Difference between revisions of "Time Frequency Analysis"

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Latest revision as of 16:57, 20 February 2018

Time Frequency Analysis Tools

Time Frequency analysis are a useful way of determining where interesting things are happening in your data in time-frequency space. Typically, spatial information is discarded. One way of doing time-frequency analysis is through Stockwell analyses, although other methods are available.

  • ctf2st is a Matlab GUI for performing Stockwell time-frequency analysis. This can be performed on all sensors, a section of sensors, or on virtual sensors after source localization - download ctf2st.tgz. Unzip, and add both ctf2st and ctf2st/st to your Matlab path. You may need to recompile the mex files by typing make clean and make in the st subdirectory. A version recompobiled to work on the NIH Biowulf system is here: ctf2stBW.tgz.
  • StockwellDs.py performs Stockwell time-frequency analysis in Python. This is included in the pyctf distribution. The default is to average all trials and compute the Stockwell on the average, giving an AFNI .BRIK and .HEAD dataset as output, Matlab output can also be requested (execute the command with no arguments to see a detailed usage message).
Usage: StockwellDs.py [options] dataset.ds
Note that Stockwell plots from two conditions can be compared using the AFNI routine 3dWilcoxon
Usage: 3dWilcoxon -out Condition1vsCondition2 StockwellCond1+orig.HEAD StockwellCond2+orig.HEAD