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Expand Up @@ -14,15 +14,6 @@
Computational generation of artificial neuronal trees based on the topology of reconstructed cells and their
statistical properties.


## Installation

It is recommended to install ``NeuroTS`` using [pip](https://pip.pypa.io/en/stable/):

```bash
pip install neurots
```

## Main usage

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 (NeuroTS) 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 spatio-temporal scales.
Expand All @@ -31,7 +22,6 @@ NeuroTS can be used for the creation of neuronal morphologies from biological re

Once the `input_parameters` and `input_distributions` have been defined, then NeuroTS can generate one or multiple cells based on the respective inputs. The generated cells can be saved in a variety of file formats (SWC, ASC, H5) so that they can be analyzed and visualized by a variety of different softwares. You can find examples on how to extract distributions, generate cells and run basic validations below.


## Examples

We provide some basic examples to showcase the basic functionality of ``NeuroTS``:
Expand All @@ -44,6 +34,14 @@ We provide some basic examples to showcase the basic functionality of ``NeuroTS`
More information can be found in [Examples](https://neurots.readthedocs.io/en/stable/examples/index.html) page of the doc.


## Installation

It is recommended to install ``NeuroTS`` using [pip](https://pip.pypa.io/en/stable/):

```bash
pip install neurots
```

## Citation

When you use the ``NeuroTS`` software or method for your research, we ask you to cite the publication associated to this repository (use the `Cite this repository` button on the [main page](https://github.com/BlueBrain/NeuroTS) of the code).
Expand All @@ -54,4 +52,4 @@ The development of this software was supported by funding to the Blue Brain Proj

For license and authors, see `LICENSE.txt` and `AUTHORS.md` respectively.

Copyright © 2021 Blue Brain Project/EPFL
Copyright © 2022 Blue Brain Project/EPFL