Abstract #2476
Processing Induced Spatial Correlations Are Quantified With A Temporal Frequency Representation in Complex-Valued fMRI
Mary C. Kociuba 1 and Daniel B. Rowe 1,2
1
Department of Mathematics, Statistics, and
Computer Science, Marquette University, Milwaukee,
Wisconsin, United States,
2
Department
of Biophysics, Medical College of Wisconsin, Milwaukee,
Wisconsin, United States
To remove variability, from image acquisition artifacts
and unwanted physiological sources, inherent within an
acquired functional MRI (fMRI) signal, the data is
preprocessed before statistical analysis is performed.
Although, it is well known that preprocessing operations
modify a voxels temporal spectrum and induce
correlations. In this study, spatial correlations are
described in terms of overlapping temporal frequency
content between voxels. Identifying the location and
extent of the induced correlations is the first step to
compensate for unwanted variability, leading to more
accurate interpretations from the data.
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