Synthetic data

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It is often useful to create synthetic fMRI datasets, in order to test analysis approaches to ensure that they are behaving as expected. I have created a MATLAB program called fakedata.m that provides this functionality. The usage is as follows: 

 [data]=fakedata(files,noise_sd,roi,desmtx,beta,smoothing,filestem,ar_weight)

 function to create a timeseries based on a single image 
 with signal injected according to a particular design matrix and parameters

 requires SPM2/99 in the matlab path (may work with spm5, but has not been tested)

 arguments:
 files - the basis file for the timeseries (usually a single 3D fMRI image)
  - if [] is passed, a gui window will appear to allow choice of files
 noise_sd - SD of gaussian noise, as a % of mean signal
 roi - the region to inject the signal into can be specified in two ways:
     1 - name of a mask file that specifies the voxels into which the
     signal should be injected  - this mask can be binary or can be
     continuous with max of 1
     2 - a 1 X 4 vector containing an MNI location and radius 
     (e.g., [-32 12 20 5] for a 5mm sphere at [-32 12 20]
     NB: THIS WILL LIKELY CRASH UNLESS THE BASE IMAGE IS IN MNI SPACE
 desmtx - design matrix for signal injection (e.g. xX.X from SPM.mat)
  - desmtx is N x C matrix (N=% observations by C=% regressors)
 beta - matrix of weightings for each column of design matrix
  - beta is C x 1 matrix (C=% of regressors)
 smoothing - FWHM of spatial smoothing filter to apply to the signal
     before injection (will write smoothed version of mask to disk)
     if smoothing is not specified, default is no smoothing
 filestem - stem for filename for synthetic data files
     (set to [] to prevent creating output files)
 ar_weight - optional parameter for AR1 model, takes values from 0-1, 
     - higher parameter results in greater temporal autocorrelation
     - default is 0.7, which gives a reasonable falloff

This creates a timeseries with signal injected as specified by the design matrix and beta matrix.

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