Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Accurate autocorrelation modeling substantially improves fMRI
  reliability   Given the recent controversies in some neuroimaging statistical methods, we
compare the most frequently used functional Magnetic Resonance Imaging (fMRI)
analysis packages: AFNI, FSL and SPM, with regard to temporal autocorrelation
modeling. This process, sometimes known as pre-whitening, is conducted in
virtually all task fMRI studies. We employ eleven datasets containing 980 scans
corresponding to different fMRI protocols and subject populations. Though
autocorrelation modeling in AFNI is not perfect, its performance is much higher
than the performance of autocorrelation modeling in FSL and SPM. The residual
autocorrelated noise in FSL and SPM leads to heavily confounded first level
results, particularly for low-frequency experimental designs. Our results show
superior performance of SPM's alternative pre-whitening: FAST, over SPM's
default. The reliability of task fMRI studies would increase with more accurate
autocorrelation modeling. Furthermore, reliability could increase if the
packages provided diagnostic plots. This way the investigator would be aware of
pre-whitening problems.

1
The categories of this paper are: cs
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con