Functional inferences vary with the method of analysis in fMRI

Neuroanatomic substrates of specific cognitive functions have been inferred from anatomic distributions of activated pixels during fMRI studies. With declarative memory tasks, interest has focused on the extent to which vario us medial temporal lobe anatomic structures are activated while subjects en code new information.: The aim of this project was to examine how commonly used variations in fMRI data processing methods affect the distribution of activation in anatomically defined medial temporal lobe regions of interest (ROIs) during a complex scene-encoding task. ROIs were drawn on an MRI ana tomic template formed from 3D SPGR scans of eight subjects combined in Tala irach space. Separate ROIs were drawn for the posterior and anterior hippoc ampal formation, parahippocampal gyrus, and entorhinal cortex. Twelve diffe rent activation maps were created for each subject by using four correlatio n coefficients and three cluster volumes. Friedman's two-way ANOVA by ranks was used to test the hypothesis that the distribution of activated pixels among defined anatomic ROIs varied as a function of the data processing met hod. By simply varying the combination of correlation coefficient and clust er volume, significantly different distributions of activation within named medial temporal lobe structures were obtained from the same fMRI datasets (P<0.015; P<0.001). The number of subjects studied (n=8) is in a range comm only found in the literature yet this clearly resulted in spurious associat ions between processing parameter variations and activation distribution. U sing data processing methods that are independent of the arbitrary selectio n of cutoff values for thresholding activation maps may reduce the likeliho od of obtaining spurious results. (C) 2001 Academic Press.