Birgit Kriener
Erik De Schutter
Fahim T. Imam
INCF MultiScale Modeling Task Force
Lars Schwabe
Padraig Gleeson
Sean Hill
Stephen D. Larson
Subhasis Ray
Yann Le Franc
13/03/2012
An ontology to describe the field of Computational Neurosciences
Computational Neuroscience Ontology
Dave Beckett
Nikki Rogers
Participants in W3C's Semantic Web Deployment Working Group.
Alistair Miles
Sean Bechhofer
An RDF vocabulary for describing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept schemes embedded in glossaries and terminologies.
SKOS Vocabulary
This ontology is used to add the Definition class of annotation as in NIF.
The source of the definition can be defined with class from OBO-annotation
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA.
version 0.5
The range of skos:altLabel is the class of RDF plain literals.
skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise disjoint properties.
alternative label
An alternative lexical label for a resource.
Acronyms, abbreviations, spelling variants, and irregular plural/singular forms may be included among the alternative labels for a concept. Mis-spelled terms are normally included as hidden labels (see skos:hiddenLabel).
change note
A note about a modification to a concept.
definition
A statement or formal explanation of the meaning of a concept.
editorial note
A note for an editor, translator or maintainer of the vocabulary.
example
An example of the use of a concept.
The range of skos:hiddenLabel is the class of RDF plain literals.
skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise disjoint properties.
hidden label
A lexical label for a resource that should be hidden when generating visual displays of the resource, but should still be accessible to free text search operations.
history note
A note about the past state/use/meaning of a concept.
note
A general note, for any purpose.
This property may be used directly, or as a super-property for more specific note types.
A resource has no more than one value of skos:prefLabel per language tag, and no more than one value of skos:prefLabel without language tag.
The range of skos:prefLabel is the class of RDF plain literals.
skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise
disjoint properties.
preferred label
The preferred lexical label for a resource, in a given language.
scope note
A note that helps to clarify the meaning and/or the use of a concept.
has broader match
skos:broadMatch is used to state a hierarchical mapping link between two conceptual resources in different concept schemes.
Broader concepts are typically rendered as parents in a concept hierarchy (tree).
has broader
Relates a concept to a concept that is more general in meaning.
By convention, skos:broader is only used to assert an immediate (i.e. direct) hierarchical link between two conceptual resources.
has broader transitive
skos:broaderTransitive is a transitive superproperty of skos:broader.
By convention, skos:broaderTransitive is not used to make assertions. Rather, the properties can be used to draw inferences about the transitive closure of the hierarchical relation, which is useful e.g. when implementing a simple query expansion algorithm in a search application.
has close match
skos:closeMatch is used to link two concepts that are sufficiently similar that they can be used interchangeably in some information retrieval applications. In order to avoid the possibility of "compound errors" when combining mappings across more than two concept schemes, skos:closeMatch is not declared to be a transitive property.
skos:exactMatch is disjoint with each of the properties skos:broadMatch and skos:relatedMatch.
has exact match
skos:exactMatch is used to link two concepts, indicating a high degree of confidence that the concepts can be used interchangeably across a wide range of information retrieval applications. skos:exactMatch is a transitive property, and is a sub-property of skos:closeMatch.
has top concept
Relates, by convention, a concept scheme to a concept which is topmost in the broader/narrower concept hierarchies for that scheme, providing an entry point to these hierarchies.
is in scheme
Relates a resource (for example a concept) to a concept scheme in which it is included.
A concept may be a member of more than one concept scheme.
These concept mapping relations mirror semantic relations, and the data model defined below is similar (with the exception of skos:exactMatch) to the data model defined for semantic relations. A distinct vocabulary is provided for concept mapping relations, to provide a convenient way to differentiate links within a concept scheme from links between concept schemes. However, this pattern of usage is not a formal requirement of the SKOS data model, and relies on informal definitions of best practice.
is in mapping relation with
Relates two concepts coming, by convention, from different schemes, and that have comparable meanings
has member
Relates a collection to one of its members.
For any resource, every item in the list given as the value of the
skos:memberList property is also a value of the skos:member property.
has member list
Relates an ordered collection to the RDF list containing its members.
has narrower match
skos:narrowMatch is used to state a hierarchical mapping link between two conceptual resources in different concept schemes.
Narrower concepts are typically rendered as children in a concept hierarchy (tree).
has narrower
Relates a concept to a concept that is more specific in meaning.
By convention, skos:broader is only used to assert an immediate (i.e. direct) hierarchical link between two conceptual resources.
has narrower transitive
skos:narrowerTransitive is a transitive superproperty of skos:narrower.
By convention, skos:narrowerTransitive is not used to make assertions. Rather, the properties can be used to draw inferences about the transitive closure of the hierarchical relation, which is useful e.g. when implementing a simple query expansion algorithm in a search application.
skos:related is disjoint with skos:broaderTransitive
has related
Relates a concept to a concept with which there is an associative semantic relationship.
has related match
skos:relatedMatch is used to state an associative mapping link between two conceptual resources in different concept schemes.
is in semantic relation with
Links a concept to a concept related by meaning.
This property should not be used directly, but as a super-property for all properties denoting a relationship of meaning between concepts.
is top concept in scheme
Relates a concept to the concept scheme that it is a top level concept of.
name
numerical value
notation
A notation, also known as classification code, is a string of characters such as "T58.5" or "303.4833" used to uniquely identify a concept within the scope of a given concept scheme.
By convention, skos:notation is used with a typed literal in the object position of the triple.
obo_annot:EnumerationClass
IAO:0000030
OBI:0001617
SBO:0000225
SBO:0000254
SBO:0000257
SBO:0000258
SBO:0000259
SBO:0000346
SBO:0000347
SBO:0000348
SBO:0000465
cno_0000001
This general class includes the most common types of models classified based on the level of description of the nervous system.
definition based on the following NCI thesaurus entry: http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#Type_of_Event
defined model type
defined type of model
a generically_dependent_continuant that is a category of models regarded as sharing particular characteristics, qualities, and/or defined similarities.
cno_0000002
This class is based on the assumption that models can represented as particular assemblies of components that can be either specific to the different level of description (cellular, synaptic and network) or generic.
definition based on element from NCI Thesaurus: http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#Element_Part
model component
model element
a generically dependent continuant that is a constituent part of a model
cno_0000003
parameter
elementary model component role that defines an elementary model component as constant value determining the characteristics or behaviour of the model
cno_0000004
reset potential
value of the membrane potential at which the model is maintained after the emission of a spike.
cno_0000005
SBO:0000565
http://en.wikipedia.org/wiki/Physical_constant
physical constant
A physical constant that is required in the calculation of a system parameter
cno_0000007
http://www.scholarpedia.org/article/Models_of_synaptic_plasticity
http://www.scholarpedia.org/article/Models_of_synaptic_plasticity
phenomenological plasticity model
long term plasticity model that is based on an input-output relationship between neuronal activity and synaptic plasticity. This type of model does not explicitly account for the biochemistry and physiology leading to synaptic plasticity.
cno_0000008
The distinction between the different subclasses is based on the different "spiking mechanisms".
cellular model
a defined type of model that represent the biological activities of a cell.
cno_0000009
synapse model
a defined type of model that represents the biological processes involved in synaptic transmission
cno_0000010
network model
a defined type of model that represents biological neural networks.
cno_0000011
plasticity model
a defined type of model that describes the mechanisms underlying the plasticity of the nervous system.
cno_0000012
This class can be further subdivided into binary neuron, McCullogh neurons and all variants of the artificial neuron models.
artificial neuron model
a cellular model that represents the electrical activity of a nerve cell with simplified function
cno_0000013
point process model
a cellular model that reproduce particular features of real neuron spiking patterns with statistical point process models.
cno_0000014
spiking model
a cellular model that describes the mechanism of action potential emission in biological nerve cell.
cno_0000015
PMID: 10809012
balanced random network
defined model that corresponds to a network of sparsely connected excitatory and inhibitory neurons which can switch between firing states depending on the balance between excitation and inhibition.
cno_0000016
http://en.wikipedia.org/wiki/Hopfield_network
Hopfield network
defined model that is a form of recurrent artificial neural network invented by John Hopfield.
cno_0000017
biophysical spiking model
a spiking model that describe the interactions between the ionic conductances that participates to the generation of an action potential
cno_0000018
threshold-based spiking model
a spiking model that represents the spiking mechanism as the result of a threshold crossing.
cno_0000019
This class could become a superclass called dynamical models or dynamical system models in contrast with biophysical and threshold based models.
It should contain models like Fitzhugh-Nagumo, Morris-Lecar models.
reduced model
biophysical model that is obtained by dimensionality reduction of a detailed model.
cno_0000020
detailed model
biophysical model that describes in detail the conductance variations of the ionic currents responsible of the generation of an action potential
cno_0000021
conductance-based model
This classe refers to detailed integrate-and-fire models as described in Destexhe A. (1997, PMID: 9097470) and Hill S. and Tononi G. (2005, PMID: 15537811)
pulse-based model
a threshold based spiking neuron model that is an hybrid between Hodgkin and Huxley and integrate-and-fire models. The model describes the impact of fast sodium and delayed rectifier potassium conductances on the subthreshold membrane voltage dynamic and considers action potentials as pulses during which the sodium and potassium conductances are set to particular values representing their participation to the generation and repolarization of the action potential.
cno_0000022
one variable model
a threshold-based model that uses only one variable to describe the nerve cells behavior.
cno_0000023
two variable model
a threshold-based model that uses two variables to describe the nerve cells behavior.
cno_0000024
three variable model
a threshold-based model that uses three variables to describe the nerve cells behavior
cno_0000025
spike response model
a threshold-based model that correspond to a generalization of the leaky integrate-and-fire model and give a simple description of action potential generation in neurons
cno_0000026
current-based model
a model of chemical synapse that consider the impact of the chemical release as a current source in the post-synaptic model with the postsynaptic membrane voltage considered to be constant.
cno_0000027
conductance-based model
a model of chemical synapse that consider the impact of the chemical release as a modification of conductance in the post-synaptic model with the post-synaptic potential varying over time.
cno_0000028
rate model
network model composed of rate-based neuron models
cno_0000029
corresponds to Kohonen maps, Multiple Layer perceptron, ...
artificial neural network model
network model composed of artificial neuron models.
cno_0000030
spiking network model
network model that is composed of spiking neuron models.
cno_0000031
chemical synapse model
a synapse model that describes the impact of chemical compounds released by the synapse
cno_0000032
electrical synapse model
a synapse model that describe synapses transmitting directly ionic currents.
cno_0000033
This class would contains models that describes the link between potassium channels and NMDA activation as described in hippocampus for instance.
cellular plasticity model
plasticity model that describes the variations of the cellular intrinsic excitability due to regulation of ionic conductances depending on the network activity.
cno_0000034
synaptic plasticity model
synaptic plasticity rule
model of plasticity that represents the mechanisms underlying changes in synaptic transmission, depending on the network or cellular activity.
cno_0000035
short term facilitation model
a model of short term synaptic plasticity that represents the increase of the synaptic efficacy for a short period of time.
cno_0000036
cellular model component
aggregated model composed that is used to build cellular models
cno_0000037
synapse model component
aggregated model component that is used to build synaptic models.
cno_0000038
resting membrane potential
value of the neuronal membrane potential at rest
cno_0000039
This is a general term that encompass the refractory period usually defined with a time constant and the resetting of the membrane potential during the refractory period.
refractory mechanism
a cellular model component that represents the mechanism by which the model is kept unresponsive to any stimulus after the emission of an action potential.
cno_0000040
model quality
quality that represents a qualitative feature of the model that can be either independent of the model specification or a property resulting of the particular model specification
cno_0000041
spiking mechanism
a cellular model component that represents the mechanisms generating action potential in a cellular model type.
cno_0000042
morphology
a cellular model component that represents the morphology of the model
cno_0000043
intracellular dynamic
a cellular model component that represents a chemical signaling occuring inside the nerve cell
cno_0000044
stimulation current
current model that represents input currents provided to the model via an electrode (intracellular or extracellular).
cno_0000045
generic model component
cno_0000046
probabilistic component
a generic model component that represents the probabilistic variations of any model component.
cno_0000047
ionic current model
a current model that describes the flow of ions through cellular membrane.
cno_0000048
synaptic current
current model that represents the flow of ions triggered by the activation of a chemical or electrical synapse model.
cno_0000049
abstract current model
a current model that is an abtraction of complex current interactions and which is used to reproduce a particular cellular behavior such as rebound or adaptation.
cno_0000050
continuous
a spiking mechanism that considers the action potential initiation as a continuous process often based on the non linearity of the conductance changes supporting the initiation of an action potential. This mechanism is the opposite of a threshold-based mechanisms.
cno_0000051
threshold-based
a spiking mechanism that considers the action potential initiation as a result of a thresholding operation.
cno_0000052
point
a morphology that is used to represents the models without specified geometry.
cno_0000053
single compartment
a morphology that consider the cellular morphology as a unique compartment
cno_0000054
multiple compartment
a morphology that represents the modeled cell with multiple compartments. This morphology spans the models called the Ball-and-stick model and the models based on reconstructed morphologies.
cno_0000055
reconstructed
morphological quality that represents model morphologies build upon the reconstruction of a real nerve cell morphology using imaging techniques such as camera lucida or two-photon imaging.
cno_0000056
calcium dynamic
an intracellular dynamic model component that represents the variation of the intracellular calcium concentration over time.
cno_0000057
NOTE: Shouldn't be separated from calcium dynamic as calcium is also a molecular participant. One possible solution would be to change into: reduced calcium dynamic to represent the simplification of buffering and detailed biochemical reactions that details the calcium buffering!!!
biochemical dynamic
an intracellular dynamic model component that represents the dynamic of the intracellular biochemical reactions and molecular participant concentrations over time.
cno_0000058
network model component
a model component that is used to build network model types.
cno_0000059
non linear spike generation current
abstract current model that represents an additional non-linear current Ïˆ which leads to a divergence of the potential toward infinity in a finite time during the emission of an action potential.
cno_0000060
defined model
a generically_dependent_continuant that represent the set of models commonly used to build other models.
cno_0000061
http://en.wikipedia.org/wiki/Biological_neuron_model#Integrate-and-fire
integrate-and-fire
a defined model that represent the evolution of voltage as the derivative of the law of capacitance. The action potential is emitted when the value of the voltage reaches a threshold and is considered as Dirac function. After the emission the voltage is resetted to the resting potential value.
cno_0000062
http://www.scholarpedia.org/article/Adaptive_exponential_integrate-and-fire_model
AdEx
adaptive exponential integrate-and-fire
a defined model that is a spiking neuron model with two variables. The first equation describes the dynamics of the membrane potential and includes an activation ter with an exponential voltage dependence. Voltage is coupled to a second equation which describes adaptation. Both variables are reset if an action potential has been triggered. This model has been introduced by Brette and Gerstner in 2005.
cno_0000063
http://en.wikipedia.org/wiki/Variable_(mathematics)
independent variable
variable regarded as inputs to a system and may take on different values freely
cno_0000064
http://en.wikipedia.org/wiki/Variable_(mathematics)
dependent variable
variable regarded as values that change as a consequence of changes in other values in the system.
cno_0000065
w.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1001056
EIF
exponential integrate-and-fire
a defined model that is an integrate-and-fire model in which the action potentials are generated by an exponential current instead of a fixed threshold. The exponential integrate-and-fire model is defined in Fourcaud-Trocme and al. 2003
cno_0000066
http://en.wikipedia.org/wiki/Biological_neuron_model#Leaky_integrate-and-fire
LIF, Lapicque's model
leaky integrate-and-fire
a defined model that is an integrate-and-fire model with a leak component added to the membrane potential, reflecting the diffusion of ions that occurs through the membrane when some equilibrium is not reached in the cell.
cno_0000067
QIF
quadratic integrate-and-fire
a defined model that is an integrate-and-fire model in which the action potentials are generated by a quadratic current instead of a fixed threshold. The quadratic integrate-and-fire model is defined in Latham and al. 2000. This model is identical to the Theta neuron proposed by Ermentrout and Kopell (1986) with a variable change.
cno_0000068
http://en.wikipedia.org/wiki/Theta_model
theta neuron model
a defined model that is well suited to describe the processes involving rapid changes in membrane potential, known as bursts. The theta model describes parabolic bursting and has been defined in Ermentrout and Kopell, SIAM journal of Applied Mathematics 1986.
cno_0000069
ALIF
adaptive integrate-and-fire
a defined model that is a two-variable integrate-and-fire model. The second variable accounts for the currents involved in spike frequency adaptation. This variable increase transiently during action potentials and decay between action potential.
cno_0000070
PMID: 12611957
GIF
generalized integrate-and-fire
a defined model that is a two variable integrate-and-fire model with a threshold for spike generation and a reset as in the leaky integrate-and-fire model. The two variables represent subthreshold resonance behavior and result from the linearization of the Hodgkin and Huxley equation around a subthreshold holding potential. This model is similar to the resonate-and-fire model proposed by Izhikevich (2001)
cno_0000071
IFB
integrate-and-fire-or-burst
a defined model that is a two-variable integrate-and-fire model. The second variable is a slow variable that represents the inactivation of the low-threshold calcium current. This model reproduces the features of the bursting behavior of thalamo-cortical relay neurons and has been proposed by Smith and al., 2000
cno_0000072
PMID: 18244602
Izhikevich model
a defined model that is a minimal two-variable integrate-and-fire model that reproduces different features depending on the value of 4 parameters. The second variable represents the adaptation. This model has been proposed in Izhikevich, 2003.
cno_0000073
PMID: 11665779
resonate-and-fire
a defined model that is a two variable integrate-and-fire model proposed by Izhikevich in Izhikevich, 2001.
cno_0000074
PMID: 6144106
http://en.wikipedia.org/wiki/Hindmarsh%E2%80%93Rose_model
HindMarch and Rose model
a defined model that is a three-variable model: the membrane potential written in dimensionless unit, the spiking variable that represent the fast transport of sodium and potassium ions and the bursting variable that represent the slow transport of other ions. This model aims to study the spiking-bursting behavior of the membrane potential observed in experiments.
cno_0000075
PMID: 16927211
Rotstein model
a defined model that is three variable reduced model defined in Rotstein and al. 2006 in J. Comp. Neurosci.
cno_0000076
PMID: 20478693
Shinomoto model
a defined model that is a multi-timescale adaptive threshold model of neuronal spiking incorporated into the stochastic framework of the linear-nonlinear Poisson model in the form of a generalized linear model.
cno_0000077
doi:10.1162/neco.1997.9.5.1015
http://icwww.epfl.ch/~gerstner/SPNM/node27.html
http://www.scholarpedia.org/article/Spike-response_model
spike response model
a defined model that is a generalization of the leaky integrate-and-fire model. As in the leaky integrate-and-fire model, action potentials are generated when the voltage passes a threshold. Leaky integrate-and-fire models are formulated using differential equations for the voltage, whereas the Spike Response Model is formulated using filters.
cno_0000078
PMID: 16633938
http://icwww.epfl.ch/~gerstner/SPNM/node27.html#SECTION02323000000000000000
http://www.scholarpedia.org/article/Spike-response_model#Spike_Response_Model_SRM.5C.28_0.5C.29
spike response model SRM0
a defined model that is a simplified version of the Spike Response Model and does not include a dependence of the response kernel Îº upon the time since the last spike.
cno_0000079
PMID: 8888612
http://www.scholarpedia.org/article/Spike-response_model#Cumulative_Spike_Response_Model:_bursting_and_adaptation
cumulative spike response model
a defined model that is a spike response model where refractoriness and adaptation were modeled by the combined effects of the spike after potentials of several previous spikes, rather than only the most recent spike.
cno_0000080
http://www.scholarpedia.org/article/Spike-response_model#Spike_Response_Model_with_a_cumulative_dynamic_threshold
spike response model with cumulative dynamic threshold
a defined model that is a spike response model in which the value of the threshold depends on all previous spikes not only the most recent one.
cno_0000081
dynamic threshold
a threshold-based spiking mechanism that represent the variation of the spiking threshold over time based on particular criterions.
cno_0000082
fixed threshold
a threshold-based spiking mechanism that considers the threshold as constant over time.
cno_0000083
http://www.scholarpedia.org/article/Spike-response_model#Mathematical_formulation
spike shape kernel
a cellular model component that is used to build spike response model and which describes the form of the action potential and its spike after-potential. This kernel is a function of the time since the last action potential. It can describe a depolarizing, hyperpolarizing or resonating spike after-potential.
cno_0000084
http://www.scholarpedia.org/article/Spike-response_model#Mathematical_formulation
linear filter of the membrane
responsiveness kernel
a cellular model component that is used to build spike response model and which describes the linear response to an incoming short pulse. The responsiveness kernel to an input pulse depends on the time since the last spike.
cno_0000085
adaptation current
an abstract current model that represents the mechanism of spiking frequency adaptation.
cno_0000086
rebound current
abstract current model that represents the mechanisms of rebound.
cno_0000087
http://en.wikipedia.org/wiki/Hindmarsh%E2%80%93Rose_model
spiking variable, y
spiking current
abstract current model that represents the mechanisms involved in the action potential and which is used to build HindMarch and Rose models
cno_0000088
http://en.wikipedia.org/wiki/Hindmarsh%E2%80%93Rose_model
bursting variable, z
bursting current
abstract current model that represents the mechanisms of bursting and used to build HindMarch and Rose models.
cno_0000089
PMID: 18244602
membrane recovery variable
abstract current model which accounts for the activation of potassium ionic currents and inactivation of sodium ionic currents and provides negative feedback to the membrane voltage
cno_0000090
PMID: 5575343
http://www.scholarpedia.org/article/Conductance-based_models#Examples_and_Variants
Connor-Stevens model
a defined model that is an extended action potential generating model using gastropod somas. This model is similar to the Hodgkin and Huxley model and contains a sodium, potassium and leak current with faster dynamics for the sodium and potassium currents. In addition, a transient potassium current, called, A-current, has been included.
cno_0000091
PMID: 8815919
Wang-Buzsaki model
a defined model that is a network model composed of single compartment models, derived from the original Hodgkin-Huxley model. This network model represents a network of hippocampal interneurons.
cno_0000092
PMID: 19431309
http://www.scholarpedia.org/article/FitzHugh-Nagumo_model
Bonhoeffer-van der Pol model
Fitzhugh-Nagumo model
a defined model that is a two-dimensional simplification of the Hodgkin-Huxley model of spike generation in squid giant axons. The model consist of a voltage-like variable having cubic nonlinearity that allows regenerative self-excitation via positive feedback and a recovery variable having a linear dynamics that provides a slower negative feedback.
cno_0000093
PMID: 7260316
http://www.scholarpedia.org/article/Morris-Lecar_model
Morris-Lecar model
a defined model that is a two-dimensional reduced excitation model applicable to systems having two non-inactivating voltage-sensitive conductances. The original form of the model employed an instantaneously responding voltage-sensitive calcium conductance for excitation and a delayed voltage-dependent potassium conductance for recovery.
cno_0000094
synaptic action
a synapse model component that describes the impact of synaptic model on the post-synaptic model.
cno_0000095
connection element
a synapse model component that describe how the synapse is connected between two neuron models
cno_0000096
http://en.wikipedia.org/wiki/Synaptic_weight
synaptic weight
a synapse model component that refers to the strength or amplitude of a connection between two nodes, corresponding in biology to the amount of influence the firing of one neuron has on another.
cno_0000097
plasticity mechanism
a synapse model component that relates to plasticity models.
cno_0000098
synaptic conductance dynamic
a synaptic model component that describes the dynamic of the synaptic conductance in the post-synaptic model
cno_0000099
synaptic delay
delay between the activation of the synapse and its impact on the post-synaptic model.
cno_0000100
voltage dependent receptor activation
a synapse model component that describes the voltage dependent activation of receptor such as NMDA receptor that will participate in the total synaptic current.
cno_0000101
release mechanism
a synapse model component that describes the neurotrasmitter release.
cno_0000102
neurotransmittor diffusion
a synapse model component that describes the diffusion of neurotransmitter in the extracellular space.
cno_0000103
post-synaptic element
a connection element which points to the model elements of the post-synaptic model that are used in the equations of the synapse model.
cno_0000104
pre-synaptic element
a connection element which points to the model elements of the pre-synaptic model that are used in the equations of the synapse model.
cno_0000105
voltage-dependent current model
an ionic current model that represents the current flowing through ionic channel triggered by the change in voltage.
cno_0000106
voltage and ionic dependent current model
an ionic current model that represents the current flowing through ionic channel triggered by the change of voltage and the binding of a particular ion.
cno_0000107
http://en.wikipedia.org/wiki/Supervised_learning
supervised learning
learning rule that produces an infered function to predict correct output value for any valid input object, based on an error function estimated through the training period with the presentation of input/output pairs.
cno_0000108
ionic dependent current model
a biochemically activated current model that represents the current flowing through ionic channel triggered by the binding of a particular ion.
cno_0000109
biochemically activated current
an ionic current model that represents the current flowing through ionic channels triggered by action of biochemical components.
cno_0000110
unsupervised learning
learning rule that produces an infered function based on unlabeled data without any feedback to evaluate the potential solution.
cno_0000111
excitatory action
a synaptic action that increases the post-synaptic model activity and/or voltage
cno_0000112
inhibitory action
a synaptic action that decreases the post-synaptic activity and/or voltage
cno_0000113
shunting action
a synaptic action that modifies the global conductance of the post-synaptic model
cno_0000114
instantaneous rise and monexponential decay
a synaptic conductance dynamic which assumes an instanteanous rise of the conductance followed by an exponential decay with a time constant.
cno_0000115
difference of two exponentials
a synaptic conductance dynamic that is described as the difference of two exponential functions which represent the rising and the decay phase with two distinct time constants.
cno_0000116
alpha function
a synaptic conductance dynamic describing a conductance that has a rising phase with a certain rise time. As it has just a single time constant, the time course of the rise and decay are correlated.
cno_0000117
cellular elements
a network model component that refers to the cellular model type used to build the network model
cno_0000118
synaptic element
a network model component that refers to the synapse model type used to build the network model
cno_0000119
connectivity pattern
a model component quality that represents a connectivity pattern obtained with specific connectivity rule
cno_0000120
rate function
a cellular model component that describes the dynamic of the cellular model firing rate.
cno_0000121
http://en.wikipedia.org/wiki/Recurrent_neural_network#Fully_recurrent_network
recurrent
a connectivity pattern in which connections between units form a directed cycle.
cno_0000122
http://en.wikipedia.org/wiki/Feedforward_neural_networks
feedforward
a connectivity pattern in which connections between units do not form a directed cycle.
cno_0000123
http://en.wikipedia.org/wiki/Small-world_network
small world
a connectivity pattern in which most nodes are not neighbors of one another, but most node can be reached from every other by a small number of hops or steps.
cno_0000124
functional grouping
cellular grouping quality that represents cellular grouping defined by common functional criterons.
cno_0000125
anatomical grouping
cellular grouping quality that represents cellular grouping based on anatomical information
cno_0000126
current model
a cellular model component that represents the different types of modeled currents that can influence the trajectory of the membrane voltage
cno_0000127
current localization
current model quality that represents the location of the current source on a neuronal model (somatic, primary dendrite, ...)
cno_0000128
current distribution
current model quality that represents the spatial distribution of current sources (ionic channels, synaptic channels, stimulation electrode) on a compartment
cno_0000129
connectivity rule
a network layout component that describe the rules used to establish connections between the cellular elements of the network model
cno_0000130
http://www.ebi.ac.uk/sbo/main/SBO:0000259
voltage
cno_0000131
capacitance
cno_0000132
current
cno_0000133
diameter
cno_0000134
length
cno_0000135
synaptic plasticity element
cno_0000136
frequency
cno_0000137
maximal conductance
cno_0000138
random
cellular grouping quality that represents probabilistic grouping of cellular models within network models.
cno_0000139
spike time
cno_0000140
time constant
cno_0000141
volume
cno_0000142
indices
cno_0000143
cellular grouping quality
a model component quality that represent the properties of cellular grouping in network models
cno_0000144
rate-based neuron model
a cellular model that describe the firing activity of neuron using a rate function.
cno_0000145
refractory period
a duration that represent the duration during which the model cannot emit a subsequent spike following an initial spike.
cno_0000146
spiking threshold
voltage above which the model emits a spike
cno_0000147
elementary model component role
role played by the model elements
cno_0000148
cellular grouping
a network layout component that defines the common attribute or property used to create arbitrary groups of cellular model type.
cno_0000149
Models can be defined without any mention of space.
The model can be enriched with particular spatial embedding.
spatial embedding
a generic model component that add spatial information to the model
cno_0000150
relates to http://neurolex.org/wiki/Category:Two_dimensional_region
two dimensional layout
cno_0000151
http://neurolex.org/wiki/Category:Three_dimensional_region
three dimensional layout
cno_0000152
spatial coordinates
cno_0000153
2D coordinates
cno_0000154
3D coordinates
cno_0000155
polar coordinates
cno_0000156
This term should be transformed into a datatype.
pre-synaptic indice
a pre-synaptic element that specifies the indices of the pre-synaptic neuron model
cno_0000157
is a quality
user-defined
cellular distribution quality that represents the distribution of cellular models in network models arranged based on user-defined criterions that are not based on anatomical information.
cno_0000158
abstract morphology
a morphological quality that describe abstract representation of the morphology. Often cellular compartment are represented as iso-potential cylindrical compartments.
cno_0000159
is a quality
uniform
cellular distribution quality that represents a cellular distribution in network models where cellular models are uniformly distributed in the abstract space.
0123456789
cno_0000160
pre-synaptic variable
elementary model component that specifies the variable of the neuronal model used into the equations of the synapse model.
cno_0000161
developmental plasticity model
model of network plasticity based on developmental rules that will change the structure of the network.
cno_0000162
PMID: 12991237
http://en.wikipedia.org/wiki/Hodgkin%E2%80%93Huxley_model
Hodgkin and Huxley model
defined model that describes how action potentials in neurons are initiated and propagated in squid giant axon.
cno_0000163
post-synaptic indice
a post-synaptic element that specifies the indices of the post-synaptic neuron model
cno_0000164
is a quality
anatomically defined
cellular distribution quality that represents the cellular distribution in the network model based on criterions derived from anatomical information
cno_0000165
Similar to sao1057800815
morphological quality
a model component quality that described the kind of morphology used in the neuron models.
cno_0000166
Example: oscillatory, bursting, synchronization, ...
functional quality
a model quality that describes the intrinsic functional quality of the models
cno_0000167
post-synaptic variable
elementary model component that specifies the variable of the neuronal model used into the equations of the synapse model.
cno_0000168
uniform
a current distribution where current models are uniformly distributed.
cno_0000169
http://en.wikipedia.org/wiki/Learning_rule
learning rule
network model component that is a method which improves the neural network's performance. It is done by updating the weights and bias level of a network after a network is stimulated in an environment.
cno_0000170
random
a current distribution where current models are distributed according to a particular probability distribution.
cno_0000171
non-linear
a current distribution where current models are distributed according to a non-linear function of space.
cno_0000172
linear
a current distribution where current models are distributed according to a linear function of space.
cno_0000173
concentration
cno_0000174
current model quality
model component quality that represent specific properties attached to current models
cno_0000175
model description
an information content entity that represents the differents types of formats which can exist for describing a model (scientific paper, database entry, XML format, ...)
cno_0000176
link to SBO, Kisao, Teddy
mathematical concept
a thing that represents the differents mathematical concepts used to represent models.
cno_0000177
network layout component
a network model component that describe the different level of organization of the network model
cno_0000178
cellular distribution
a network layout component that represents the distribution of the cellular model type in euclidian or non euclidean space.
cno_0000179
related to definition in NIF: http://neurolex.org/wiki/Category:One_dimensional_region
one dimensional layout
cno_0000180
model
a generically_dependent_continuant that is a placeholder for any model
cno_0000181
http://www.thefreedictionary.com/elementary
elementary model component
an elementary model component is the smallest model component on which aggregated component are built. These elements can have either the role of parameter or the role of variable.
cno_0000182
short term plasticity model
short term plasticity rule
model of synaptic plasticity that describes the short term changes in the synaptic activity.
cno_0000183
long term plasticity model
long term plasticity rule
model of synaptic plasticity that describes the long term changes in the synaptic activity.
cno_0000184
rate-based plasticity model
a phenomenological model of long term synaptic plasticity that represent the variation of synaptic impact depending on the firing rate of the models.
cno_0000185
spike timing dependent plasticity model
a phenomenological model of long term synaptic plasticity that represent the variation of synaptic efficacy depending on the relative spike timing of the pre- and post-synaptic models.
cno_0000186
biophysical model
a model of long term synaptic plasticity that represents the biophysical mechanisms involved in the changes of synaptic efficacy.
cno_0000187
http://en.wikipedia.org/wiki/Homeostatic_plasticity
homeostatic plasticity model
homeostatic plasticity rule
synaptic plasticity model that account for the capacity of neurons to regulate their own excitability relative to network activity.
cno_0000188
PMID: 9012851
Markram and Tsodyks model
defined model that describes the impact of neurotransmitter release and synaptic depression.
cno_0000189
PMID: 10966623
http://www.scholarpedia.org/article/Models_of_synaptic_plasticity#Spike_timing_based_models
Song and Abbott model
defined model that is a phenomenological model of spike timing dependent plasticity
cno_0000190
relates to http://neurolex.org/wiki/Category:Zero_dimensional_region
zero dimensional layout
cno_0000191
http://www.ebi.ac.uk/sbo/main/SBO:0000254
resistance
cno_0000192
time
0987654321
cno_0000194
rate
cno_0000195
developmental learning
learning rule based on the mechanisms taking place during the development of the nervous system.
cno_0000196
http://www.scholarpedia.org/article/Reinforcement_learning
reward-based learning
reinforcement learning
a learning rule that allow to learn by interacting with an environment through a trial and error process during which the reward is maximized.
cno_0000197
synaptic plasticity model component
a component of plasticity models that describes the rules governing the changes in synaptic efficacy.
cno_0000198
pair-based rule
timing dependency that modifies the synaptic weight depending on the time difference between pairs of action potentials.
cno_0000199
triplet-based rule
timing dependency that modifies the synaptic weight depending on the time difference between triplets of action potentials.
cno_0000200
reference the model from Froemke and Dan, 2002 described in Morrisson, 2008
suppression model
timing dependency that accounts for the suppression of NMDA receptor during spike timing dependent long term depression
cno_0000201
short term depression model
a model of short term synaptic plasticity that represent the decrease of the synaptic efficacy for a short period of time
cno_0000202
model component quality
quality exhibited by model components
cno_0000203
cellular distribution quality
model component quality that describes the distribution of cellular model in abstract space
cno_0000205
ModelDB accession number
A CRID symbol that is sufficient to look up a model from ModelDB
cno_0000206
mixed grouping
cellular grouping quality that represents the grouping of cellular model based on two criterions: anatomical and functional
cno_0000207
http://www.ebi.ac.uk/sbo/main/SBO:0000225
delay
cno_0000208
http://www.ebi.ac.uk/sbo/main/SBO:0000347
duration
cno_0000209
obsolete
cno_0000210
plasticity model component
a model component that is used to build a plasticity model type
cno_0000211
timing dependency
a component of a synaptic plasticity rule that describes the dependency of synaptic changes on the relative spike timing in the pre- and post-synaptic models
cno_0000212
weight update component
a component of a synaptic plasticity rule that describes the changes in synaptic weight.
cno_0000213
voltage dependency
a component of a synaptic plasticity rule that describes the relation between the post-synaptic voltage and the change in synaptic efficacy.
cno_0000214
weight independent
additive
a weight update component that updates the weight with additive increment
cno_0000215
http://www.scholarpedia.org/article/Spike-timing_dependent_plasticity#Weight_dependence:_hard_bounds_and_soft_bounds
weight dependent
weight update component that updates the weight within bounded range by multiplying the changes by constants called soft bounds or multiplicative weight dependence.
cno_0000216
learning rate
elementary model component that set the amount by which synaptic weight are updated
cno_0000217
http://www.scholarpedia.org/article/Conductance-based_models
leakage current
abstract current model that approximates the passive properties of biological neurons.
cno_0000218
aggregated model component
a model component that results from the aggregation of parameters and/or variable and/or mathematical operators
cno_0000219
http://en.wikipedia.org/wiki/Variable_(mathematics)
variable
elementary model component role that defines an elementary model component as a value that may change within the scope of a given problem or set of operations.
cno_0000220
membrane capacitance
Measure of the amount of electric charge stored (or separated) by the cellular membrane for a given electric potential. The unit of capacitance is the Farad.
cno_0000221
membrane resistance
Measure of the degree to which the cellular membrane opposes the passage of an electric current. The SI unit of electrical resistance is the ohm.
cno_0000222
membrane time constante
0123456789
fakething
Federal Funding Resource
snap:GenericallyDependentContinuant
snap:Quality
snap:Role
rdf:List
core:Collection
skos:Collection
Collection
A meaningful collection of concepts.
Labelled collections can be used where you would like a set of concepts to be displayed under a 'node label' in the hierarchy.
core:Concept
skos:Concept
Concept
An idea or notion; a unit of thought.
core:ConceptScheme
skos:ConceptScheme
Concept Scheme
A set of concepts, optionally including statements about semantic relationships between those concepts.
Thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', and other types of controlled vocabulary are all examples of concept schemes. Concept schemes are also embedded in glossaries and terminologies.
A concept scheme may be defined to include concepts from different sources.
skos:OrderedCollection
Ordered Collection
An ordered collection of concepts, where both the grouping and the ordering are meaningful.
Ordered collections can be used where you would like a set of concepts to be displayed in a specific order, and optionally under a 'node label'.
version 0.5
13/03/2012
version 0.5
An ontology to describe the field of Computational Neurosciences
Yann Le Franc
Erik De Schutter
Computational Neuroscience Ontology
Padraig Gleeson
Subhasis Ray
Stephen D. Larson
This ontology is used to add the Definition class of annotation as in NIF.
The source of the definition can be defined with class from OBO-annotation
Fahim T. Imam
Lars Schwabe
This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, Mountain View, California, 94041, USA.
Birgit Kriener
INCF MultiScale Modeling Task Force
Sean Hill
Participants in W3C's Semantic Web Deployment Working Group.
Sean Bechhofer
Dave Beckett
SKOS Vocabulary
Alistair Miles
Nikki Rogers
An RDF vocabulary for describing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, 'folksonomies', other types of controlled vocabulary, and also concept schemes embedded in glossaries and terminologies.