| | --- |
| | language: |
| | - en |
| | pipeline_tag: tabular-classification |
| | tags: |
| | - Computational Neuroscience |
| | license: mit |
| | --- |
| | |
| | ## Model description |
| | This model is part of the `UnitRefine` project. |
| | The model is trained on 11 mice in V1, SC, and ALM using Neuropixels on mice. |
| | Each recording was labeled by at least two people and in different combinations. |
| | The agreement amongst labelers is 80%. |
| |
|
| | # Intended use |
| | Used to identify SUA clusters automatically in SpikeInterface. |
| |
|
| | # How to Get Started with the Model |
| | This can be used to automatically identify SUA units in spike-sorted outputs. If you have a sorting_analyzer, it can be used as follows: |
| | |
| | ``` python |
| | from spikeinterface.curation import auto_label_units |
| | labels = auto_label_units( |
| | sorting_analyzer = sorting_analyzer, |
| | repo_id = "SpikeInterface/UnitRefine_sua_mua_classifier", |
| | trusted = ['numpy.dtype'] |
| | ) |
| | ``` |
| | ## 📜 Citation |
| | |
| | If you find [UnitRefine](https://github.com/anoushkajain/UnitRefine) models useful in your research, please cite the following DOI: |
| | **[10.6084/m9.figshare.28282841.v2](https://doi.org/10.6084/m9.figshare.28282841.v2)**. |
| | |
| | We will be releasing a **preprint soon**. In the meantime, please use the above DOI for referencing. |
| | |
| | ## 🔗 Resources |
| | |
| | - **GitHub Repository:** [UnitRefine](https://github.com/anoushkajain/UnitRefine) |
| | - 📖 **SpikeInterface Tutorial – Automated Curation:** |
| | [View Here](https://spikeinterface.readthedocs.io/en/latest/tutorials_custom_index.html#automated-curation-tutorials) |
| | |
| | UnitRefine is **fully integrated with SpikeInterface**, making it easy to incorporate into existing workflows. 🚀 |
| | |
| | # Authors |
| | |
| | Anoushka Jain and Chris Halcrow |
