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Abnormally and spike events - Detect the abnormality in the system, given spontaneous data. #68

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skim0119 opened this issue Jun 28, 2022 · 2 comments
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@skim0119
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@skim0119 skim0119 mentioned this issue Jun 28, 2022
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@jihugo
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jihugo commented Jun 30, 2022

@skim0119 Here's my approach that I'd like to check with you before I go deeper into this:

  1. Generate PCA cutouts for spontaneous recording
  2. For each component, have the user label spontaneous spikes into ['neuronal', 'false', 'mixed']
  • User isn't required to do label components for every single channel
  • We can possibly make algorithms to suggest the user which channel to consider labeling
  1. Train the model
  2. For the experimental recordings:
  • Catch the channels with higher uncertainties. These may indicate some new spike shape.
  • (Possibly) Filter out channels with same ratio of neuronal to false spikes as spontaneous
  • Generate new spiketrains with the false spikes removed

@skim0119
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skim0119 commented Jul 2, 2022

@jihugo Sounds reasonable to me! 👍

@skim0119 skim0119 added the enhancement New feature or request label Jul 2, 2022
@skim0119 skim0119 added this to the Version 0.2 milestone Jul 2, 2022
@skim0119 skim0119 mentioned this issue Jul 24, 2022
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@skim0119 skim0119 modified the milestones: Version 0.2, Version 0.3 Aug 2, 2022
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