Manual cell sorting of cell extraction outputs

Manual cell sorting of cell extraction outputs

This page will go over best practices and common issues seen when sorting cells from PCA-ICA. Advice can also apply to other cell sorting algorithms (CNMF, etc.).

Usage

Usage instructions below for signalSorter.m:

Main inputs

• inputImages - [x y N] matrix where N = number of images, x/y are dimensions.
• inputSignals - [N frames] double matrix where N = number of signals (traces).
• inputMovie - [x y frames] matrix

Main outputs

• choices - [N 1] vector of 1 = cell, 0 = not a cell
• inputImagesSorted - [x y N] filtered by `choices'
• inputSignalsSorted - [N frames] filtered by choice

iopts.inputMovie = inputMovie; % movie associated with traces
iopts.valid = 'neutralStart'; % all choices start out gray or neutral to not bias user
iopts.cropSizeLength = 20; % region, in px, around a signal source for transient cut movies (subplot 2)
iopts.cropSize = 20; % see above
iopts.medianFilterTrace = 0; % whether to subtract a rolling median from trace
iopts.subtractMean = 0; % whether to subtract the trace mean
iopts.movieMin = -0.01; % helps set contrast for subplot 2, preset movie min here or it is calculated
iopts.movieMax = 0.05; % helps set contrast for subplot 2, preset movie max here or it is calculated
iopts.backgroundGood = [208,229,180]/255;
iopts.backgroundBad = [244,166,166]/255;
iopts.backgroundNeutral = repmat(230,[1 3])/255;
[inputImagesSorted, inputSignalsSorted, choices] = signalSorter(inputImages, inputSignals, 'options',iopts);

Best practices

• Always sort the cells with the trace, filter, and either images or video cut to transients in the movie.
• This gets around two types of cells: those with irregular firing patterns that might be thrown out (see below) or those whose filter and traces look good, but are either fragments of a high SNR cell (see Common issues) or not actually a cell (e.g. a particulate in the field of view that has transient-like movement).

Example of a good cell with GCaMP like rise/decay and for one-photon miniature microscope movies, has nice 2D Gaussian-like shape during transients in the movie.

Example of good cells on left and bad on right. Subplots: CELLMax output, mean movie frame centered on the cell and aligned to cell transients, and example CELLMax traces.

Additional examples of good cells.

Good cells with their matched movies aligned to algorithm (PCA-ICA in this case) detected transients.

As noted, without the transient aligned movie (see above), cells with unusual traces might be discarded, e.g. all three below are actual cells when the movie is visualized.

Common issues

• Cells with high SNR will sometimes have their cells split. Refer to algorithm specific to note how to get around this problem.