REMLfit Error

AFNI Message Board
1

Hi Daniel,

After orienting the epi data, I reran my preprocessing through afni_proc.py. I want to do pre-whitening through 3dREMLfit, but I’m getting the following error:
3dREMLfit -matrix X.xmat.1D -input pb04.sub_id.r01.scale+tlrc.HEAD -fout -tout -Rbuck stats.sub_id_REML -Rvar stats.sub_id_REMLvar -Rfitts fitts.sub_id_REML -Rerrts errts.sub_id_REML -verb
++ 3dREMLfit: AFNI version=AFNI_18.2.04 (Jul 6 2018) [64-bit]
++ Authored by: RWCox
++ Number of OpenMP threads = 23
++ No mask ==> computing for all 1050624 voxels
++ FDR automask has 648696 voxels (out of 1050624 = 61.7%)
++ ----- matrix condition (1359x721): 3157.43 ++ OK ++
*+ WARNING: !! in matrix:

  • Largest singular value=2.28069
  • 2 singular values are less than cutoff=2.28069e-07
  • Implies strong collinearity in the matrix columns!
    ++ matrix singular values:
    1.87612e-07 1.99549e-07 2.2877e-07 2.64371e-07 2.25929e-05
    0.000198812 0.00750844 0.0332996 0.0401774 0.0923025
    0.151598 0.207106 0.324679 0.440766 0.674007
    0.809561 0.999858 0.999925 0.999933 0.999934
    0.999937 0.99994 0.99994 0.99994 0.999941
    0.999942 0.999942 0.999943 0.999943 0.999945
    0.999945 0.999946 0.999946 0.999947 0.999947
    0.999948 0.999949 0.999949 0.999949 0.999949
    0.99995 0.99995 0.999951 0.999951 0.999952
    0.999952 0.999952 0.999953 0.999953 0.999953
    0.999954 0.999954 0.999954 0.999955 0.999955
    0.999955 0.999956 0.999956 0.999956 0.999956
    0.999956 0.999957 0.999957 0.999957 0.999958
    0.999958 0.999958 0.999958 0.999959 0.999959
    0.999959 0.99996 0.99996 0.99996 0.99996
    0.99996 0.999961 0.999961 0.999961 0.999962
    0.999962 0.999962 0.999962 0.999962 0.999962
    0.999963 0.999963 0.999963 0.999963 0.999964
    0.999964 0.999964 0.999964 0.999964 0.999965
    0.999965 0.999965 0.999965 0.999965 0.999966
    0.999966 0.999966 0.999966 0.999966 0.999967
    0.999967 0.999967 0.999967 0.999967 0.999968
    0.999968 0.999968 0.999968 0.999968 0.999969
    0.999969 0.999969 0.999969 0.999969 0.99997
    0.99997 0.99997 0.99997 0.99997 0.999971
    0.999971 0.999971 0.999971 0.999971 0.999972
    0.999972 0.999972 0.999972 0.999972 0.999972
    0.999973 0.999973 0.999973 0.999973 0.999973
    0.999973 0.999974 0.999974 0.999974 0.999974
    0.999974 0.999974 0.999975 0.999975 0.999975
    0.999975 0.999975 0.999975 0.999976 0.999976
    0.999976 0.999976 0.999976 0.999976 0.999977
    0.999977 0.999977 0.999977 0.999977 0.999977
    0.999978 0.999978 0.999978 0.999978 0.999978
    0.999978 0.999979 0.999979 0.999979 0.999979
    0.999979 0.999979 0.999979 0.999979 0.99998
    0.99998 0.99998 0.99998 0.99998 0.99998
    0.99998 0.99998 0.999981 0.999981 0.999981
    0.999981 0.999981 0.999981 0.999981 0.999982
    0.999982 0.999982 0.999982 0.999982 0.999982
    0.999982 0.999983 0.999983 0.999983 0.999983
    0.999983 0.999983 0.999983 0.999983 0.999984
    0.999984 0.999984 0.999984 0.999984 0.999984
    0.999984 0.999984 0.999985 0.999985 0.999985
    0.999985 0.999985 0.999985 0.999985 0.999985
    0.999986 0.999986 0.999986 0.999986 0.999986
    0.999986 0.999986 0.999986 0.999987 0.999987
    0.999987 0.999987 0.999987 0.999987 0.999987
    0.999987 0.999987 0.999987 0.999988 0.999988
    0.999988 0.999988 0.999988 0.999988 0.999988
    0.999988 0.999988 0.999989 0.999989 0.999989
    0.999989 0.999989 0.999989 0.999989 0.999989
    0.999989 0.99999 0.99999 0.99999 0.99999
    0.99999 0.99999 0.99999 0.99999 0.99999
    0.99999 0.999991 0.999991 0.999991 0.999991
    0.999991 0.999991 0.999991 0.999991 0.999991
    0.999991 0.999992 0.999992 0.999992 0.999992
    0.999992 0.999992 0.999992 0.999992 0.999992
    0.999992 0.999993 0.999993 0.999993 0.999993
    0.999993 0.999993 0.999993 0.999993 0.999993
    0.999993 0.999993 0.999994 0.999994 0.999994
    0.999994 0.999994 0.999994 0.999994 0.999994
    0.999994 0.999994 0.999994 0.999995 0.999995
    0.999995 0.999995 0.999995 0.999995 0.999995
    0.999995 0.999995 0.999995 0.999996 0.999996
    0.999996 0.999996 0.999996 0.999996 0.999996
    0.999996 0.999996 0.999996 0.999996 0.999996
    0.999997 0.999997 0.999997 0.999997 0.999997
    0.999997 0.999997 0.999997 0.999997 0.999997
    0.999997 0.999998 0.999998 0.999998 0.999998
    0.999998 0.999998 0.999998 0.999998 0.999998
    0.999998 0.999998 0.999998 0.999999 0.999999
    0.999999 0.999999 0.999999 0.999999 0.999999
    0.999999 0.999999 0.999999 0.999999 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1 1
    1 1 1 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00001
    1.00001 1.00001 1.00001 1.00001 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00002 1.00002 1.00002 1.00002
    1.00002 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00003 1.00003 1.00003
    1.00003 1.00003 1.00004 1.00004 1.00004
    1.00004 1.00004 1.00004 1.00004 1.00004
    1.00004 1.00004 1.00004 1.00004 1.00004
    1.00004 1.00004 1.00004 1.00004 1.00004
    1.00004 1.00004 1.00004 1.00004 1.00004
    1.00004 1.00004 1.00004 1.00004 1.00004
    1.00004 1.00005 1.00005 1.00005 1.00005
    1.00005 1.00005 1.00005 1.00005 1.00005
    1.00005 1.00005 1.00005 1.00005 1.00005
    1.00005 1.00005 1.00005 1.00005 1.00005
    1.00005 1.00005 1.00005 1.00005 1.00005
    1.00005 1.00006 1.00006 1.00006 1.00006
    1.00006 1.00006 1.00006 1.00006 1.00006
    1.00006 1.00006 1.00006 1.00006 1.00006
    1.00006 1.00006 1.00006 1.00006 1.00006
    1.00007 1.00007 1.00007 1.00007 1.00007
    1.00007 1.00008 1.0001 1.0001 1.00015
    1.0002 1.00396 1.00587 1.0229 1.07135
    1.17158 1.27479 1.38634 1.4097 1.41083
    1.41432 1.41615 1.43039 1.51861 1.68593
    2.28069
    ** FATAL ERROR: Can’t continue after matrix condition errors!
    ** you might try -GOFORIT, but be careful! (cf. ‘-help’)
    ** Program compile date = Jul 6 2018

What would be the cause of this error? And, how do I fix this error?

Thanks,
Daniel Zhu

2

Hi Daniel,

It is difficult to say. Are there any duplicate or empty regressors in X.xmat.1D?
What is the output from:

1d_tool.py -show_cormat_warnings -infile  X.xmat.1D
  • rick
3

I’ve run it just now and got:

– no warnings for correlation matrix (cut = 0.400) –

Would it be relevant to mention that I’m running this on resting-state fmri data? I’ve used the -GOFORIT and -Rwherr options and am using the output from that as the final epi dataset. Is that an appropriate usage of 3dREMLfit for removing temporal autocorrelation in resting state data?