2007-11-12 version 1.2-3

  - read.AFNI() has a new argument 'vol' which contains a vector of 
    volumes to be read. This hopefully enables to read parts of large datastes 
    without running into memory problems.
  - if in fmri.pvalue() the df is larger than 171, a Gaussian Random Field instead of t-field is used.
    gamma() is not defined otherwise. On the other df is large enough!
  - bugfix in read.NIFTI which contained a misinterpretation of the header entries 
    (bitpix, dim)
  - new function write.NIFTI()

2007-09-05 version 1.2-2

  - write.AFNI() completely re-written, it has new arguments header (AFNI-header 
    list with entries such as DATASET_RANK etc.) and logical taxis, which controls,
    whether sub-bricks contain time series data. All other (old) arguments are 
    depreciated, but the function should behave as in former version when called 
    as such. This will be removed in some future version!
  - read.AFNI() now does not include ' and ~ in string-attributes in header

2007-07-02 version 1.2-1

  - bugfix in fmri.lm() which was unable to calculate spatial correlation for
    some datasets with optimize().

2007-04-23 version 1.2-0

  - to save memory fmri datasets are now stored in in the $ttt list element in 
    raw() format. This allows for handling much larger time series. To directly
    access the data (including dimension) use the extract.data() function.
