This toolbox includes routines for using principal component analysis (PCA) and independent component analysis (ICA) to extract cellular signals from imaging data sets. A full description and validation of the method is provided in the paper, "Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data," Neuron, 63:747 (2009): h…
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doc
CellsortApplyFilter.m
CellsortChoosePCs.m
CellsortFindspikes.m
CellsortICA.m
CellsortICA_Optimize.m
CellsortICAplot.m
CellsortPCA.m
CellsortPlotPCspectrum.m
CellsortSegmentation.m
README.md
README.rtf

README.md

CellSort 1.1

Independent Component Analysis for Optical Imaging Data Sets

Copyright Eran Mukamel, 2009 email: emukamel@ucsd.edu

INSTALLATION ---------------------- Add the folder "CellSort 1.1" to the MATLAB path by selecting "Set Path" in the file menu.

INSTRUCTIONS ---------------------- D

ocumentation about each of the routines in this package is available in the "doc" directory. For more information, see "Automated analysis of cellular signals from large-scale calcium imaging data" by Eran Mukamel, Axel Nimmerjahn and Mark Schnitzer, NEURON (2009).

UPDATE 1.3 - APRIL 2013 ------------------------------- Fixed a problem with the function tiff_frames that altered its behavior in MATLAB 2012.

UPDATE 1.4 - JUNE 2016 ------------------------------- Fixed an inconsistency in CellsortPCA between create_tcov and creat_xcov. In the current version, both methods agree with the previous version of create_tcov.