`nml` Module (NeuroML Core classes)¶

These NeuroML core classes are Python representations of the Component Types defined in the NeuroML standard . These can be used to build NeuroML models in Python, and these models can then be exported to the standard XML NeuroML representation. These core classes also contain some utility functions to make it easier for users to carry out common tasks.

Each NeuroML Component Type is represented here as a Python class. Due to implementation limitations, whereas NeuroML Component Types use lower camel case naming, the Python classes here use upper camel case naming. So, for example, the adExIaFCell Component Type in the NeuroML schema becomes the AdExIaFCell class here, and expTwoSynapse becomes the ExpTwoSynapse class.

The child and children elements that NeuroML Component Types can have are represented in the Python classes as variables. The variable names, to distinguish them from class names, use snake case. So for example, the cell NeuroML Component Type has a corresponding Cell Python class here. The biophysicalProperties child Component Type in cell is represented as the biophysical_properties list variable in the Cell Python class. The class signatures list all the child/children elements and text fields that the corresponding Component Type possesses. To again use the Cell class as an example, the construction signature is this:

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_)

As can be seen here, it includes both the biophysical_properties and morphology child elements as variables.

Please see the examples in the NeuroML documentation to see usage examples of libNeuroML. Please also note that this module is also included in the top level of the neuroml package, so you can use these classes by importing neuroml:

from neuroml import AdExIaFCell

List of Component classes¶

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_)¶

AlphaCondSynapse¶

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_)¶

AlphaCurrSynapse¶

class neuroml.nml.nml.AlphaCurrSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, **kwargs_)¶

AlphaCurrentSynapse¶

class neuroml.nml.nml.AlphaCurrentSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau=None, ibase=None, **kwargs_)¶

AlphaSynapse¶

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_)¶

Annotation¶

class neuroml.nml.nml.Annotation(anytypeobjs_=None, **kwargs_)¶: Placeholder for MIRIAM related metadata, among others.

Base¶

class neuroml.nml.nml.Base(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶: Anything which can have a unique (within its parent) id of the form NmlId (spaceless combination of letters, numbers and underscore).

BaseCell¶

class neuroml.nml.nml.BaseCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶

BaseCellMembPotCap¶

class neuroml.nml.nml.BaseCellMembPotCap(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, C=None, extensiontype_=None, **kwargs_)¶: This is to prevent it conflicting with attribute c (lowercase) e.g. in izhikevichCell2007

BaseConductanceBasedSynapse¶

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_)¶

BaseConductanceBasedSynapseTwo¶

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_)¶

BaseConnection¶

class neuroml.nml.nml.BaseConnection(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶: Base of all synaptic connections (chemical/electrical/analog, etc.) inside projections

BaseConnectionNewFormat¶

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_)¶: Base of all synaptic connections with preCell, postSegment, etc. See BaseConnectionOldFormat

BaseConnectionOldFormat¶

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_)¶: 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

BaseCurrentBasedSynapse¶

class neuroml.nml.nml.BaseCurrentBasedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶

BaseNonNegativeIntegerId¶

class neuroml.nml.nml.BaseNonNegativeIntegerId(neuro_lex_id=None, id=None, extensiontype_=None, **kwargs_)¶: Anything which can have a unique (within its parent) id, which must be an integer zero or greater.

BaseProjection¶

class neuroml.nml.nml.BaseProjection(neuro_lex_id=None, id=None, presynaptic_population=None, postsynaptic_population=None, extensiontype_=None, **kwargs_)¶: Base for projection (set of synaptic connections) between two populations

BasePynnSynapse¶

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_)¶

BaseSynapse¶

class neuroml.nml.nml.BaseSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶

BaseVoltageDepSynapse¶

class neuroml.nml.nml.BaseVoltageDepSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶

BaseWithoutId¶

class neuroml.nml.nml.BaseWithoutId(neuro_lex_id=None, extensiontype_=None, **kwargs_)¶: 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).

BiophysicalProperties¶

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_)¶: Standalone element which is usually inside a single cell, but could be outside and referenced by id.

BiophysicalProperties2CaPools¶

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_)¶: Standalone element which is usually inside a single cell, but could be outside and referenced by id.

BlockMechanism¶

class neuroml.nml.nml.BlockMechanism(type=None, species=None, block_concentration=None, scaling_conc=None, scaling_volt=None, **kwargs_)¶

BlockingPlasticSynapse¶

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_)¶

Case¶

class neuroml.nml.nml.Case(condition=None, value=None, **kwargs_)¶

Cell¶

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_)¶

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

get_actual_proximal(segment_id)¶

Get the proximal point of a segment.

Get the proximal point of a segment, even the proximal field is None and so the proximal point is on the parent (at a point set by fraction_along).

Parameters: segment_id – ID of segment
Returns: proximal point

get_all_segments_in_group(segment_group, assume_all_means_all=True)¶

Get all the segments in a segment group of the cell.

Parameters

segment_group – segment group to get all segments of
assume_all_means_all – return all segments if the segment group wasn’t explicitly defined

Todo

check docstring

Returns

list of segments

Raises

Exception – if no segment group is found in the cell.

get_ordered_segments_in_groups(group_list, check_parentage=False, include_cumulative_lengths=False, include_path_lengths=False, path_length_metric='Path Length from root')¶

Get ordered list of segments in specified groups

Parameters

group_list – list of groups to get segments from
check_parentage – verify parentage
include_commulative_lengths – also include cummulative lengths
include_path_lengths – also include path lengths
path_length_metric –

Returns

dictionary of segments with additional information depending on what parameters were used:

Raises

Exception if check_parentage is True and parentage cannot be verified

get_segment(segment_id)¶

Get segment object by its id

Parameters: segment_id – ID of segment
Returns: segment
Raises: Exception – if the segment is not found in the cell

get_segment_group(sg_id)¶

Return the SegmentGroup object for the specified segment group id.

Parameters: sg_id (str) – id of segment group to find
Returns: SegmentGroup object of specified ID
Raises: Exception – if segment group is not found in cell

get_segment_groups_by_substring(substring)¶

Get a dictionary of segment group IDs and the segment groups matching the specified substring

Parameters: substring (str) – substring to match
Returns: dictionary with segment group ID as key, and segment group as value
Raises: Exception – if no segment groups are not found in cell

get_segment_ids_vs_segments()¶

Get a dictionary of segment IDs and the segments in the cell.

Returns: dictionary with segment ID as key, and segment as value

get_segment_length(segment_id)¶

Get the length of the segment.

Parameters: segment_id – ID of segment
Returns: length of segment

get_segment_surface_area(segment_id)¶

Get the surface area of the segment.

Parameters: segment_id – ID of the segment
Returns: surface area of segment

get_segment_volume(segment_id)¶

Get volume of segment

Parameters: segment_id – ID of the segment
Returns: volume of the segment

get_segments_by_substring(substring)¶

Get a dictionary of segment IDs and the segment matching the specified substring

Parameters: substring (str) – substring to match
Returns: dictionary with segment ID as key, and segment as value
Raises: Exception – if no segments are found

summary()¶: Print cell summary.

Cell2CaPools¶

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_)¶

CellSet¶

class neuroml.nml.nml.CellSet(neuro_lex_id=None, id=None, select=None, anytypeobjs_=None, **kwargs_)¶

ChannelDensity¶

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_)¶: 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.

ChannelDensityGHK¶

class neuroml.nml.nml.ChannelDensityGHK(neuro_lex_id=None, id=None, ion_channel=None, permeability=None, segment_groups='all', segments=None, ion=None, **kwargs_)¶: 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.

ChannelDensityGHK2¶

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_)¶: 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.

ChannelDensityNernst¶

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_)¶: 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.

ChannelDensityNernstCa2¶

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_)¶

ChannelDensityNonUniform¶

class neuroml.nml.nml.ChannelDensityNonUniform(neuro_lex_id=None, id=None, ion_channel=None, erev=None, ion=None, variable_parameters=None, **kwargs_)¶: 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.

ChannelDensityNonUniformGHK¶

class neuroml.nml.nml.ChannelDensityNonUniformGHK(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶: 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.

ChannelDensityNonUniformNernst¶

class neuroml.nml.nml.ChannelDensityNonUniformNernst(neuro_lex_id=None, id=None, ion_channel=None, ion=None, variable_parameters=None, **kwargs_)¶: 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.

ChannelDensityVShift¶

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_)¶

ChannelPopulation¶

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_)¶: 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.

ClosedState¶

class neuroml.nml.nml.ClosedState(neuro_lex_id=None, id=None, **kwargs_)¶

ComponentType¶

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_)¶: Contains an extension to NeuroML by creating custom LEMS ComponentType.

CompoundInput¶

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_)¶

CompoundInputDL¶

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_)¶

ConcentrationModel_D¶

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_)¶

ConditionalDerivedVariable¶

class neuroml.nml.nml.ConditionalDerivedVariable(name=None, dimension=None, description=None, exposure=None, Case=None, **kwargs_)¶: LEMS ComponentType for ConditionalDerivedVariable

Connection¶

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_)¶

Individual chemical (event based) synaptic connection, weight==1 and no delay

get_post_cell_id()¶

Get the ID of the post-synaptic cell

Returns: ID of post-synaptic cell
Return type: str

get_post_fraction_along()¶: Get post-synaptic fraction along information

get_post_info()¶: Get post-synaptic information summary

get_post_segment_id()¶

Get the ID of the post-synpatic segment

Returns: ID of post-synaptic segment.
Return type: str

get_pre_cell_id()¶

Get the ID of the pre-synaptic cell

Returns: ID of pre-synaptic cell
Return type: str

get_pre_fraction_along()¶: Get pre-synaptic fraction along information

get_pre_info()¶: Get pre-synaptic information summary

get_pre_segment_id()¶

Get the ID of the pre-synpatic segment

Returns: ID of pre-synaptic segment.
Return type: str

ConnectionWD¶

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_)¶

Individual synaptic connection with weight and delay

get_delay_in_ms()¶

Get connection delay in milli seconds

Returns: connection delay in milli seconds
Return type: float

get_post_cell_id()¶

Get the ID of the post-synaptic cell

Returns: ID of post-synaptic cell
Return type: str

get_post_fraction_along()¶: Get post-synaptic fraction along information

get_post_info()¶: Get post-synaptic information summary

get_post_segment_id()¶

Get the ID of the post-synpatic segment

Returns: ID of post-synaptic segment.
Return type: str

get_pre_cell_id()¶

Get the ID of the pre-synaptic cell

Returns: ID of pre-synaptic cell
Return type: str

get_pre_fraction_along()¶: Get pre-synaptic fraction along information

get_pre_info()¶: Get pre-synaptic information summary

get_pre_segment_id()¶

Get the ID of the pre-synpatic segment

Returns: ID of pre-synaptic segment.
Return type: str

Constant¶

class neuroml.nml.nml.Constant(name=None, dimension=None, value=None, description=None, **kwargs_)¶: LEMS ComponentType for Constant.

ContinuousConnection¶

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_)¶

Individual continuous/analog synaptic connection

get_post_cell_id()¶

Get the ID of the post-synaptic cell

Returns: ID of post-synaptic cell
Return type: str

get_post_fraction_along()¶: Get post-synaptic fraction along information

get_post_info()¶: Get post-synaptic information summary

get_post_segment_id()¶

Get the ID of the post-synpatic segment

Returns: ID of post-synaptic segment.
Return type: str

get_pre_cell_id()¶

Get the ID of the pre-synaptic cell

Returns: ID of pre-synaptic cell
Return type: str

get_pre_fraction_along()¶: Get pre-synaptic fraction along information

get_pre_info()¶: Get pre-synaptic information summary

get_pre_segment_id()¶

Get the ID of the pre-synpatic segment

Returns: ID of pre-synaptic segment.
Return type: str

ContinuousConnectionInstance¶

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_)¶: Individual continuous/analog synaptic connection - instance based

ContinuousConnectionInstanceW¶

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_)¶

Individual continuous/analog synaptic connection - instance based. Includes setting of _weight for the connection

get_weight()¶

Get weight.

If weight is not set, the default value of 1.0 is returned.

ContinuousProjection¶

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_)¶

Projection between two populations consisting of analog connections (e.g. graded synapses)

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

DecayingPoolConcentrationModel¶

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_)¶: Should not be required, as it’s present on the species element!

DerivedVariable¶

class neuroml.nml.nml.DerivedVariable(name=None, dimension=None, description=None, exposure=None, value=None, select=None, **kwargs_)¶: LEMS ComponentType for DerivedVariable

DistalDetails¶

class neuroml.nml.nml.DistalDetails(normalization_end=None, **kwargs_)¶

DoubleSynapse¶

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_)¶

Dynamics¶

class neuroml.nml.nml.Dynamics(StateVariable=None, DerivedVariable=None, ConditionalDerivedVariable=None, TimeDerivative=None, **kwargs_)¶: LEMS ComponentType for Dynamics

EIF_cond_alpha_isfa_ista¶

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_)¶

EIF_cond_exp_isfa_ista¶

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_)¶

ElectricalConnection¶

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_)¶

Individual electrical synaptic connection

get_post_cell_id()¶

Get the ID of the post-synaptic cell

Returns: ID of post-synaptic cell
Return type: str

get_post_fraction_along()¶: Get post-synaptic fraction along information

get_post_info()¶: Get post-synaptic information summary

get_post_segment_id()¶

Get the ID of the post-synpatic segment

Returns: ID of post-synaptic segment.
Return type: str

get_pre_cell_id()¶

Get the ID of the pre-synaptic cell

Returns: ID of pre-synaptic cell
Return type: str

get_pre_fraction_along()¶: Get pre-synaptic fraction along information

get_pre_info()¶: Get pre-synaptic information summary

get_pre_segment_id()¶

Get the ID of the pre-synpatic segment

Returns: ID of pre-synaptic segment.
Return type: str

ElectricalConnectionInstance¶

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_)¶: Projection between two populations consisting of analog connections (e.g. graded synapses)

ElectricalConnectionInstanceW¶

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_)¶

Projection between two populations consisting of analog connections (e.g. graded synapses). Includes setting of weight for the connection

get_weight()¶

Get the weight of the connection

If a weight is not set (or is set to None), returns the default value of 1.0.

Returns: weight of connection or 1.0 if not set
Return type: float

ElectricalProjection¶

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_)¶

Projection between two populations consisting of electrical connections (gap junctions)

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

ExpCondSynapse¶

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_)¶

ExpCurrSynapse¶

class neuroml.nml.nml.ExpCurrSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, tau_syn=None, **kwargs_)¶

ExpOneSynapse¶

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_)¶

ExpThreeSynapse¶

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_)¶

ExpTwoSynapse¶

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_)¶

ExplicitInput¶

class neuroml.nml.nml.ExplicitInput(target=None, input=None, destination=None, **kwargs_)¶

Single explicit input. Introduced to test inputs in LEMS. Will probably be removed in favour of inputs wrapped in inputList element

get_fraction_along()¶

Get fraction along.

Returns 0.5 is fraction_along was not set.

get_segment_id()¶

Get the ID of the segment.

Returns 0 if segment_id was not set.

get_target_cell_id()¶: Get target cell ID

get_target_population()¶: Get target population.

Exposure¶

class neuroml.nml.nml.Exposure(name=None, dimension=None, description=None, **kwargs_)¶: LEMS Exposure (ComponentType property)

ExtracellularProperties¶

class neuroml.nml.nml.ExtracellularProperties(neuro_lex_id=None, id=None, species=None, **kwargs_)¶

ExtracellularPropertiesLocal¶

class neuroml.nml.nml.ExtracellularPropertiesLocal(species=None, **kwargs_)¶

FitzHughNagumo1969Cell¶

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_)¶

FitzHughNagumoCell¶

class neuroml.nml.nml.FitzHughNagumoCell(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, I=None, **kwargs_)¶

FixedFactorConcentrationModel¶

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_)¶: Should not be required, as it’s present on the species element!

ForwardTransition¶

class neuroml.nml.nml.ForwardTransition(neuro_lex_id=None, id=None, from_=None, to=None, anytypeobjs_=None, **kwargs_)¶

GapJunction¶

class neuroml.nml.nml.GapJunction(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, conductance=None, **kwargs_)¶: Gap junction/single electrical connection

GateFractional¶

class neuroml.nml.nml.GateFractional(neuro_lex_id=None, id=None, instances=None, notes=None, q10_settings=None, sub_gates=None, **kwargs_)¶

GateFractionalSubgate¶

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_)¶

GateHHInstantaneous¶

class neuroml.nml.nml.GateHHInstantaneous(neuro_lex_id=None, id=None, instances=None, notes=None, steady_state=None, **kwargs_)¶

GateHHRates¶

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_)¶

GateHHRatesInf¶

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_)¶

GateHHRatesTau¶

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_)¶

GateHHRatesTauInf¶

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_)¶

GateHHTauInf¶

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_)¶

GateHHUndetermined¶

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_)¶: Note all sub elements for gateHHrates, gateHHratesTau, gateFractional etc. allowed here. Which are valid should be constrained by what type is set

GateKS¶

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_)¶

GradedSynapse¶

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_)¶: Based on synapse in Methods of http://www.nature.com/neuro/journal/v7/n12/abs/nn1352.html.

GridLayout¶

class neuroml.nml.nml.GridLayout(x_size=None, y_size=None, z_size=None, **kwargs_)¶

HHRate¶

class neuroml.nml.nml.HHRate(type=None, rate=None, midpoint=None, scale=None, **kwargs_)¶

HHTime¶

class neuroml.nml.nml.HHTime(type=None, rate=None, midpoint=None, scale=None, tau=None, **kwargs_)¶

HHVariable¶

class neuroml.nml.nml.HHVariable(type=None, rate=None, midpoint=None, scale=None, **kwargs_)¶

HH_cond_exp¶

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_)¶

IF_cond_alpha¶

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_)¶

IF_cond_exp¶

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_)¶

IF_curr_alpha¶

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_)¶

IF_curr_exp¶

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_)¶

IafCell¶

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_)¶

IafRefCell¶

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_)¶

IafTauCell¶

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_)¶

IafTauRefCell¶

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_)¶

Include¶

class neuroml.nml.nml.Include(segment_groups=None, **kwargs_)¶

IncludeType¶

class neuroml.nml.nml.IncludeType(href=None, **kwargs_)¶

InhomogeneousParameter¶

class neuroml.nml.nml.InhomogeneousParameter(neuro_lex_id=None, id=None, variable=None, metric=None, proximal=None, distal=None, **kwargs_)¶

InhomogeneousValue¶

class neuroml.nml.nml.InhomogeneousValue(inhomogeneous_parameters=None, value=None, **kwargs_)¶

InitMembPotential¶

class neuroml.nml.nml.InitMembPotential(value=None, segment_groups='all', **kwargs_)¶: Explicitly set initial membrane potential for the cell

Input¶

class neuroml.nml.nml.Input(id=None, target=None, destination=None, segment_id=None, fraction_along=None, extensiontype_=None, **kwargs_)¶

Individual input to the cell specified by target

get_fraction_along()¶

Get fraction along.

Returns 0.5 is fraction_along was not set.

get_segment_id()¶

Get the ID of the segment.

Returns 0 if segment_id was not set.

get_target_cell_id()¶: Get ID of target cell.

InputList¶

class neuroml.nml.nml.InputList(neuro_lex_id=None, id=None, populations=None, component=None, input=None, input_ws=None, **kwargs_)¶

List of inputs to a population. Currents will be provided by the specified component.

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

InputW¶

class neuroml.nml.nml.InputW(id=None, target=None, destination=None, segment_id=None, fraction_along=None, weight=None, **kwargs_)¶

Individual input to the cell specified by target. Includes setting of _weight for the connection

get_weight()¶

Get weight.

If weight is not set, the default value of 1.0 is returned.

Instance¶

class neuroml.nml.nml.Instance(id=None, i=None, j=None, k=None, location=None, **kwargs_)¶

InstanceRequirement¶

class neuroml.nml.nml.InstanceRequirement(name=None, type=None, **kwargs_)¶

IntracellularProperties¶

class neuroml.nml.nml.IntracellularProperties(species=None, resistivities=None, extensiontype_=None, **kwargs_)¶

IntracellularProperties2CaPools¶

class neuroml.nml.nml.IntracellularProperties2CaPools(species=None, resistivities=None, **kwargs_)¶

IonChannel¶

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_)¶: Note ionChannel and ionChannelHH are currently functionally identical. This is needed since many existing examples use ionChannel, some use ionChannelHH. One of these should be removed, probably ionChannelHH.

IonChannelHH¶

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_)¶: Note ionChannel and ionChannelHH are currently functionally identical. This is needed since many existing examples use ionChannel, some use ionChannelHH. One of these should be removed, probably ionChannelHH.

IonChannelKS¶

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_)¶: Kinetic scheme based ion channel.

IonChannelScalable¶

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_)¶

IonChannelVShift¶

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_)¶: 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.

Izhikevich2007Cell¶

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_)¶

IzhikevichCell¶

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_)¶

LEMS_Property¶

class neuroml.nml.nml.LEMS_Property(name=None, dimension=None, description=None, default_value=None, **kwargs_)¶

Layout¶

class neuroml.nml.nml.Layout(spaces=None, random=None, grid=None, unstructured=None, **kwargs_)¶

LinearGradedSynapse¶

class neuroml.nml.nml.LinearGradedSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, conductance=None, **kwargs_)¶: Behaves just like a one way gap junction.

Location¶

class neuroml.nml.nml.Location(x=None, y=None, z=None, **kwargs_)¶

Member¶

class neuroml.nml.nml.Member(segments=None, **kwargs_)¶

MembraneProperties¶

class neuroml.nml.nml.MembraneProperties(channel_populations=None, channel_densities=None, channel_density_v_shifts=None, channel_density_nernsts=None, channel_density_ghks=None, channel_density_ghk2s=None, channel_density_non_uniforms=None, channel_density_non_uniform_nernsts=None, channel_density_non_uniform_ghks=None, spike_threshes=None, specific_capacitances=None, init_memb_potentials=None, extensiontype_=None, **kwargs_)¶

MembraneProperties2CaPools¶

class neuroml.nml.nml.MembraneProperties2CaPools(channel_populations=None, channel_densities=None, channel_density_v_shifts=None, channel_density_nernsts=None, channel_density_ghks=None, channel_density_ghk2s=None, channel_density_non_uniforms=None, channel_density_non_uniform_nernsts=None, channel_density_non_uniform_ghks=None, spike_threshes=None, specific_capacitances=None, init_memb_potentials=None, channel_density_nernst_ca2s=None, **kwargs_)¶

Morphology¶

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_)¶

Standalone element which is usually inside a single cell, but could be outside and referenced by id.

property num_segments¶

Get the number of segments included in this cell morphology.

Returns: number of segments
Return type: int

NamedDimensionalType¶

class neuroml.nml.nml.NamedDimensionalType(name=None, dimension=None, description=None, extensiontype_=None, **kwargs_)¶

NamedDimensionalVariable¶

class neuroml.nml.nml.NamedDimensionalVariable(name=None, dimension=None, description=None, exposure=None, extensiontype_=None, **kwargs_)¶

Network¶

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_)¶

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

get_by_id(id)¶

Get a component by its ID

Parameters: id (str) – ID of component to find
Returns: component with specified ID or None if no component with specified ID found

NeuroMLDocument¶

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_)¶

append(element)¶

Append an element

Parameters: element (Object) – element to append

get_by_id(id)¶

Get a component by specifying its ID.

Parameters: id (str) – id of Component to get
Returns: Component with given ID or None if no Component with provided ID was found

summary(show_includes=True, show_non_network=True)¶

Get a pretty-printed summary of the complete NeuroMLDocument.

This includes information on the various Components included in the NeuroMLDocument: networks, cells, projections, synapses, and so on.

OpenState¶

class neuroml.nml.nml.OpenState(neuro_lex_id=None, id=None, **kwargs_)¶

Parameter¶

class neuroml.nml.nml.Parameter(name=None, dimension=None, description=None, **kwargs_)¶

Path¶

class neuroml.nml.nml.Path(from_=None, to=None, **kwargs_)¶

PinskyRinzelCA3Cell¶

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_)¶

PlasticityMechanism¶

class neuroml.nml.nml.PlasticityMechanism(type=None, init_release_prob=None, tau_rec=None, tau_fac=None, **kwargs_)¶

Point3DWithDiam¶

class neuroml.nml.nml.Point3DWithDiam(x=None, y=None, z=None, diameter=None, **kwargs_)¶

A 3D point with diameter.

distance_to(other_3d_point)¶

Find the distance between this point and another.

Parameters: other_3d_point (Point3DWithDiam) – other 3D point to calculate distance to
Returns: distance between the two points
Return type: float

PoissonFiringSynapse¶

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_)¶

Population¶

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_)¶

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

get_size()¶

Projection¶

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_)¶

Projection (set of synaptic connections) between two populations. Chemical/event based synaptic transmission

exportHdf5(h5file, h5Group)¶: Export to HDF5 file.

Property¶

class neuroml.nml.nml.Property(tag=None, value=None, **kwargs_)¶: Generic property with a tag and value

ProximalDetails¶

class neuroml.nml.nml.ProximalDetails(translation_start=None, **kwargs_)¶

PulseGenerator¶

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_)¶: Generates a constant current pulse of a certain amplitude (with dimensions for current) for a specified duration after a delay.

PulseGeneratorDL¶

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_)¶: Generates a constant current pulse of a certain amplitude (non dimensional) for a specified duration after a delay.

Q10ConductanceScaling¶

class neuroml.nml.nml.Q10ConductanceScaling(q10_factor=None, experimental_temp=None, **kwargs_)¶

Q10Settings¶

class neuroml.nml.nml.Q10Settings(type=None, fixed_q10=None, q10_factor=None, experimental_temp=None, **kwargs_)¶

RampGenerator¶

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_)¶

RampGeneratorDL¶

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_)¶

RandomLayout¶

class neuroml.nml.nml.RandomLayout(number=None, regions=None, **kwargs_)¶

ReactionScheme¶

class neuroml.nml.nml.ReactionScheme(neuro_lex_id=None, id=None, source=None, type=None, anytypeobjs_=None, **kwargs_)¶

Region¶

class neuroml.nml.nml.Region(neuro_lex_id=None, id=None, spaces=None, anytypeobjs_=None, **kwargs_)¶

Requirement¶

class neuroml.nml.nml.Requirement(name=None, dimension=None, description=None, **kwargs_)¶

Resistivity¶

class neuroml.nml.nml.Resistivity(value=None, segment_groups='all', **kwargs_)¶

The resistivity, or specific axial resistance, of the cytoplasm

validate_Nml2Quantity_resistivity(value)¶

validate_Nml2Quantity_resistivity_patterns_ = [['^-?([0-9]*(\\.[0-9]+)?)([eE]-?[0-9]+)?[\\s]*(ohm_cm|kohm_cm|ohm_m)$']]¶

ReverseTransition¶

class neuroml.nml.nml.ReverseTransition(neuro_lex_id=None, id=None, from_=None, to=None, anytypeobjs_=None, **kwargs_)¶

Segment¶

class neuroml.nml.nml.Segment(neuro_lex_id=None, id=None, name=None, parent=None, proximal=None, distal=None, **kwargs_)¶

property length¶

Get the length of the segment.

Returns: length of the segment
Return type: float

property surface_area¶

Get the surface area of the segment.

Returns: surface area of segment
Return type: float

property volume¶

Get the volume of the segment.

Returns: volume of segment
Return type: float

SegmentEndPoint¶

class neuroml.nml.nml.SegmentEndPoint(segments=None, **kwargs_)¶

SegmentGroup¶

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_)¶

SegmentParent¶

class neuroml.nml.nml.SegmentParent(segments=None, fraction_along='1', **kwargs_)¶

SilentSynapse¶

class neuroml.nml.nml.SilentSynapse(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, **kwargs_)¶: Dummy synapse which emits no current. Used as presynaptic endpoint for analog synaptic connection (continuousConnection).

SineGenerator¶

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_)¶

SineGeneratorDL¶

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_)¶

Space¶

class neuroml.nml.nml.Space(neuro_lex_id=None, id=None, based_on=None, structure=None, **kwargs_)¶

SpaceStructure¶

class neuroml.nml.nml.SpaceStructure(x_spacing=None, y_spacing=None, z_spacing=None, x_start=0, y_start=0, z_start=0, **kwargs_)¶

Species¶

class neuroml.nml.nml.Species(id=None, concentration_model=None, ion=None, initial_concentration=None, initial_ext_concentration=None, segment_groups='all', **kwargs_)¶: 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.

SpecificCapacitance¶

class neuroml.nml.nml.SpecificCapacitance(value=None, segment_groups='all', **kwargs_)¶: Capacitance per unit area

Spike¶

class neuroml.nml.nml.Spike(neuro_lex_id=None, id=None, time=None, **kwargs_)¶

SpikeArray¶

class neuroml.nml.nml.SpikeArray(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, spikes=None, **kwargs_)¶

SpikeGenerator¶

class neuroml.nml.nml.SpikeGenerator(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, period=None, **kwargs_)¶

SpikeGeneratorPoisson¶

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_)¶

SpikeGeneratorRandom¶

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_)¶

SpikeGeneratorRefPoisson¶

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_)¶

SpikeSourcePoisson¶

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_)¶

SpikeThresh¶

class neuroml.nml.nml.SpikeThresh(value=None, segment_groups='all', **kwargs_)¶: Membrane potential at which to emit a spiking event. Note, usually the spiking event will not be emitted again until the membrane potential has fallen below this value and rises again to cross it in a positive direction.

Standalone¶

class neuroml.nml.nml.Standalone(neuro_lex_id=None, id=None, metaid=None, notes=None, properties=None, annotation=None, extensiontype_=None, **kwargs_)¶: Elements which can stand alone and be referenced by id, e.g. cell, morphology.

StateVariable¶

class neuroml.nml.nml.StateVariable(name=None, dimension=None, description=None, exposure=None, **kwargs_)¶

SubTree¶

class neuroml.nml.nml.SubTree(from_=None, to=None, **kwargs_)¶

SynapticConnection¶

class neuroml.nml.nml.SynapticConnection(from_=None, to=None, synapse=None, destination=None, **kwargs_)¶: Single explicit connection. Introduced to test connections in LEMS. Will probably be removed in favour of connections wrapped in projection element

TauInfTransition¶

class neuroml.nml.nml.TauInfTransition(neuro_lex_id=None, id=None, from_=None, to=None, steady_state=None, time_course=None, **kwargs_)¶

TimeDerivative¶

class neuroml.nml.nml.TimeDerivative(variable=None, value=None, **kwargs_)¶

TimedSynapticInput¶

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_)¶

TransientPoissonFiringSynapse¶

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_)¶

UnstructuredLayout¶

class neuroml.nml.nml.UnstructuredLayout(number=None, **kwargs_)¶

VariableParameter¶

class neuroml.nml.nml.VariableParameter(parameter=None, segment_groups=None, inhomogeneous_value=None, **kwargs_)¶

VoltageClamp¶

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_)¶

VoltageClampTriple¶

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_)¶

basePyNNCell¶

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_)¶

basePyNNIaFCell¶

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_)¶

basePyNNIaFCondCell¶

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_)¶

API documentation

loaders Module

nml Module (NeuroML Core classes)¶

List of Component classes¶

AdExIaFCell¶

AlphaCondSynapse¶

AlphaCurrSynapse¶

AlphaCurrentSynapse¶

AlphaSynapse¶

Annotation¶

Base¶

BaseCell¶

BaseCellMembPotCap¶

BaseConductanceBasedSynapse¶

BaseConductanceBasedSynapseTwo¶

BaseConnection¶

BaseConnectionNewFormat¶

BaseConnectionOldFormat¶

BaseCurrentBasedSynapse¶

BaseNonNegativeIntegerId¶

BaseProjection¶

BasePynnSynapse¶

BaseSynapse¶

BaseVoltageDepSynapse¶

BaseWithoutId¶

BiophysicalProperties¶

BiophysicalProperties2CaPools¶

BlockMechanism¶

BlockingPlasticSynapse¶

Case¶

Cell¶

Cell2CaPools¶

CellSet¶

ChannelDensity¶

ChannelDensityGHK¶

ChannelDensityGHK2¶

ChannelDensityNernst¶

ChannelDensityNernstCa2¶

ChannelDensityNonUniform¶

ChannelDensityNonUniformGHK¶

ChannelDensityNonUniformNernst¶

ChannelDensityVShift¶

ChannelPopulation¶

ClosedState¶

ComponentType¶

CompoundInput¶

CompoundInputDL¶

ConcentrationModel_D¶

ConditionalDerivedVariable¶

Connection¶

ConnectionWD¶

Constant¶

ContinuousConnection¶

ContinuousConnectionInstance¶

ContinuousConnectionInstanceW¶

ContinuousProjection¶

DecayingPoolConcentrationModel¶

DerivedVariable¶

DistalDetails¶

DoubleSynapse¶

Dynamics¶

EIF_cond_alpha_isfa_ista¶

EIF_cond_exp_isfa_ista¶

ElectricalConnection¶

ElectricalConnectionInstance¶

ElectricalConnectionInstanceW¶

ElectricalProjection¶

ExpCondSynapse¶

ExpCurrSynapse¶

ExpOneSynapse¶

ExpThreeSynapse¶

ExpTwoSynapse¶

ExplicitInput¶

Exposure¶

ExtracellularProperties¶

ExtracellularPropertiesLocal¶

FitzHughNagumo1969Cell¶

FitzHughNagumoCell¶

FixedFactorConcentrationModel¶

ForwardTransition¶

GapJunction¶

GateFractional¶

`nml` Module (NeuroML Core classes)¶