https://github.com/bluebrain/diameter-synthesis
Synthesize diameters of neuronal morphologies
Science Score: 75.0%
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Synthesize diameters of neuronal morphologies
Basic Info
Statistics
- Stars: 3
- Watchers: 7
- Forks: 2
- Open Issues: 1
- Releases: 14
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Metadata Files
README.md
[!WARNING] The Blue Brain Project concluded in December 2024, so development has ceased under the BlueBrain GitHub organization. Future development will take place at: https://github.com/openbraininstitute/diameter-synthesis
Diameter synthesis
This code aims at generating synthetic diameters for neurons, with parameters learned from a set of biological neurons.
Installation
Use pip:
bash
pip install diameter-synthesis
Main usage
Step 1: Building models
In folder example, you first have to modify create_jsons.py to suit your needs.
You have the following important parameters for the dict extract_models_params:
morph_path: path to morphology filesmtypes_sort: how to learn distributions:allto use all together,mtypesto use by mtypes ,super_mtypesto use home made cells types (seediameter_typesbelow)models: to create several models (for now they are all the same, just different realisation of random numbers)neurite_types: types of neurite to learn parameters forextra_params: dict of additional model parameters
Step 2: Building diameters
Then simply run ./run_models.sh to create the models (saved in a json file).
In create_jsons.py, the dict generate_diameters_params needs to be updated, too, with entries matching the previous dict.
The path in new_morph_path will be where the new morphologies will be saved.
Then run ./run_diamters.sh to generate diameters.
Additional scripts
Several additional scripts in folder scripts:
diameter-checks: run the diameter-check code (bluepymm) on the biological and sampled cellsdiameter_types: cluster mtypes using distributions of surface areas (uses two privates repositories a the moment)extract_morphometrics: from bio and sample cells, extracts and plot distribution of surface area and diameter as a function of branch order and path lengthsextract_morphologies: from a cell release, find the ones that can be run through diameter-checkplot_morphologies: plot all morphologies in mtype folders
Examples
The examples folder contains a simple example that will fetch morphologies from neuromorpho.org, learn a diameter model, rediametrize these morphologies, and perform some analysis of the results to compare original and diametrized morphologies.
This example can simply be run using the following command:
bash
./run.sh
Funding & Acknowledgment
The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
For license and authors, see LICENSE.txt and AUTHORS.md respectively.
Copyright © 2021-2022 Blue Brain Project/EPFL
Owner
- Name: The Blue Brain Project
- Login: BlueBrain
- Kind: organization
- Email: bbp.opensource@epfl.ch
- Location: Geneva, Switzerland
- Website: https://portal.bluebrain.epfl.ch/
- Repositories: 226
- Profile: https://github.com/BlueBrain
Open Source Software produced and used by the Blue Brain Project
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: >-
Computational synthesis of cortical dendritic
morphologies.
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- family-names: Kanari
given-names: Lida
orcid: 'https://orcid.org/0000-0002-9539-5070'
- family-names: Dictus
given-names: Hugo
- family-names: Chalimourda
given-names: Athanassia
- family-names: Van Geit
given-names: Werner
orcid: 'https://orcid.org/0000-0002-2915-720X'
- family-names: Coste
given-names: Benoit
- family-names: Shillcock
given-names: Julian
orcid: 'https://orcid.org/0000-0002-7885-735X'
- given-names: Kathryn
family-names: Hess
orcid: 'https://orcid.org/0000-0003-2788-9754'
- family-names: Markram
given-names: Henry
orcid: 'https://orcid.org/0000-0001-6164-2590'
- family-names: Arnaudon
given-names: Alexis
orcid: 'https://orcid.org/0000-0001-9486-1458'
identifiers:
- type: doi
value: 10.1016/j.celrep.2022.110586
description: The DOI of the related article.
repository-code: 'https://github.com/BlueBrain/diameter-synthesis'
abstract: >-
Neuronal morphologies provide the foundation for the electrical behavior of
neurons, the connectomes they form, and the dynamical properties of the brain.
Comprehensive neuron models are essential for defining cell types, discerning
their functional roles, and investigating brain-disease-related dendritic
alterations. However, a lack of understanding of the principles underlying
neuron morphologies has hindered attempts to computationally synthesize
morphologies for decades. We introduce a synthesis algorithm based on a
topological descriptor of neurons, which enables the rapid digital
reconstruction of entire brain regions from few reference cells. This
topology-guided synthesis generates dendrites that are statistically similar to
biological reconstructions in terms of morpho-electrical and connectivity
properties and offers a significant opportunity to investigate the links between
neuronal morphology and brain function across different spatiotemporal scales.
Synthesized cortical networks based on structurally altered dendrites associated
with diverse brain pathologies revealed principles linking branching properties
to the structure of large-scale
networks.
keywords:
- Dendritic morphology
- Topological synthesis
- Artificial neuron
- Topological Morphology Descriptor
- Morphological synthesis
license: GPL-3.0
GitHub Events
Total
- Release event: 1
- Delete event: 3
- Issue comment event: 1
- Push event: 6
- Pull request review event: 1
- Pull request event: 8
- Create event: 5
Last Year
- Release event: 1
- Delete event: 3
- Issue comment event: 1
- Push event: 6
- Pull request review event: 1
- Pull request event: 8
- Create event: 5
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 178
- Total Committers: 8
- Avg Commits per committer: 22.25
- Development Distribution Score (DDS): 0.315
Top Committers
| Name | Commits | |
|---|---|---|
| Alexis Arnaudon | a****n@e****h | 122 |
| Adrien Berchet | a****t@e****h | 45 |
| Adrien Berchet | a****t@g****m | 3 |
| Eleftherios Zisis | e****s@e****h | 3 |
| aleksei sanin | a****n@e****h | 2 |
| alexis arnaudon | a****n@g****m | 1 |
| Dries Verachtert | d****t@e****h | 1 |
| bbpgithubaudit | 8****t@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 4
- Total pull requests: 51
- Average time to close issues: about 1 month
- Average time to close pull requests: 5 days
- Total issue authors: 2
- Total pull request authors: 5
- Average comments per issue: 5.5
- Average comments per pull request: 0.65
- Merged pull requests: 49
- Bot issues: 0
- Bot pull requests: 9
Past Year
- Issues: 0
- Pull requests: 13
- Average time to close issues: N/A
- Average time to close pull requests: about 2 hours
- Issue authors: 0
- Pull request authors: 3
- Average comments per issue: 0
- Average comments per pull request: 0.15
- Merged pull requests: 13
- Bot issues: 0
- Bot pull requests: 6
Top Authors
Issue Authors
- adrien-berchet (2)
- riddick-the-furyan (1)
- dependabot[bot] (1)
Pull Request Authors
- adrien-berchet (35)
- arnaudon (13)
- dependabot[bot] (12)
- eleftherioszisis (1)
- bbpgithubaudit (1)