README.md

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title: README
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This space hosts pre-trained models used for electrophysiology analysis and spike sorting through the [SpikeInterface](https://spikeinterface.readthedocs.io/en/latest/) Python package.

Examples of models that can be part of this repo are:
- models for curation of spike sorting results, e.g., built on quality metrics
- models for Deep Learning based denoising, like [DeepInterpolation](https://www.nature.com/articles/s41592-021-01285-2)
- models used internally by spike sorting algorithms, such as Neural Network-based waveform denoising (as in [YASS](https://www.biorxiv.org/content/10.1101/2020.03.18.997924v1))

## Available models

### [Curation models](https://huggingface.co/collections/SpikeInterface/curation-models)

Models to automatically curate spike sorting outputs through the `spikeinterface.curation.unitrefine_label_units` function.

### [SortingComponents models](https://huggingface.co/collections/SpikeInterface/sortingcomponents-models)

Models for the sortingcomponents module of SpikeInterface, e.g. for waveform denoising based in neural networks.



### Contacts

For questions, please contact [Chris Halcrow](chalcrow@ed.ac.uk), [Heberto Mayorquin](h.mayorquin@gmail.com), or [Alessio Buccino](alessio.buccino@alleninstitute.org)