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#pynn

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Ankur Sinha "FranciscoD"

#NeuroML is participating in #GSoC2025 again this year under @INCF . We're looking for people with some experience of #ComputationalNeuroscience to work on developing #standardised biophysically detailed computational models using #NeuroML #PyNN and #OpenSourceBrain.

Please spread the word, especially to students interested in modelling. We will help them learn the NeuroML ecosystem so they can use its standardised pipeline in their work.

docs.neuroml.org/NeuroMLOrg/Ou

CC #AcademicChatter

docs.neuroml.orgOutreach and training — NeuroML Documentation
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Public
Ankur Sinha "FranciscoD"

#NeuroML supports all stages of the modelling life-cycle with a vast ecosystem of software tools: creating (#pyNeuroML, #neuroConstruct, #NEURON, #NetPyNE, #PyNN, #N2A), validating (pyNeuroML, #OMV, #SciUnit), visualising (pyNeuroML, #OSB, #NeuroML-DB), simulating (#NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN), model fitting/optimisation (#NeuroTune, #BluePyOpt, NetPyNE), sharing and reusing of models (OSB, NeuroML-DB, #NeuroMorpho.org). 7/x

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Ankur Sinha "FranciscoD"

A number of software tools are available for construction and simulation of models: #NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN etc. These have their own features, styles, programming interfaces (APIs). This is great but it also means that researchers need to learn each of these individually to use them. It also means that tools and models developed for one don’t necessarily work for others and need to be manually converted. This is often a non-trivial task and limits model reuse. 3/x

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