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https://github.com/cmancio00/sand-2024
Analysis of visual cortical neurons of mice
https://github.com/cmancio00/sand-2024
igraph network-analysis python3 r university-project
Last synced: 26 days ago
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Analysis of visual cortical neurons of mice
- Host: GitHub
- URL: https://github.com/cmancio00/sand-2024
- Owner: cMancio00
- License: gpl-3.0
- Created: 2024-04-09T12:45:05.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-05-28T10:38:49.000Z (7 months ago)
- Last Synced: 2024-07-06T00:31:17.487Z (6 months ago)
- Topics: igraph, network-analysis, python3, r, university-project
- Language: Jupyter Notebook
- Homepage:
- Size: 11.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Analysis of visual cortical neurons of mice
| Authors | email |
|---------------------|-----------------------------------------|
| Cristian Bargiacchi | [email protected] |
| Christian Mancini | [email protected] |
## Project description
This is the final project of [Statistical Analysis of Network Data](https://www.unifi.it/p-ins2-2022-624136-0.html) at
University of Florence.
The aim of the project is to analyse some network data with the techniques seen during the course.
We choose da dataset including the network of visual cortex of mice [[2]](#references).
Data represents cell-to-cell mapping of axonal tracts between neurons, created from cellular data like electron microscopy.
Graphs are provided by default in [graphML](http://graphml.graphdrawing.org/) format.
The result of scope of the study and the results can be found in the paper [Network anatomy and in vivo physiology of visual cortical neurons](#references).
### Scope of the paper
The study shows how the neurons of the brain of a mouse interacts between them in the primary visual cortex.
Data of the study are collected thanks to the advance of two techniques:
1. Two-photon calcium imaging, to "create" specific visual stimulus,
2. Large-scale electron microscopy (EM), to trace a portion of these neurons’ local network.
### Result of the paper
The are neurons that stops and regulate neural activity and some that promote it.
Researchers found that the neurons that promote neural activity have preference of
specific visual stimulus type (i.e. horizontal, vertical oblique).
This opens the doors of further research for understanding the brain.
### What we have
A graph of the synaps of a specific stimulus was created to understand better the structure and the connections
of the network. We do not have all the data and imaging of the study since wold be to big but just the network
of a synaps.
We will use statistical techniques seen during the course to analyse this kind of data.
> [!CAUTION]
> It's important to have a good understanding of the domain we are working in when analyzing data.
> Without this understanding, the analysis can be misleading and influenced by random factors.
> For more detailed information about the data components, you can refer to the [Notebook](notebooks/Cortical.ipynb) provided.
# Run the Notebook
> [!TIP]
> An IDE like Pycharm will detect the [requirements](requirements.txt) and install a virtual environment for you in the project folder,
> we encourage you to use this mechanism to run the Notebook. Otherwise you can follow these steps to manually install the
> [requirements](#manually-install-the-requirement).
## Manually install the requirement
In the project folder run the following commands:
```bash
python3 -m venv .venv
```
> [!NOTE]
> The name of the virtual environment will be the same as the name of hidden folder,
>in this case `.venv`.
The virtual environment can be activated with:
```bash
source .venv/bin/activate
```
The requirements can be installed with:
```bash
pip install --upgrade pip & pip install -r requirements.txt
```
We just now need to make the virtual environment a Jupyter kernel.
```bash
python -Xfrozen_modules=off -m ipykernel install --user --name=sand-2024
```
Now you can choose `sand-2024` as a Kernel.
We can see the installed kernels with:
```bash
jupyter kernelspec list
```
The output should be something like this:
```
Available kernels:
python3 /home/mancio/PycharmProjects/sand-2024/.venv/share/jupyter/kernels/python3
sand-2024 /home/mancio/.local/share/jupyter/kernels/sand-2024
```
> [!NOTE]
> You can remove a kernel with the following command:
```bash
jupyter kernelspec uninstall sand-2024 -y
```
## Converting the Notebook to a pdf
The notebook can be converted with the following command
```bash
jupyter nbconvert --to pdf notebooks/Cortical.ipynb --LatexPreprocessor.title "Analysis of visual cortical neurons of mice" --LatexPreprocessor.date "May, 2024" --LatexPreprocessor.author_names "Cristian Bargiacchi,Christian Mancini"
```
# References
[1] [Neurodata repository](https://neurodata.io/project/connectomes/).
[2] [Mouse_visual.cortex_2](https://s3.amazonaws.com/connectome-graphs/mouse/mouse_visual.cortex_2.graphml)
[3] [Network anatomy and in vivo physiology of visual cortical neurons](https://www.nature.com/articles/nature09802).