title: Imperfect (de)convolution may introduce spurious psychophysiological interactions and how to avoid it.
abstract: Psychophysiological interaction (PPI) is a widely used regression-based method to study connectivity changes in different experimental conditions. A PPI effect is generated by point-by-point multiplication of a psychological variable (experimental design) and a physiological variable (time series of a seed region). If the psychological variable is non-centered with a constant component, the constant component will add a physiological variable to the PPI term. The physiological component would in theory be accounted for by the physiological main effect in the model. But due to imperfect deconvolution and convolution with hemodynamic response function, the physiological component in PPI may no longer be exactly the same as the physiological main effect. This issue was illustrated by analyzing two block-designed fMRI datasets, one simple visual checkerboard task and a set of different tasks designed to activate different hemispheres. When PPI was calculated with deconvolution but without centering, significant results were usually observed between regions that are known to have baseline functional connectivity. These results could be suppressed by simply centering the psychological variable when calculating the PPI term or adding a deconvolve-reconvolved version of the physiological covariate. The PPI results with centering and with deconvolve-reconvolved physiological covariate are consistent with an explicit test for differences in coupling between conditions. It was, therefore, suggested that centering of the psychological variable or the addition of a deconvolve-reconvolved covariate is necessary for PPI analysis. Hum Brain Mapp 38:1723-1740, 2017. © 2017 Wiley Periodicals, Inc.
authors.affiliation: Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey.
authors.forename: Xin
authors.initials: X
authors.lastname: Di
authors.affiliation: Department of Health and Human Services, Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland.
authors.forename: Richard C
authors.initials: RC
authors.lastname: Reynolds
authors.affiliation: Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey.
authors.forename: Bharat B
authors.initials: BB
authors.lastname: Biswal
mesh_terms: D000293:Adolescent; D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D001931:Brain Mapping; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D021621:Imaging, Three-Dimensional; D007600:Judgment; D008279:Magnetic Resonance Imaging; D008297:Male; D008606:Mental Processes; D008875:Middle Aged; D008959:Models, Neurological; D009434:Neural Pathways / Q000000981:diagnostic imaging / Q000502:physiology*; D010100:Oxygen / Q000097:blood; D010775:Photic Stimulation; D011603:Psychophysiology; D014796:Visual Perception / Q000502:physiology; D014825:Vocabulary; D055815:Young Adult
chemical_list: D010100:Oxygen
keywords: connectivity; fMRI; mean centering; psychophysiological interactions