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Watershed Spike Sorting Guide: Raw Data Plotting & Feature Modification

Learn how to effectively use the watershed algorithm for spike sorting by plotting raw data and modifying feature space in MATLAB. Follow this step-by-step guide for efficient analysis.

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Watershed Spike Sorting Guide: Raw Data Plotting & Feature Modification

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  1. Watershed moment in spike-sorting

  2. Plotting Raw Data

  3. Modifying Feature Space

  4. Watershed algorithm

  5. Apples From Mathworks

  6. Computer Finds Apples From Mathworks

  7. Making an Image from the spikes

  8. Watershed on Image

  9. Watershed on Image

  10. Quick reference guide to watershed add on: Installation: • Go to website koulakovlab.cshl.edu/watershed and download Mclust.zip • Unzip it to any directory • Include directory AND ALL SUBDIRECTORIES into matlab path • Type MClust at the MATLAB prompt • You are ready to go

  11. USAGE • In the main MClust window select additional features ud like to use • PCApeak – PCA on the maxima for each channel • PCAwave – PCA on the voltage profile • PCAshft – PCA of the voltage shifted so that the maximal voltage for an event is in the middle of the profile • PCAchsh – PCA on voltage shifted that the maximum of voltage FOR EACH CHANNEL is in the middle (individual time-shifts for each channel) • Press View Clusters 3D

  12. Watersheding • USE PCApeak components (2,3,4) for best results • Press Watershed button • Examine the voxelated density using the interface • Close the interface for proceed further

  13. Filtering data • When asked about the smoothing size respond (2-5 is best) • When asked about high-pass filter size respond (3-5 is best). Type 0 for none • When asked for the depth of the marker type a number btw 0 and 1. type 0 for no marker based WS. The value of 0.1 is acceptable in most cases. • Wait a few seconds. • Type Update Clusters • Type Redraw Clusters • Enjoy!

  14. Acknowledgements • Dr. Koulakov • Mainen Laboratory (recording data) • Spike-Sorting scientists • CSHL administration

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