metadata

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 noise clusters automatically in SpikeInterface.

How to Get Started with the Model

This can be used to automatically identify noise in spike-sorted outputs. If you have a sorting_analyzer, it can be used as follows:

    from spikeinterface.curation import auto_label_units

    labels = auto_label_units(
        sorting_analyzer=sorting_analyzer,
        repo_id="SpikeInterface/UnitRefine_noise_neural_classifier",
        trust_model=True
    )

Authors

Anoushka Jain and Chris Halcrow