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James Jun edited this page Nov 13, 2018 · 1 revision

Welcome to the IronClust wiki

IronClust is a fast and drift-resistant spike sorting pipeline. The accuracy of spike sorting is validated by multiple ground-truth datasets from a number of contributing labs. IronClust can take advantage of GPU or a compute cluster if available. IronClust requires Matlab with image, parallel, and signal processing toolboxes. IronClust supports Windows, Mac, and Linux.

Please use GitHub issue tracker if you encounter any problems.

IronClust is maintained by Flatiron Institute by the original developer of JRCLUST

JRCLUST paper on bioRxiv

Performance benchmark

  • Spike sorting error is quantified by the average of the false positive (FP) and false negative (FN) rates for each ground-truth unit.
  • Mean and SD are shown
    • Green: dataset without probe drift
    • Magenta: simulated probe drift (generated by combining 4 probe depths with 4 um increments)
  • Ground-truth dataset: biophysically detailed simulation (708 cells in 200 x 200 x 600 um volume)
    • generated by Catalin Mitelut from the Allen Institute for Brain Science (16 minutes, 20 KS/s)
    • Pooled four probe layout patterns (two-columns and four-column checkerboard pattern). 32 um horizontal spacing, 20 um vertical spacing (center-to-center)

Speed performance for running the entire pipeline (pre-processing + spike detection + clustering + post-merging/splitting)

System hardware: Dual Xeon 3.0 GHz (8 cores), 128 GB RAM, Titan X GPU (12 GB, Maxwell)
Windows 7 64-bit for running JRCLUST and Kilosort, Ubuntu 16 for MountainSort and YASS

Video tutorials on YouTube

Please maximize the resolution to 720p for optimal viewing

  1. JRCLUST tutorial: Creating a .prm file

  2. JRCLUST tutorial: Show a probe layout

  3. JRCLUST tutorial: Detect spikes

  4. JRCLUST tutorial: Sort spikes

  5. JRCLUST tutorial: Detect and sort spikes in one step

  6. JRCLUST tutorial: Show raw traces and power spectrum

  7. JRCLUST tutorial: Manual spike sorting

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