eprintid: 10203596 rev_number: 6 eprint_status: archive userid: 699 dir: disk0/10/20/35/96 datestamp: 2025-01-20 09:59:05 lastmod: 2025-01-20 09:59:05 status_changed: 2025-01-20 09:59:05 type: article metadata_visibility: show sword_depositor: 699 creators_name: Sinha, Ankur creators_name: Gleeson, Padraig creators_name: Marin, Bóris creators_name: Dura-Bernal, Salvador creators_name: Panagiotou, Sotirios creators_name: Crook, Sharon creators_name: Cantarelli, Matteo creators_name: Cannon, Robert C creators_name: Davison, Andrew P creators_name: Gurnani, Harsha creators_name: Silver, Robin Angus title: The NeuroML ecosystem for standardized multi-scale modeling in neuroscience ispublished: pub divisions: UCL divisions: B02 divisions: C08 divisions: D09 divisions: G02 note: © Copyright Sinha, Gleeson et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. abstract: 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. date: 2025-01-10 date_type: published publisher: eLife Sciences Publications, Ltd official_url: https://doi.org/10.7554/elife.95135.3 oa_status: green full_text_type: pub language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2353635 doi: 10.7554/elife.95135.3 lyricists_name: Sinha, Ankur lyricists_name: Silver, Robin lyricists_name: Gleeson, Patrick lyricists_id: ASINH28 lyricists_id: ASILV65 lyricists_id: PGLEE72 actors_name: Silver, Robin actors_id: ASILV65 actors_role: owner full_text_status: public publication: eLife volume: 13 article_number: RP95135 issn: 2050-084X citation: Sinha, Ankur; Gleeson, Padraig; Marin, Bóris; Dura-Bernal, Salvador; Panagiotou, Sotirios; Crook, Sharon; Cantarelli, Matteo; ... Silver, Robin Angus; + view all <#> Sinha, Ankur; Gleeson, Padraig; Marin, Bóris; Dura-Bernal, Salvador; Panagiotou, Sotirios; Crook, Sharon; Cantarelli, Matteo; Cannon, Robert C; Davison, Andrew P; Gurnani, Harsha; Silver, Robin Angus; - view fewer <#> (2025) The NeuroML ecosystem for standardized multi-scale modeling in neuroscience. eLife , 13 , Article RP95135. 10.7554/elife.95135.3 <https://doi.org/10.7554/elife.95135.3>. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10203596/1/Sinha_eLIFE_2025.pdf