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Model Downloads

Below are instances of models from the reconstructed neocortical microcircuit. The models are made available in the native format in use at the BBP, based on the NEURON simulation package (http://www.neuron.yale.edu).

See the Tools page for instructions on the execution of simulations using NEURON based models.

Neurons

Models of individual neurons (in the NEURON simulation environment) can be obtained from the me-type fact sheets. A model package contains a morphology file, the ion channel descriptions, the synapse descriptions and templates to instantiate the cell. There is code to construct the model, distribute the ion channels and synapses on the morphology, generate a GUI, and inject current clamp and synaptic input into the model.

The morphology description is a formatted as a Neurolucide ASCII file. The ion channel and synapse description are available as NEURON MOD files. The code for the templates, GUI and simulations is written in the NEURON HOC language or Python. The files containing the synaptic parameters and m-type mappings are tab-separated files.

The complete set of neuron models is available here

You can select specific neuron models in the interface below or by browsing to the relevant me-type fact sheet.

NeuroML2 version

Thanks to a collaboration with Padraig Gleeson of the Open Source Brain, the model packages can be converted to NeuroML2:

https://github.com/OpenSourceBrain/BlueBrainProjectShowcase/blob/master/NMC/NeuroML2/README.md

A file with the NeuroML2 versions of the model packages is available here

smw-download-portlet smw-download-portlet

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Circuit

.JSON file containing information about the circuit can be downloaded here:

Circuit data

Units are the same as in the circuit factsheet.

Layers

.JSON files containing information about the layers can be downloaded here:

Layers data

Units are the same as in the layers factsheets.

Pathways

.JSON files containing anatomical and physiological data for all the pathways can be downloaded here:

Anatomy data

Physiology data

Units are the same as in the pathways factsheets.

Connectome

Connectivity of an instance of a modeled microcircuit is available as an HDF5 file.

Gal, E., London, M., Globerson, A., Ramaswamy, S., Reimann, M.W., Muller, E., Markram, H., and Segev, I. (2017).

Rich cell-type-specific network topology in neocortical microcircuitry. Nat. Neurosci.

https://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4576.html

Reimann, M.W., Horlemann, A.-L., Ramaswamy, S., Muller, E.B., and Markram, H. (2017).

Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity. Cereb. Cortex 1-16.

https://academic.oup.com/cercor/article/doi/10.1093/cercor/bhx150/3872356/Morphological-Diversity-Strongly-Constrains


To download click the file name

TERMS OF USE

VISION

Welcome to the Blue Brain Project ("BBP"") Neocortical Microcircuit Collaboration Portal ("Portal"").

This Portal provides an online public resource of the BBP's first release of a digital reconstruction of the microcircuitry of juvenile Rat somatosensory cortex, access to experimental databases used in the reconstruction, and the resulting models (collectively "Databases and Models""). The following functionality is provided through this Portal to support community engagement to use and refine the reconstruction.

The BBP is committed to ensuring that the outputs of the its research are managed and used in ways that maximize public benefit. Making Data widely available to the research community in a timely and responsible manner ensures that these data can be verified, built upon and used to advance knowledge and its application to generate improvements.

By accessing and using the Portal, you agree to the following terms and conditions of use ("Terms"") and to any future revision. We may chance, suspend, discontinue, limit or remove any part of the Portal at any time, without prior notice or liability. Your continued use of the Portal following any changes is an agreement by you to the change in Terms.

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Subject to the Citation section below, under these Terms BBP grants you a world-wide, non-commercial, non-exclusive, nonsublicensable, royalty-free license on the Databases and Models to:

i) use, copy, distribute, publicly perform, publicly display, republish the Databases and Models for non-commercial purposes only;

ii) create derivative works for non-commercial purposes only.

Non-commercial purpose means: purpose not primarily intended for or directed towards sale, commercial advantage or monetary compensation. Use of Databases and Models for research and academic publication, in scholarly journal, textbook or other professional, academic or journalist publications (with appropriate Citation) is not considered commercial use.

Except for the limited permissions expressly stated in these Terms, all rights not specifically granted in these Terms are reserved. BBP/EPFL shall remain the sole owner of all and any intellectual property rights on Databases and Models. Additionally, BBP/EPFL retain its rights, title and interest in any Databases and Models that is part or it is used by you to create derivative works.

These Terms prohibits you to offer or impose any additional or different terms, conditions or purposes on derivative works if doing so restricts exercise of the licensed Databases and Models by BBP and any recipient of the Databases and Models.

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CITATION

While BBP is committed to ensure that its Data are used in ways that maximize public benefit, in all cases where Data are used publicly BBP requests to give credit to the original authors by acknowledging the scientists who have provided the Data with an appropriate citation as detailed below ("Citation"").

The Citation shall be as follows:

1. Markram H, et al. (2015). Reconstruction and Simulation of Neocortical Microcircuitry. Cell 163:2, 456 - 492. doi: 10.1016/j.cell.2015.09.029

2. Ramaswamy S, et al., (2015). The Neocortical Microcircuit Collaboration Portal: A Resource for Rat Somatosensory Cortex. Front. Neural Circuits 9:44. doi: 10.3389/fncir.2015.00044

3. Reimann MW, et al., (2015). An Algorithm to Predict the Connectome of Neural Microcircuits. Front. Comput Neurosci. 9:28. doi: 10.3389/fncom.2015.00120

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