This "jezzard" directory contains a small fMRI data set that is 
suitable for the analyses in the toolbox.

The data acquisition issues is described in the paper referenced below.

The 64 gradient-echo EPI 64x64 scans were obtained with a 4T scanner 
and the subject was exposed to a "photic stimulation (at 16 hz) provided 
by goggles fitted with light emitting diodes" - A quite strong stimulus 
and there is a high signal-to-noise ratio compared with usual fMRI.

The first four scans should be omitted due to magnetic saturation effect.


We thank Peter Jezzard and Robert Turner for letting us use their
data set.


If you use this data set in a scientific paper you could/should cite 
the paper that the provider has published in "Human Brain Mapping":

@Article{Friston1994Analysis,
  author =       {K. J. Friston and  P. Jezzard and R. Turner},
  title =        {The Analysis of functional {MRI} time-series},
  journal =      {Human Brain Mapping},
  year =         {1994},
  OPTkey =       {},
  volume =       {1},
  OPTnumber =    {},
  OPTmonth =     {},
  pages =        {153--171},
  OPTnote =      {},
  OPTannote =    {},
  url =          {http://www.fil.ion.ucl.ac.uk/spm/papers/fMRI_2/}
  keyword =      {functional MRI, fMRI, time-series, statistical
                  parametric mapping, SPM, significance, visual,
                  cross-correlations, autocorrelations},
  abstract =     {We present a method for detecting significant and
                  regionally specific correlations between sensory
                  input and the brain's physiological response, as
                  measured with functional MRI. The method involves
                  testing for correlations, between sensory input and
                  the hemodynamic response, after convolving the
                  sensory input with an estimate of the hemodynamic
                  response function. This estimate is obtained without
                  reference to any assumed input. 

                  To lend the approach statistical validity, it is
                  brought into the framework of statistical parametric
                  mapping by using a measure of cross-correlations,
                  between sensory input and hemodynamic response, that
                  is valid in the presence of intrinsic
                  autocorrelations. These autocorrelations are
                  necessarily present, due to the hemodynamic response
                  function or temporal point spread function.},
}
 
