#neuroml — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #neuroml, aggregated by home.social.
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Progress on building an #AI assistant for #Neuroscience: scope, funding, ideas, and a name: #Klea
#Neuroscience #OpenScience #LLM #LangChain #LangGraph #MCP #Python #FastAPI #FastMCP #NeuroML #NWB #ComputationalNeuroscience #ComputationalModelling #DataAnalysis #Klea
TLDR: the #RAG is ready for you to play with. The coding agent is WIP.
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Progress on building an #AI assistant for #Neuroscience: scope, funding, ideas, and a name: #Klea
#Neuroscience #OpenScience #LLM #LangChain #LangGraph #MCP #Python #FastAPI #FastMCP #NeuroML #NWB #ComputationalNeuroscience #ComputationalModelling #DataAnalysis #Klea
TLDR: the #RAG is ready for you to play with. The coding agent is WIP.
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Progress on building an #AI assistant for #Neuroscience: scope, funding, ideas, and a name: #Klea
#Neuroscience #OpenScience #LLM #LangChain #LangGraph #MCP #Python #FastAPI #FastMCP #NeuroML #NWB #ComputationalNeuroscience #ComputationalModelling #DataAnalysis #Klea
TLDR: the #RAG is ready for you to play with. The coding agent is WIP.
-
Progress on building an #AI assistant for #Neuroscience: scope, funding, ideas, and a name: #Klea
#Neuroscience #OpenScience #LLM #LangChain #LangGraph #MCP #Python #FastAPI #FastMCP #NeuroML #NWB #ComputationalNeuroscience #ComputationalModelling #DataAnalysis #Klea
TLDR: the #RAG is ready for you to play with. The coding agent is WIP.
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Building detailed neuronal models is hard---#NeuroML helps, but there’s still a steep learning curve. We're investigating how #LLMs can be used to create natural language interfaces to improve accessibility:
- #RAG for NeuroML: learn from and query curated information sources
- iterative LLM assisted code/model generation: modelling, validation, and simulationMore details in the post:
#Neuroscience #ComputationalNeuroscience #AcademicChatter #LangChain
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Building detailed neuronal models is hard---#NeuroML helps, but there’s still a steep learning curve. We're investigating how #LLMs can be used to create natural language interfaces to improve accessibility:
- #RAG for NeuroML: learn from and query curated information sources
- iterative LLM assisted code/model generation: modelling, validation, and simulationMore details in the post:
#Neuroscience #ComputationalNeuroscience #AcademicChatter #LangChain
-
Building detailed neuronal models is hard---#NeuroML helps, but there’s still a steep learning curve. We're investigating how #LLMs can be used to create natural language interfaces to improve accessibility:
- #RAG for NeuroML: learn from and query curated information sources
- iterative LLM assisted code/model generation: modelling, validation, and simulationMore details in the post:
#Neuroscience #ComputationalNeuroscience #AcademicChatter #LangChain
-
Building detailed neuronal models is hard---#NeuroML helps, but there’s still a steep learning curve. We're investigating how #LLMs can be used to create natural language interfaces to improve accessibility:
- #RAG for NeuroML: learn from and query curated information sources
- iterative LLM assisted code/model generation: modelling, validation, and simulationMore details in the post:
#Neuroscience #ComputationalNeuroscience #AcademicChatter #LangChain
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I created a #CookieCutter project template for #ComputationalModelling using #NeuroML
(You can use it for non NeuroML models too, or modify it for your own templates)
More information here:
#ComputationalNeuroscience #Python #Neuroscience #AcademicChatter
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I created a #CookieCutter project template for #ComputationalModelling using #NeuroML
(You can use it for non NeuroML models too, or modify it for your own templates)
More information here:
#ComputationalNeuroscience #Python #Neuroscience #AcademicChatter
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I created a #CookieCutter project template for #ComputationalModelling using #NeuroML
(You can use it for non NeuroML models too, or modify it for your own templates)
More information here:
#ComputationalNeuroscience #Python #Neuroscience #AcademicChatter
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I created a #CookieCutter project template for #ComputationalModelling using #NeuroML
(You can use it for non NeuroML models too, or modify it for your own templates)
More information here:
#ComputationalNeuroscience #Python #Neuroscience #AcademicChatter
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A lot of steps for starting new computational modelling projects in #NeuroML are repeatable and can be automated. So, I created a #Cookiecutter template to quickstart these projects. It includes boilerplate code and implements lots of other recommended/best practices in model and software development. Feedback/suggestions welcome!
#Neuroscience #ComputationalNeuroscience #Python #Git #AcademicChatter #FAIR #OpenScience #FOSS #SoftwareDevelopment
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A lot of steps for starting new computational modelling projects in #NeuroML are repeatable and can be automated. So, I created a #Cookiecutter template to quickstart these projects. It includes boilerplate code and implements lots of other recommended/best practices in model and software development. Feedback/suggestions welcome!
#Neuroscience #ComputationalNeuroscience #Python #Git #AcademicChatter #FAIR #OpenScience #FOSS #SoftwareDevelopment
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A lot of steps for starting new computational modelling projects in #NeuroML are repeatable and can be automated. So, I created a #Cookiecutter template to quickstart these projects. It includes boilerplate code and implements lots of other recommended/best practices in model and software development. Feedback/suggestions welcome!
#Neuroscience #ComputationalNeuroscience #Python #Git #AcademicChatter #FAIR #OpenScience #FOSS #SoftwareDevelopment
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A new version of the Open Source Brain (#OpenSourceBrain) model validation framework was just released. Please update your installations:
```
pip install -U OSBModelValidation
```https://github.com/OpenSourceBrain/osb-model-validation/releases/tag/v0.3.9
#OMV is a #Python package that allows you to validate your #NeuroML models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:
https://github.com/OpenSourceBrain/.github/blob/main/testsheet/README.md
#FAIR #ComputationalNeuroscience #Neuroscience #ModelValidation
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A new version of the Open Source Brain (#OpenSourceBrain) model validation framework was just released. Please update your installations:
```
pip install -U OSBModelValidation
```https://github.com/OpenSourceBrain/osb-model-validation/releases/tag/v0.3.9
#OMV is a #Python package that allows you to validate your #NeuroML models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:
https://github.com/OpenSourceBrain/.github/blob/main/testsheet/README.md
#FAIR #ComputationalNeuroscience #Neuroscience #ModelValidation
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A new version of the Open Source Brain (#OpenSourceBrain) model validation framework was just released. Please update your installations:
```
pip install -U OSBModelValidation
```https://github.com/OpenSourceBrain/osb-model-validation/releases/tag/v0.3.9
#OMV is a #Python package that allows you to validate your #NeuroML models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:
https://github.com/OpenSourceBrain/.github/blob/main/testsheet/README.md
#FAIR #ComputationalNeuroscience #Neuroscience #ModelValidation
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of PyNeuroML is available, please update your installations:
https://github.com/NeuroML/pyNeuroML/releases
```
pip install --upgrade pyneuroml
```#NeuroML #ComputationalNeuroscience #Neuroscience #Python #AcademicChatter
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A new release of #PyNeuroML is available. Please update to get the latest fixes and features. #NeuroML #ComputationalModelling #ComputationalNeuroscience
```
pip install --upgrade pyneuroml
``` -
A new release of #PyNeuroML is available. Please update to get the latest fixes and features. #NeuroML #ComputationalModelling #ComputationalNeuroscience
```
pip install --upgrade pyneuroml
``` -
A new release of #PyNeuroML is available. Please update to get the latest fixes and features. #NeuroML #ComputationalModelling #ComputationalNeuroscience
```
pip install --upgrade pyneuroml
``` -
In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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In the next version, 0.6.6, all component classes in the #libNeuroML #Python API gain a quick method to list the parameters of their model objects. So, if you load a #NeuroML file/model, you can easily print the parameters of the different model entities. See the test in the pull request for a quick example:
https://github.com/NeuralEnsemble/libNeuroML/pull/208/files
#ComputationalNeuroscience #AcademicChatter #Neuroscience #FAIR
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#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.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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#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.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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#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.
https://docs.neuroml.org/NeuroMLOrg/OutreachTraining.html#google-summer-of-code
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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Please see the paper for more details, and whether you’d like to use #NeuroML in your work, or support NeuroML in your tools/modelling pipelines, please come speak to us on any of our communication channels. Full documentation on NeuroML is here at https://docs.neuroml.org 9/9
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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#NeuroML is a global community initiative. It is developed by an elected Editorial Board and overseen by a Scientific Committee. All the software/documentation/models produced in NeuroML are completely Free/Open. In this way, NeuroML supports #FAIR (Findability, Accessibility, Interoperability, and Reusability) principles, thus promoting open, transparent and reproducible science. 8/x
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#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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#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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#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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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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You can also create new model elements if existing ones aren’t enough AND because #NeuroML is designed to be modular and hierarchical, ALL model elements are independent and can be reused in any NeuroML models. See the full specification here: https://docs.neuroml.org/Userdocs/Specification.html 6/x
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a curated set of model elements for researchers to use. This includes simpler single compartment cells (integrate and fire, Izhikevich, and so on), but also bits required to build detailed multi-compartmental cells (Hodgkin Huxley and Kinetic scheme ionic conductances), synapse models, networks/projections, and network inputs such as spike trains and pulse generators.
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#NeuroML provides a simulator independent standard and software tools. The idea is that researchers can use NeuroML to build their models, and these models will “just run” in any of the supported simulators. So, researchers only need to learn how to use NeuroML and then choose what simulator they want to run their model in. NeuroML-compliant tools will take care of the rest, “under the hood”. 4/x
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#NeuroML provides a simulator independent standard and software tools. The idea is that researchers can use NeuroML to build their models, and these models will “just run” in any of the supported simulators. So, researchers only need to learn how to use NeuroML and then choose what simulator they want to run their model in. NeuroML-compliant tools will take care of the rest, “under the hood”. 4/x
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#NeuroML provides a simulator independent standard and software tools. The idea is that researchers can use NeuroML to build their models, and these models will “just run” in any of the supported simulators. So, researchers only need to learn how to use NeuroML and then choose what simulator they want to run their model in. NeuroML-compliant tools will take care of the rest, “under the hood”. 4/x
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We are very happy to provide a consolidated update on the #NeuroML ecosystem in our @eLife paper, “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience”: https://doi.org/10.7554/eLife.95135.3
#NeuroML is a standard and software ecosystem for data-driven biophysically detailed #ComputationalModelling endorsed by the @INCF and CoMBINE, and includes a large community of users and software developers.
#Neuroscience #ComputationalNeuroscience #ComputationalModelling 1/x
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We are very happy to provide a consolidated update on the #NeuroML ecosystem in our @eLife paper, “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience”: https://doi.org/10.7554/eLife.95135.3
#NeuroML is a standard and software ecosystem for data-driven biophysically detailed #ComputationalModelling endorsed by the @INCF and CoMBINE, and includes a large community of users and software developers.
#Neuroscience #ComputationalNeuroscience #ComputationalModelling 1/x
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We are very happy to provide a consolidated update on the #NeuroML ecosystem in our @eLife paper, “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience”: https://doi.org/10.7554/eLife.95135.3
#NeuroML is a standard and software ecosystem for data-driven biophysically detailed #ComputationalModelling endorsed by the @INCF and CoMBINE, and includes a large community of users and software developers.
#Neuroscience #ComputationalNeuroscience #ComputationalModelling 1/x
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Update on what I did from weeks 27-36 this year:
https://ankursinha.in/2024/09/06/week-27-36-update.html
#NeuroML #ComputationalNeuroscience #Fedora #OpenSourceBrain #GoogleSummerOfCode #ComputationalModelling #AcademicChatter #FOSS #OpenScience
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Update on what I did from weeks 27-36 this year:
https://ankursinha.in/2024/09/06/week-27-36-update.html
#NeuroML #ComputationalNeuroscience #Fedora #OpenSourceBrain #GoogleSummerOfCode #ComputationalModelling #AcademicChatter #FOSS #OpenScience
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Update on what I did from weeks 27-36 this year:
https://ankursinha.in/2024/09/06/week-27-36-update.html
#NeuroML #ComputationalNeuroscience #Fedora #OpenSourceBrain #GoogleSummerOfCode #ComputationalModelling #AcademicChatter #FOSS #OpenScience
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You can also get it from #NeuroML-DB here:
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You can also get it from #NeuroML-DB here:
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You can also get it from #NeuroML-DB here:
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#Standardized #NeuroML model of the day (2024-09-11):
Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties, Hay et al 2011
See if on #OpenSourceBrain here:
https://v1.opensourcebrain.org/projects/l5bpyrcellhayetal2011
and on #GitHub here: https://github.com/OpenSourceBrain/L5bPyrCellHayEtAl2011
#ComputationalNeuroscience #ComputationalModelling #Neuroscience #Cortex #Layer5B #FAIR #OpenScience #AcademicChatter
Learn more about NeuroML here: https://docs.neuroml.org
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#Standardized #NeuroML model of the day (2024-09-11):
Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties, Hay et al 2011
See if on #OpenSourceBrain here:
https://v1.opensourcebrain.org/projects/l5bpyrcellhayetal2011
and on #GitHub here: https://github.com/OpenSourceBrain/L5bPyrCellHayEtAl2011
#ComputationalNeuroscience #ComputationalModelling #Neuroscience #Cortex #Layer5B #FAIR #OpenScience #AcademicChatter
Learn more about NeuroML here: https://docs.neuroml.org
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#Standardized #NeuroML model of the day (2024-09-11):
Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties, Hay et al 2011
See if on #OpenSourceBrain here:
https://v1.opensourcebrain.org/projects/l5bpyrcellhayetal2011
and on #GitHub here: https://github.com/OpenSourceBrain/L5bPyrCellHayEtAl2011
#ComputationalNeuroscience #ComputationalModelling #Neuroscience #Cortex #Layer5B #FAIR #OpenScience #AcademicChatter
Learn more about NeuroML here: https://docs.neuroml.org