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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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