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NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail

Gleeson, Padraig ; Crook, Sharon ; Cannon, Robert C ; Hines, Michael L ; Billings, Guy O ; Farinella, Matteo ; Morse, Thomas M ; Davison, Andrew P ; Ray, Subhasis ; Bhalla, Upinder S ; Barnes, Simon R ; Dimitrova, Yoana D ; Silver, R Angus Friston, Karl J.

PLoS computational biology, 2010-06, Vol.6 (6), p.e1000815-e1000815 [Periódico revisado por pares]

United States: Public Library of Science

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Título:
NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail
Autor: Gleeson, Padraig ; Crook, Sharon ; Cannon, Robert C ; Hines, Michael L ; Billings, Guy O ; Farinella, Matteo ; Morse, Thomas M ; Davison, Andrew P ; Ray, Subhasis ; Bhalla, Upinder S ; Barnes, Simon R ; Dimitrova, Yoana D ; Silver, R Angus
Friston, Karl J.
Assuntos: Brain research ; CA1 Region, Hippocampal ; CA1 Region, Hippocampal - cytology ; CA1 Region, Hippocampal - physiology ; Cerebral Cortex ; Cerebral Cortex - cytology ; Cerebral Cortex - physiology ; Computational Biology ; Computational Biology - methods ; Computational Biology/Computational Neuroscience ; Computational Biology/Systems Biology ; Computer Simulation ; Electrical Synapses ; Grants ; Humans ; Language ; Life Sciences ; Models, Neurological ; Nerve Net ; Neural networks ; Neurons ; Neurons - physiology ; Neurons and Cognition ; Neuroscience ; Neuroscience/Theoretical Neuroscience ; Neurosciences ; Open source software ; Physiological aspects ; Public software ; Reproducibility of Results ; Software ; Studies ; Thalamus ; Thalamus - cytology ; Thalamus - physiology
É parte de: PLoS computational biology, 2010-06, Vol.6 (6), p.e1000815-e1000815
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMCID: PMC2887454
Wrote the paper: PG RAS. Conceived and managed the project: PG SC RAS. Developed current structure of NeuroML: PG SC RCC MLH GOB RAS. Developed NEURON support: PG MLH TMM. Developed PSICS support: PG RCC. Developed PyNN support: PG GOB APD. Developed MOOSE support: PG SR USB. Ported models from Traub et al., 2005 to NeuroML and solved interoperability issues: PG MF SRB YDD RAS.
Descrição: Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. While neuronal simulators such as NEURON, GENESIS, MOOSE, NEST, and PSICS facilitate the development of these data-driven neuronal models, the specialized languages they employ are generally not interoperable, limiting model accessibility and preventing reuse of model components and cross-simulator validation. To overcome these problems we have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience.
Editor: United States: Public Library of Science
Idioma: Inglês

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NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail

Gleeson, Padraig ; Crook, Sharon ; Cannon, Robert C ; Hines, Michael L ; Billings, Guy O ; Farinella, Matteo ; Morse, Thomas M ; Davison, Andrew P ; Ray, Subhasis ; Bhalla, Upinder S ; Barnes, Simon R ; Dimitrova, Yoana D ; Silver, R Angus Friston, Karl J.

United States: Public Library of Science

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