The NeuroML ecosystem for standardized multi-scale modeling in neuroscience
Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complex...
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| Format: | Article |
| Language: | English |
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eLife Sciences Publications Ltd
2025-01-01
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| Series: | eLife |
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| Online Access: | https://elifesciences.org/articles/95135 |
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| author | Ankur Sinha Padraig Gleeson Bóris Marin Salvador Dura-Bernal Sotirios Panagiotou Sharon Crook Matteo Cantarelli Robert C Cannon Andrew P Davison Harsha Gurnani Robin Angus Silver |
| author_facet | Ankur Sinha Padraig Gleeson Bóris Marin Salvador Dura-Bernal Sotirios Panagiotou Sharon Crook Matteo Cantarelli Robert C Cannon Andrew P Davison Harsha Gurnani Robin Angus Silver |
| author_sort | Ankur Sinha |
| collection | DOAJ |
| description | Data-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows. NeuroML, a model description language for computational neuroscience, was developed to address this fragmentation in modeling tools. Since its inception, NeuroML has evolved into a mature community standard that encompasses a wide range of model types and approaches in computational neuroscience. It has enabled the development of a large ecosystem of interoperable open-source software tools for the creation, visualization, validation, and simulation of data-driven models. Here, we describe how the NeuroML ecosystem can be incorporated into research workflows to simplify the construction, testing, and analysis of standardized models of neural systems, and supports the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. |
| format | Article |
| id | doaj-art-089c5504cc874d9e8b3ccc57e7abd536 |
| institution | Kabale University |
| issn | 2050-084X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj-art-089c5504cc874d9e8b3ccc57e7abd5362025-01-10T16:55:11ZengeLife Sciences Publications LtdeLife2050-084X2025-01-011310.7554/eLife.95135The NeuroML ecosystem for standardized multi-scale modeling in neuroscienceAnkur Sinha0https://orcid.org/0000-0001-7568-7167Padraig Gleeson1https://orcid.org/0000-0001-5963-8576Bóris Marin2Salvador Dura-Bernal3Sotirios Panagiotou4Sharon Crook5Matteo Cantarelli6https://orcid.org/0000-0002-0054-226XRobert C Cannon7Andrew P Davison8https://orcid.org/0000-0002-4793-7541Harsha Gurnani9Robin Angus Silver10https://orcid.org/0000-0002-5480-6638Department of Neuroscience, Physiology and Pharmacology, University College London, London, United KingdomDepartment of Neuroscience, Physiology and Pharmacology, University College London, London, United KingdomUniversidade Federal do ABC, São Bernardo do Campo, BrazilSUNY Downstate Medical Center, Brooklyn, United States; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, United StatesErasmus University Rotterdam, Rotterdam, NetherlandsArizona State University, Tempe, United StatesMetaCell Ltd, Cambridge, United StatesOpus2 International Ltd, London, United KingdomCNRS, Gif-Sur-Yvette, FranceUniversity of Washington, Seattle, United StatesDepartment of Neuroscience, Physiology and Pharmacology, University College London, London, United KingdomData-driven models of neurons and circuits are important for understanding how the properties of membrane conductances, synapses, dendrites, and the anatomical connectivity between neurons generate the complex dynamical behaviors of brain circuits in health and disease. However, the inherent complexity of these biological processes makes the construction and reuse of biologically detailed models challenging. A wide range of tools have been developed to aid their construction and simulation, but differences in design and internal representation act as technical barriers to those who wish to use data-driven models in their research workflows. NeuroML, a model description language for computational neuroscience, was developed to address this fragmentation in modeling tools. Since its inception, NeuroML has evolved into a mature community standard that encompasses a wide range of model types and approaches in computational neuroscience. It has enabled the development of a large ecosystem of interoperable open-source software tools for the creation, visualization, validation, and simulation of data-driven models. Here, we describe how the NeuroML ecosystem can be incorporated into research workflows to simplify the construction, testing, and analysis of standardized models of neural systems, and supports the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science.https://elifesciences.org/articles/95135systems modelingcomputationalsoftware infrastucturesimulation |
| spellingShingle | Ankur Sinha Padraig Gleeson Bóris Marin Salvador Dura-Bernal Sotirios Panagiotou Sharon Crook Matteo Cantarelli Robert C Cannon Andrew P Davison Harsha Gurnani Robin Angus Silver The NeuroML ecosystem for standardized multi-scale modeling in neuroscience eLife systems modeling computational software infrastucture simulation |
| title | The NeuroML ecosystem for standardized multi-scale modeling in neuroscience |
| title_full | The NeuroML ecosystem for standardized multi-scale modeling in neuroscience |
| title_fullStr | The NeuroML ecosystem for standardized multi-scale modeling in neuroscience |
| title_full_unstemmed | The NeuroML ecosystem for standardized multi-scale modeling in neuroscience |
| title_short | The NeuroML ecosystem for standardized multi-scale modeling in neuroscience |
| title_sort | neuroml ecosystem for standardized multi scale modeling in neuroscience |
| topic | systems modeling computational software infrastucture simulation |
| url | https://elifesciences.org/articles/95135 |
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