Afni3dWavelets

Afni3dWavelets is a wrapper for the AFNI (RW Cox, NIH) waver application.
Program to perform wavelet analysis of an FMRI 3d+time dataset.
B. Douglas Ward
For more information about the AFNI package, see the AFNI Homepage

To see the AFNI postscript documentation please go here.

To read the help documentation generated from the command line go here.

Invocation

	java  Afni3dWavelets

This starts up the java interpreter and runs the Afni3dWavelets application. You need to have set up your environment for java in order for this to work.

Afni3dWavelets window

Information to be entered

Input
- 3D+time dataset
  Specify the location of a 3d+time AFNI dataset to perform wavelet analysis on.
- 1D timeseries
  Specify the location of a single 1D fMRI timeseries to perform wavelet analysis on.
Output
- Bucket dataset prefix
  Here, specify the prefix of AFNI 'bucket' dataset containing parameters of interest, such as the F-statistic for significance of the wavelet signal model.
Options...
Press this button to access more options.
- Input Options
  - 3D mask dataset
    Specify the location of a 3d mask dataset to perform wavelet analysis on.
  - First dataset image for analysis
    Specify the number of first dataset image to use in the wavelet analysis here. Default is 0, the first image in the dataset.
  - Last dataset image for analysis
    Specify the number of last dataset image to use in the wavelet analysis here. Default is the last image in the dataset.
- Output Options
  - Full model wavelet coefficients
    Sets the flag to output the full model wavelet coefficients
  - F-statistics
    Sets the flag to output the F-statistics.
  - Sample variance map
    Sets the flag to output the sample variance (MSE) map
  - R^2 statistics
    Sets the flag to output the R^2 statistics
  - Allow full model statistics to appear before wavelet coefficients
    Sets the f
  - Save forward wavelet transform coefficients
    Here, specify the prefix of 3d+time output dataset which will contain the forward wavelet transform coefficients
  - Save full model
    Here, specify the prefix of 3d+time output dataset which will contain the full model time series fit to the input data
  - Save signal model
    Here, specify the prefix of 3d+time output dataset which will contain the signal model time series fit to the input data
  - Save residual errors
    Here, specify the prefix of 3d+time output dataset which will contain the residual error time series from the full model fit to the input data
- Screen Display Options
  - Write results of voxels for F-statistic
    Specify that the full model statistics will appear prior to the wavelet coefficients in the bucket dataset output.
Algorithm Options...
Press this button to access more options.
- Type of wavelet for analysis
  Choose the name of wavelet to use for the analysis here. There are two choices: Haar wavelets or Daubechies wavelets
- Wavelet coefficient specification
  - Set to zero
    Specify wavelet coefficients to set to zero here.
  - Baseline model
    Specify wavelet coefficients for baseline model here.
  - Signal model
    Specify wavelet coefficients for signal model here.
  - Values to specify
    - frequency band
      Specify frequency band here.
    - minimum TR
      Specify minimum value for time window in TR.
    - maximum TR
      Specify maximum value for time window in TR.

Last updated Tue Jun 03 13:58:44 EDT 2003