{"id":22180249,"url":"https://github.com/cmancio00/sand-2024","last_synced_at":"2026-05-09T05:31:37.982Z","repository":{"id":233484908,"uuid":"784227188","full_name":"cMancio00/sand-2024","owner":"cMancio00","description":"Analysis of visual cortical neurons of mice","archived":false,"fork":false,"pushed_at":"2024-05-28T10:38:49.000Z","size":12224,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-25T05:46:34.347Z","etag":null,"topics":["igraph","network-analysis","python3","r","university-project"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cMancio00.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-09T12:45:05.000Z","updated_at":"2024-05-28T10:38:53.000Z","dependencies_parsed_at":"2024-05-28T13:25:11.102Z","dependency_job_id":"0672f718-71f2-49c8-afe8-47fca28e5977","html_url":"https://github.com/cMancio00/sand-2024","commit_stats":null,"previous_names":["cmancio00/sand-2024"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/cMancio00/sand-2024","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cMancio00%2Fsand-2024","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cMancio00%2Fsand-2024/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cMancio00%2Fsand-2024/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cMancio00%2Fsand-2024/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cMancio00","download_url":"https://codeload.github.com/cMancio00/sand-2024/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cMancio00%2Fsand-2024/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32808390,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"online","status_checked_at":"2026-05-09T02:00:06.633Z","response_time":123,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["igraph","network-analysis","python3","r","university-project"],"created_at":"2024-12-02T09:17:41.505Z","updated_at":"2026-05-09T05:31:37.954Z","avatar_url":"https://github.com/cMancio00.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Analysis of visual cortical neurons of mice\n\n| Authors             | email                                   | \n|---------------------|-----------------------------------------|\n| Cristian Bargiacchi | \u003ca href=\"mailto:cristian.bargiacchi@edu.unifi.it\"\u003ecristian.bargiacchi@edu.unifi.it\u003c/a\u003e | \n| Christian Mancini   | \u003ca href=\"mailto:christian.mancini1@edu.unifi.it\"\u003echristian.mancini1@edu.unifi.it\u003c/a\u003e |  \n\n## Project description\n\nThis is the final project of [Statistical Analysis of Network Data](https://www.unifi.it/p-ins2-2022-624136-0.html) at \nUniversity of Florence.\n\nThe aim of the project is to analyse some network data with the techniques seen during the course.\n\nWe choose da dataset including the network of visual cortex of mice [[2]](#references).\n\nData represents cell-to-cell mapping of axonal tracts between neurons, created from cellular data like electron microscopy.\n\nGraphs are provided by default in [graphML](http://graphml.graphdrawing.org/) format.\n\nThe 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).\n\n### Scope of the paper\n\nThe study shows how the neurons of the brain of a mouse interacts between them in the primary visual cortex.\n\nData of the study are collected thanks to the advance of two techniques:\n\n1. Two-photon calcium imaging, to \"create\" specific visual stimulus,\n2. Large-scale electron microscopy (EM), to trace a portion of these neurons’ local network.\n\n### Result of the paper\n\nThe are neurons that stops and regulate neural activity and some that promote it.\n\nResearchers found that the neurons that promote neural activity have preference of \nspecific visual stimulus type (i.e. horizontal, vertical oblique).\n\nThis opens the doors of further research for understanding the brain.\n\n### What we have\n\nA graph of the synaps  of a specific stimulus was created to understand better the structure and the connections \nof the network. We do not have all the data and imaging of the study since wold be to big but just the network \nof a synaps.\n\nWe will use statistical techniques seen during the course to analyse this kind of data.\n\n\u003e [!CAUTION]\n\u003e It's important to have a good understanding of the domain we are working in when analyzing data.\n\u003e Without this understanding, the analysis can be misleading and influenced by random factors.\n\u003e For more detailed information about the data components, you can refer to the [Notebook](notebooks/Cortical.ipynb) provided.\n\n# Run the Notebook\n\n\u003e [!TIP]\n\u003e An IDE like Pycharm will detect the [requirements](requirements.txt) and install a virtual environment for you in the project folder,\n\u003e we encourage you to use this mechanism to run the Notebook. Otherwise you can follow these steps to manually install the \n\u003e [requirements](#manually-install-the-requirement).\n\n## Manually install the requirement\n\nIn the project folder run the following commands:\n\n```bash\npython3 -m venv .venv\n```\n\u003e [!NOTE]\n\u003e The name of the virtual environment will be the same as the name of hidden folder, \n\u003ein this case `.venv`.\n\nThe virtual environment can be activated with:\n\n```bash\nsource .venv/bin/activate\n```\nThe requirements can be installed with:\n\n```bash\npip install --upgrade pip \u0026 pip install -r requirements.txt\n```\n\nWe just now need to make the virtual environment a Jupyter kernel.\n\n```bash\npython -Xfrozen_modules=off -m ipykernel install --user --name=sand-2024\n```\nNow you can choose `sand-2024` as a Kernel.\n\nWe can see the installed kernels with:\n\n```bash\njupyter kernelspec list\n```\nThe output should be something like this:\n\n```\nAvailable kernels:\n  python3      /home/mancio/PycharmProjects/sand-2024/.venv/share/jupyter/kernels/python3\n  sand-2024    /home/mancio/.local/share/jupyter/kernels/sand-2024\n```\n\u003e [!NOTE]  \n\u003e You can remove a kernel with the following command:\n\n```bash\njupyter kernelspec uninstall sand-2024 -y\n```\n\n## Converting the Notebook to a pdf\n\nThe notebook can be converted with the following command\n\n```bash\njupyter 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\"\n```\n\n# References\n[1] [Neurodata repository](https://neurodata.io/project/connectomes/).\n\n[2] [Mouse_visual.cortex_2](https://s3.amazonaws.com/connectome-graphs/mouse/mouse_visual.cortex_2.graphml)\n\n[3] [Network anatomy and in vivo physiology of visual cortical neurons](https://www.nature.com/articles/nature09802).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcmancio00%2Fsand-2024","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcmancio00%2Fsand-2024","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcmancio00%2Fsand-2024/lists"}