Uses of Class
org.neuroml.model.Standalone

Packages that use Standalone

Package	Description
org.neuroml.model
org.neuroml.model.util

Uses of Standalone in org.neuroml.model

Subclasses of Standalone in org.neuroml.model

Modifier and Type	Class	Description
class	AdExIaFCell	Model based on Brette R and Gerstner W ( 2005 ) Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity.
class	AlphaCondSynapse	Alpha synapse: rise time and decay time are both tau_syn.
class	AlphaCurrentSynapse	Alpha current synapse: rise time and decay time are both **tau.** \n :param tau: Time course for rise and decay :type tau: time :param ibase: Baseline current increase after receiving a spike :type ibase: current
class	AlphaCurrSynapse	Alpha synapse: rise time and decay time are both tau_syn.
class	AlphaSynapse	Ohmic synapse model where rise time and decay time are both **tau.** Max conductance reached during this time ( assuming zero conductance before ) is **gbase** * **weight.** \n :param tau: Time course of rise/decay :type tau: time :param gbase: Baseline conductance, generally the maximum conductance following a single spike :type gbase: conductance :param erev: Reversal potential of the synapse :type erev: voltage
class	BaseCell	Base type of any cell ( e.
class	BaseCellMembPotCap	Any cell with a membrane potential **v** with voltage units and a membrane capacitance **C.** Also defines exposed value **iSyn** for current due to external synapses and **iMemb** for total transmembrane current ( usually channel currents plus **iSyn** ) \n :param C: Total capacitance of the cell membrane :type C: capacitance
class	BaseConductanceBasedSynapse	Synapse model which exposes a conductance **g** in addition to producing a current.
class	BaseConductanceBasedSynapseTwo	Synapse model suited for a sum of two expTwoSynapses which exposes a conductance **g** in addition to producing a current.
class	BaseCurrentBasedSynapse	Synapse model which produces a synaptic current.
class	BasePyNNCell	Base type of any PyNN standard cell model.
class	BasePyNNIaFCell	Base type of any PyNN standard integrate and fire model \n :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	BasePyNNIaFCondCell	Base type of conductance based PyNN IaF cell models \n :param e_rev_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_E: none :param e_rev_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_I: none :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	BasePynnSynapse	Base type for all PyNN synapses.
class	BaseSynapse	Base type for all synapses, i.
class	BaseVoltageDepSynapse	Base type for synapses with a dependence on membrane potential
class	BiophysicalProperties	The biophysical properties of the **cell** , including the **membraneProperties** and the **intracellularProperties**
class	BiophysicalProperties2CaPools	The biophysical properties of the **cell** , including the **membraneProperties2CaPools** and the **intracellularProperties2CaPools** for a cell with two Ca pools
class	BlockingPlasticSynapse	Biexponential synapse that allows for optional block and plasticity mechanisms, which can be expressed as child elements.
class	Cell	Cell with **segment** s specified in a **morphology** element along with details on its **biophysicalProperties** .
class	Cell2CaPools	Variant of cell with two independent Ca2+ pools.
class	CompoundInput	Generates a current which is the sum of all its child **basePointCurrent** element, e.
class	CompoundInputDL	Generates a current which is the sum of all its child **basePointCurrentDL** elements, e.
class	ConcentrationModelD	Java class for ConcentrationModel_D complex type.
class	DecayingPoolConcentrationModel	Model of an intracellular buffering mechanism for **ion** ( currently hard Coded to be calcium, due to requirement for **iCa** ) which has a baseline level **restingConc** and tends to this value with time course **decayConstant.** The ion is assumed to occupy a shell inside the membrane of thickness **shellThickness.** \n :param restingConc: :type restingConc: concentration :param decayConstant: :type decayConstant: time :param shellThickness: :type shellThickness: length
class	DoubleSynapse	Synapse consisting of two independent synaptic mechanisms ( e.
class	EIFCondAlphaIsfaIsta	Adaptive exponential integrate and fire neuron according to Brette R and Gerstner W ( 2005 ) with alpha-function-shaped post-synaptic conductance \n :param v_spike: :type v_spike: none :param delta_T: :type delta_T: none :param tau_w: :type tau_w: none :param a: :type a: none :param b: :type b: none :param e_rev_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_E: none :param e_rev_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_I: none :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	EIFCondExpIsfaIsta	Adaptive exponential integrate and fire neuron according to Brette R and Gerstner W ( 2005 ) with exponentially-decaying post-synaptic conductance \n :param v_spike: :type v_spike: none :param delta_T: :type delta_T: none :param tau_w: :type tau_w: none :param a: :type a: none :param b: :type b: none :param e_rev_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_E: none :param e_rev_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_I: none :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	ExpCondSynapse	Conductance based synapse with instantaneous rise and single exponential decay ( with time constant tau_syn ) \n :param e_rev: :type e_rev: none :param tau_syn: :type tau_syn: none
class	ExpCurrSynapse	Current based synapse with instantaneous rise and single exponential decay ( with time constant tau_syn ) \n :param tau_syn: :type tau_syn: none
class	ExpOneSynapse	Ohmic synapse model whose conductance rises instantaneously by ( **gbase** * **weight** ) on receiving an event, and which decays exponentially to zero with time course **tauDecay** \n :param tauDecay: Time course of decay :type tauDecay: time :param gbase: Baseline conductance, generally the maximum conductance following a single spike :type gbase: conductance :param erev: Reversal potential of the synapse :type erev: voltage
class	ExpThreeSynapse	Ohmic synapse similar to expTwoSynapse but consisting of two components that can differ in decay times and max conductances but share the same rise time.
class	ExpTwoSynapse	Ohmic synapse model whose conductance waveform on receiving an event has a rise time of **tauRise** and a decay time of **tauDecay.** Max conductance reached during this time ( assuming zero conductance before ) is **gbase** * **weight.** \n :param tauRise: :type tauRise: time :param tauDecay: :type tauDecay: time :param gbase: Baseline conductance, generally the maximum conductance following a single spike :type gbase: conductance :param erev: Reversal potential of the synapse :type erev: voltage
class	FitzHughNagumo1969Cell	The Fitzhugh Nagumo model is a two-dimensional simplification of the Hodgkin-Huxley model of spike generation in squid giant axons.
class	FitzHughNagumoCell	Simple dimensionless model of spiking cell from FitzHugh and Nagumo.
class	FixedFactorConcentrationModel	Model of buffering of concentration of an ion ( currently hard coded to be calcium, due to requirement for **iCa** ) which has a baseline level **restingConc** and tends to this value with time course **decayConstant.** A fixed factor **rho** is used to scale the incoming current *independently of the size of the compartment* to produce a concentration change.
class	GapJunction	Gap junction/single electrical connection \n :param conductance: :type conductance: conductance
class	GradedSynapse	Graded/analog synapse.
class	HHCondExp	Single-compartment Hodgkin-Huxley-type neuron with transient sodium and delayed-rectifier potassium currents using the ion channel models from Traub.
class	HindmarshRose1984Cell	The Hindmarsh Rose model is a simplified point cell model which captures complex firing patterns of single neurons, such as periodic and chaotic bursting.
class	IafCell	Integrate and fire cell with capacitance **C,** **leakConductance** and **leakReversal** \n :param leakConductance: :type leakConductance: conductance :param leakReversal: :type leakReversal: voltage :param thresh: :type thresh: voltage :param reset: :type reset: voltage :param C: Total capacitance of the cell membrane :type C: capacitance
class	IafRefCell	Integrate and fire cell with capacitance **C,** **leakConductance,** **leakReversal** and refractory period **refract** \n :param refract: :type refract: time :param leakConductance: :type leakConductance: conductance :param leakReversal: :type leakReversal: voltage :param thresh: :type thresh: voltage :param reset: :type reset: voltage :param C: Total capacitance of the cell membrane :type C: capacitance
class	IafTauCell	Integrate and fire cell which returns to its leak reversal potential of **leakReversal** with a time constant **tau** \n :param leakReversal: :type leakReversal: voltage :param tau: :type tau: time :param thresh: The membrane potential at which to emit a spiking event and reset voltage :type thresh: voltage :param reset: The value the membrane potential is reset to on spiking :type reset: voltage
class	IafTauRefCell	Integrate and fire cell which returns to its leak reversal potential of **leakReversal** with a time course **tau.** It has a refractory period of **refract** after spiking \n :param refract: :type refract: time :param leakReversal: :type leakReversal: voltage :param tau: :type tau: time :param thresh: The membrane potential at which to emit a spiking event and reset voltage :type thresh: voltage :param reset: The value the membrane potential is reset to on spiking :type reset: voltage
class	IFCondAlpha	Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic conductance \n :param e_rev_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_E: none :param e_rev_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_I: none :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	IFCondExp	Leaky integrate and fire model with fixed threshold and exponentially-decaying post-synaptic conductance \n :param e_rev_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_E: none :param e_rev_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type e_rev_I: none :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	IFCurrAlpha	Leaky integrate and fire model with fixed threshold and alpha-function-shaped post-synaptic current \n :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	IFCurrExp	Leaky integrate and fire model with fixed threshold and decaying-exponential post-synaptic current \n :param tau_refrac: :type tau_refrac: none :param v_thresh: :type v_thresh: none :param tau_m: :type tau_m: none :param v_rest: :type v_rest: none :param v_reset: :type v_reset: none :param cm: :type cm: none :param i_offset: :type i_offset: none :param tau_syn_E: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_E: none :param tau_syn_I: This parameter is never used in the NeuroML2 description of this cell! Any synapse producing a current can be placed on this cell :type tau_syn_I: none :param v_init: :type v_init: none
class	IonChannel	Note **ionChannel** and **ionChannelHH** are currently functionally identical.
class	IonChannelHH	Note **ionChannel** and **ionChannelHH** are currently functionally identical.
class	IonChannelKS	A kinetic scheme based ion channel with multiple **gateKS** s, each of which consists of multiple **KSState** s and **KSTransition** s giving the rates of transition between them \n :param conductance: :type conductance: conductance
class	IonChannelScalable	Java class for IonChannelScalable complex type.
class	IonChannelVShift	Same as **ionChannel** , but with a **vShift** parameter to change voltage activation of gates.
class	Izhikevich2007Cell	Cell based on the modified Izhikevich model in Izhikevich 2007, Dynamical systems in neuroscience, MIT Press \n :param v0: Initial membrane potential :type v0: voltage :param k: :type k: conductance_per_voltage :param vr: Resting membrane potential :type vr: voltage :param vt: Spike threshold :type vt: voltage :param vpeak: Peak action potential value :type vpeak: voltage :param a: Time scale of recovery variable u :type a: per_time :param b: Sensitivity of recovery variable u to subthreshold fluctuations of membrane potential v :type b: conductance :param c: After-spike reset value of v :type c: voltage :param d: After-spike increase to u :type d: current :param C: Total capacitance of the cell membrane :type C: capacitance
class	IzhikevichCell	Cell based on the 2003 model of Izhikevich, see http://izhikevich.org/publications/spikes.htm \n :param v0: Initial membrane potential :type v0: voltage :param a: Time scale of the recovery variable U :type a: none :param b: Sensitivity of U to the subthreshold fluctuations of the membrane potential V :type b: none :param c: After-spike reset value of V :type c: none :param d: After-spike increase to U :type d: none :param thresh: Spike threshold :type thresh: voltage
class	LinearGradedSynapse	Behaves just like a one way gap junction.
class	Morphology	The collection of **segment** s which specify the 3D structure of the cell, along with a number of **segmentGroup** s
class	Network	Network containing: **population** s ( potentially of type **populationList** , and so specifying a list of cell **location** s ); **projection** s ( with lists of **connection** s ) and/or **explicitConnection** s; and **inputList** s ( with lists of **input** s ) and/or **explicitInput** s.
class	NeuroMLDocument	Java class for NeuroMLDocument complex type.
class	PinskyRinzelCA3Cell	Reduced CA3 cell model from Pinsky, P.
class	PoissonFiringSynapse	Poisson spike generator firing at **averageRate,** which is connected to single **synapse** that is triggered every time a spike is generated, producing an input current.
class	Population	A population of components, with just one parameter for the **size,** i.
class	PulseGenerator	Generates a constant current pulse of a certain **amplitude** for a specified **duration** after a **delay.** Scaled by **weight,** if set \n :param delay: Delay before change in current.
class	PulseGeneratorDL	Dimensionless equivalent of **pulseGenerator** .
class	RampGenerator	Generates a ramping current after a time **delay,** for a fixed **duration.** During this time the current steadily changes from **startAmplitude** to **finishAmplitude.** Scaled by **weight,** if set \n :param delay: Delay before change in current.
class	RampGeneratorDL	Dimensionless equivalent of **rampGenerator** .
class	SilentSynapse	Dummy synapse which emits no current.
class	SineGenerator	Generates a sinusoidally varying current after a time **delay,** for a fixed **duration.** The **period** and maximum **amplitude** of the current can be set as well as the **phase** at which to start.
class	SineGeneratorDL	Dimensionless equivalent of **sineGenerator** .
class	SpikeArray	Set of spike ComponentTypes, each emitting one spike at a certain time.
class	SpikeGenerator	Simple generator of spikes at a regular interval set by **period** \n :param period: Time between spikes.
class	SpikeGeneratorPoisson	Generator of spikes whose ISI is distributed according to an exponential PDF with scale: 1 / **averageRate** \n :param averageRate: The average rate at which spikes are emitted :type averageRate: per_time
class	SpikeGeneratorRandom	Generator of spikes with a random interspike interval of at least **minISI** and at most **maxISI** \n :param maxISI: Maximum interspike interval :type maxISI: time :param minISI: Minimum interspike interval :type minISI: time
class	SpikeGeneratorRefPoisson	Generator of spikes whose ISI distribution is the maximum entropy distribution over [ **minimumISI,** +infinity ) with mean: 1 / **averageRate** \n :param minimumISI: The minimum interspike interval :type minimumISI: time :param averageRate: The average rate at which spikes are emitted :type averageRate: per_time
class	SpikeSourcePoisson	Spike source, generating spikes according to a Poisson process.
class	TimedSynapticInput	Spike array connected to a single **synapse,** producing a current triggered by each **spike** in the array.
class	TransientPoissonFiringSynapse	Poisson spike generator firing at **averageRate** after a **delay** and for a **duration,** connected to single **synapse** that is triggered every time a spike is generated, providing an input current.
class	VoltageClamp	Voltage clamp.
class	VoltageClampTriple	Voltage clamp with 3 clamp levels.

Methods in org.neuroml.model that return Standalone

Modifier and Type	Method	Description
Standalone	ObjectFactory.createStandalone()	Create an instance of Standalone

Uses of Standalone in org.neuroml.model.util

Methods in org.neuroml.model.util that return types with arguments of type Standalone

Modifier and Type	Method	Description
static LinkedHashMap<String,Standalone>	NeuroMLConverter.getAllStandaloneElements(NeuroMLDocument nmlDocument)

Methods in org.neuroml.model.util with parameters of type Standalone

Modifier and Type	Method	Description
static void	NeuroMLConverter.addElementToDocument(NeuroMLDocument nmlDocument, Standalone nmlElement)