Computational protocol: Distinctive neural responses to pain stimuli during induced sadness in patients with somatoform pain disorder: An fMRI study☆

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Protocol publication

[…] Image processing and statistical analyses were carried out using Statistical Parametric Mapping (SPM8) software (Wellcome Department of Cognitive Neurology, London, UK). The first three volumes of each fMRI run were discarded because the MRI signal was unsteady. Each set of functional volumes was realigned to the first volume. A slice timing correction was performed on the model slice to correct for the sequential sampling of the brain in the slice direction. Volumes were spatially normalized to a standard template based upon the Montreal Neurological Institute (MNI) reference brain, and finally smoothed using an 8-mm FWHM Gaussian kernel.For the statistical analysis, subject-specific t-contrast images were calculated for the pain effects using the general linear model (first level analysis). For each participant the preprocessed data were assigned to the following four conditions in the model specification: High pain during sad facial images, low pain during sad facial images, high pain during neutral facial images, and low pain during neutral facial images. These contrasts were entered into the second level analysis. Using group analysis according to a random effects model, we conducted repeated measures 3-way ANOVAs as implemented in SPM8 with group (patients or controls) as a between-subjects factor and pain (moderate or low) and emotional context (sad or neutral) as within-subjects factors. BDI, STAI-S, and STAI-T scores were used as covariates to control for individual differences in depressive and anxiety states, in consideration of the modulatory effects of depression and anxiety on pain sensitivity. The spatial coordinates provided by SPM8, which are in MNI brain space, were converted to spatial coordinates of the Anatomical Automatic Labeling (AAL) atlas using the MarsBar SPM Toolbox. Peak voxel parameter estimates from interactions were examined using post-hoc Bonferroni multiple comparisons performed in SPSS version 16.0.We conducted a psychophysiological interaction (PPI) analysis () to examine interactions between brain regions in relation to the experimental paradigm. This approach can capture the way in which activity in one brain region modulates activity in another region by specifically assessing responses to the active task relative to an informative baseline. To undertake PPI analysis a design matrix is established, which typically contains three columns of variables as follows: (1) a psychological variable that reflects the experimental paradigm, (2) a time series variable representing the time course of the source region; here, the source region was a 6-mm sphere with a center defined by the peak coordinate of the foregoing analysis, and (3) a variable that represents the interaction between (1) and (2). The regression coefficient for the interaction term provides a measure of PPI. In the present context, a significant effect for PPI means that the correlation (or covariance) between the source and the sink region during an emotional pain condition is significantly different from that during another emotional condition. In this regard, PPI analysis assesses differences in functional connectivity between the regions of interest. To perform PPI analyses, the first eigenvariate time series of the 6-mm sphere activated according to the previous analyses was extracted. The effect of the interaction term was then studied using the contrast [1 0 0], where the first column represents the interaction term. The extracted individual images were then taken to the second level to perform a random effects analysis, using a one-sample t-test.The statistical threshold for all the imaging analyses described above was set at an uncorrected p value of 0.001 and at a minimum cluster size of 20 voxels, based on previous pain related fMRI studies ().Finally, we examined the correlations between the brain regions involved in modulating low pain levels within the context of sadness and the sadness-specific low-pain rating scores of patients. We also analyzed the correlations between the brain regions involved in modulating low pain levels within the context of sadness and BDI or STAI scores for all participants, and examined whether sadness-induced pain perception changes were correlated with individual differences in depressed mood or anxiety state. A correlation analysis was performed for the brain areas for which there was a significant interaction effect in the 3-way ANOVAs (the anterior/posterior insula and the hippocampus) as regions of interest (ROIs). […]

Pipeline specifications

Software tools SPM, AAL, SPSS
Applications Miscellaneous, Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens