Effects of preprocessing on local homogeneity of fMRI data

Abstract

Local functional connectivity - or the degree of homogeneity in brain function - is fast gaining popularity within the neuroscience research community. In particular, certain diseases and psychological conditions have been associated with disruptions in brain activity at the local level [1-5]. Algorithms that provide a measure of small-scale connectivity in fMRI data do so by gauging the degree of affinity between time series of neighbouring voxels, and thus rely on the assumption that preprocessing does not affect any intrinsic correlations. However, many of the preprocessing routines employ interpolation, and by its very nature, interpolation introduces artificial correlations. To our knowledge, none of the works published on the subject have taken the issue into account.