a delay.
- superclass¶
alias of
neuroml.nml.nml.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.Standalone
Generates a constant current pulse of a certain amplitude (non dimensional) for a specified duration after a delay.
- superclass¶
alias of
neuroml.nml.nml.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
neuroml.nml.nml.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
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.ReactionScheme(neuro_lex_id=None, id=None, source=None, type=None, anytypeobjs_=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
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
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.Resistivity(value=None, segment_groups='all', segments=None, **kwargs_)¶
Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroup
Using 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
- superclass¶
alias of
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¶
- 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
- superclass¶
alias of
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.BaseSynapse
Dummy synapse which emits no current. Used as presynaptic endpoint for analog synaptic connection (continuousConnection).
- superclass¶
alias of
neuroml.nml.nml.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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.Space(neuro_lex_id=None, id=None, based_on=None, structure=None, **kwargs_)¶
Bases:
neuroml.nml.nml.Base
- superclass¶
alias of
neuroml.nml.nml.Base
- 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.ValueAcrossSegOrSegGroup
Specifying 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.
- class neuroml.nml.nml.SpecificCapacitance(value=None, segment_groups='all', segments=None, **kwargs_)¶
Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroup
Using a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
- class neuroml.nml.nml.Spike(neuro_lex_id=None, id=None, time=None, **kwargs_)¶
Bases:
neuroml.nml.nml.BaseNonNegativeIntegerId
- superclass¶
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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¶
- 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
neuroml.nml.nml.Standalone
- class neuroml.nml.nml.SpikeThresh(value=None, segment_groups='all', segments=None, **kwargs_)¶
Bases:
neuroml.nml.nml.ValueAcrossSegOrSegGroup
Using a thin extension of ValueAcrossSegOrSegGroup to facilitate library generation (e.g. libNeuroML)
- 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.Base
Elements which can stand alone and be referenced by id, e.g. cell, morphology.
- superclass¶
alias of
neuroml.nml.nml.Base
- class neuroml.nml.nml.SynapticConnection(from_=None, to=None, synapse=None, destination=None, **kwargs_)¶
Bases:
neuroml.nml.nml.GeneratedsSuper
Single explicit connection. Introduced to test connections in LEMS. Will probably be removed in favour of connections wrapped in projection element
- 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
- superclass¶
alias of
neuroml.nml.nml.Base
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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
neuroml.nml.nml.Standalone
- 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
- superclass¶
alias of
neuroml.nml.nml.BaseCell
- 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
neuroml.nml.nml.basePyNNCell
- 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
neuroml.nml.nml.basePyNNIaFCell