Computational models are powerful tools for exploring the properties of complex biological systems. In neuroscience, data-driven models of neural circuits that span multiple scales are increasingly being used to understand brain function in health and disease. But their adoption and reuse has been limited by the specialist knowledge required to evaluate and use them. To address this, we have developed Open Source Brain, a platform for sharing, viewing, analyzing, and simulating standardized models from different brain regions and species. Model structure and parameters can be automatically visualized and their dynamical properties explored through browser-based simulations. Infrastructure and tools for collaborative interaction, development, and testing are also provided. We demonstrate how existing components can be reused by constructing new models of inhibition-stabilized cortical networks that match recent experimental results. These features of Open Source Brain improve the accessibility, transparency, and reproducibility of models and facilitate their reuse by the wider community. Open Source Brain is an online resource of neuronal and circuit models that enables browser-based visualization, analysis, and simulation. Gleeson et al. describe how the resource and tools for collaborative model development provide accessible, up-to-date models from different brain regions.

Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits / Gleeson, P.; Cantarelli, M.; Marin, B.; Quintana, A.; Earnshaw, M.; Sadeh, S.; Piasini, E.; Birgiolas, J.; Cannon, R. C.; Cayco-Gajic, N. A.; Crook, S.; Davison, A. P.; Dura-Bernal, S.; Ecker, A.; Hines, M. L.; Idili, G.; Lanore, F.; Larson, S. D.; Lytton, W. W.; Majumdar, A.; Mcdougal, R. A.; Sivagnanam, S.; Solinas, S.; Stanislovas, R.; van Albada, S. J.; van Geit, W.; Silver, R. A.. - In: NEURON. - ISSN 0896-6273. - 103:3(2019), pp. 395-411. [10.1016/j.neuron.2019.05.019]

Open Source Brain: A Collaborative Resource for Visualizing, Analyzing, Simulating, and Developing Standardized Models of Neurons and Circuits

Piasini, E.;
2019-01-01

Abstract

Computational models are powerful tools for exploring the properties of complex biological systems. In neuroscience, data-driven models of neural circuits that span multiple scales are increasingly being used to understand brain function in health and disease. But their adoption and reuse has been limited by the specialist knowledge required to evaluate and use them. To address this, we have developed Open Source Brain, a platform for sharing, viewing, analyzing, and simulating standardized models from different brain regions and species. Model structure and parameters can be automatically visualized and their dynamical properties explored through browser-based simulations. Infrastructure and tools for collaborative interaction, development, and testing are also provided. We demonstrate how existing components can be reused by constructing new models of inhibition-stabilized cortical networks that match recent experimental results. These features of Open Source Brain improve the accessibility, transparency, and reproducibility of models and facilitate their reuse by the wider community. Open Source Brain is an online resource of neuronal and circuit models that enables browser-based visualization, analysis, and simulation. Gleeson et al. describe how the resource and tools for collaborative model development provide accessible, up-to-date models from different brain regions.
2019
103
3
395
411
https://doi.org/10.1016/j.neuron.2019.05.019
Gleeson, P.; Cantarelli, M.; Marin, B.; Quintana, A.; Earnshaw, M.; Sadeh, S.; Piasini, E.; Birgiolas, J.; Cannon, R. C.; Cayco-Gajic, N. A.; Crook, S.; Davison, A. P.; Dura-Bernal, S.; Ecker, A.; Hines, M. L.; Idili, G.; Lanore, F.; Larson, S. D.; Lytton, W. W.; Majumdar, A.; Mcdougal, R. A.; Sivagnanam, S.; Solinas, S.; Stanislovas, R.; van Albada, S. J.; van Geit, W.; Silver, R. A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/127543
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