NeuroML/pyNeuroML: v1.1.0

What's Changed fix(plots): provide axis for colorbar by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/252 fix(vispy-morph): get title from cell object if no network is found by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/251 feat(morph-plots): improve colouring of cells/groups in schematic plot by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/248 feat(pynml): include more info in version by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/249 Feat/chan den analysis by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/242 Feat/nsgr integration by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/243 To v1.1.0; Update to jnml v0.12.3 jar by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/254 Full Changelog: https://github.com/NeuroML/pyNeuroML/compare/v1.0.10...v1.1.

NeuroML/pyNeuroML: v1.1.4

<h2>What's Changed</h2> <ul> <li>Close cylindrical meshes for vispy viewer by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/264</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/NeuroML/pyNeuroML/compare/v1.1.3...v1.1.4</p&gt

NeuroML/pyNeuroML: v1.1.3

<h2>What's Changed</h2> <ul> <li>chore(deps): remove unused pandas by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/261</li> <li>Improve performance of vispy plotter using meshes and their instances by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/260</li> <li>For 1.1.3 release by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/263</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/NeuroML/pyNeuroML/compare/v1.1.2...v1.1.3</p&gt

NeuroML/pyNeuroML: v1.1.7

<h2>What's Changed</h2> <ul> <li>Testing sbml by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/267</li> <li>feat(graph-generator): allow passing kwargs to GraphVizHandler by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/270</li> <li>feat(plotter): use matplotlib rcparams defaults for missing options by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/271</li> <li>Test sbml by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/274</li> <li>added -validate-sbml option by @robertvi in https://github.com/NeuroML/pyNeuroML/pull/266</li> <li>Tweaks to sbml; fix generate_plot() in pynml; to v1.1.7 by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/275</li> <li>Expose <code>meta</code> in LEMSSimulation by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/262</li> </ul> <h2>New Contributors</h2> <ul> <li>@robertvi made their first contribution in https://github.com/NeuroML/pyNeuroML/pull/266</li> </ul> <p><strong>Full Changelog</strong>: https://github.com/NeuroML/pyNeuroML/compare/v1.1.5...v1.1.7</p&gt

NeuroML/pyNeuroML: v1.1.2

What's Changed Reduce memory usage when generating morph plots and a few minor fixes by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/258 To 1.1.2 by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/259 Full Changelog: https://github.com/NeuroML/pyNeuroML/compare/v1.1.1...v1.1.

NeuroML/pyNeuroML: v1.1.1

What's Changed To v1.1.0; uses jnml jar 0.12.4 by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/256 feat(write): include HDF5 writing by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/255 Feat/hybrid plots: allow users to specify how they want various cells in networks to be plotted by @sanjayankur31 in https://github.com/NeuroML/pyNeuroML/pull/253 Changes for NML v2.3 release by @pgleeson in https://github.com/NeuroML/pyNeuroML/pull/257 Full Changelog: https://github.com/NeuroML/pyNeuroML/compare/v1.1.0...v1.1.

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

International audienceComputational 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