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--- |
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language: |
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- en |
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pipeline_tag: tabular-classification |
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tags: |
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- Computational Neuroscience |
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license: mit |
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--- |
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## Model description |
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This model is part of the `UnitRefine` project. |
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The model is trained on 11 mice in V1, SC, and ALM using Neuropixels on mice. |
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Each recording was labeled by at least two people and in different combinations. |
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The agreement amongst labelers is 80%. |
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# Intended use |
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Used to identify noise clusters automatically in SpikeInterface. |
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# How to Get Started with the Model |
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This can be used to automatically identify noise in spike-sorted outputs. If you have a sorting_analyzer, it can be used as follows: |
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``` python |
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from spikeinterface.curation import auto_label_units |
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labels = auto_label_units( |
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sorting_analyzer=sorting_analyzer, |
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repo_id="SpikeInterface/UnitRefine_noise_neural_classifier", |
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trust_model=True |
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) |
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``` |
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# Authors |
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Anoushka Jain and Chris Halcrow |
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