Individual Difference clinical trials

Identifying Neuroimaging Biomarkers, Demographic, Personality and Sensory Factors for Predicting Extreme Pain Responses to Various Experimental Pain Stimulations in Healthy Subjects

The proneness to react to noxious stimuli varies widely between individuals and pain ratings of seemingly identical noxious stimuli may range from "no pain" to "excruciating pain" . Imaging studies in healthy subjects have provided useful information on the identification of the inter-individual variability in pain perception [2,3,4]. These studies have shown that subjective pain reports are closely related to the degree of neuronal activity in several brain regions known to be identified in pain processing. Furthermore, there has been a growing interest in understanding structural and functional mechanisms of inter-individual variability in responses to identical noxious stimuli [5,6,7]. Yet, the relationship between pain perception and various anatomical and functional connectivity within resting state brain networks is not completely understood. With regard to the anatomical correlate of pain sensitivity, differences in grey matter may reflect neural processes contributing to the construction and modulation of pain in healthy individuals. As such, studies are inconsistent regarding this issue, showing positive [7] or inverse connections [6] between pain sensitivity and brain morphology. The inconsistency regarding this issue warrant further investigation which may elucidate the relationship between differences in pain sensitivity and regional grey matter and may provide novel insights into brain mechanisms contributing to that topic. Understanding brain morphology and connectivity within specific regions associated with pain processing can provide reliable anchor for the individual differences in pain response. A widely used approach to examine brain morphology from MRI images is voxel based morphometry (VBM). VBM tests for statistically significant differences in regional gray matter (GM) density between study groups, and its temporal changes. Diffusion tensor imaging (DTI) is a type of diffusion weighted imaging with the advantage of being able to resolve individual functional tracts within the white matter (WM) thus, DTI parameters serve as indirect measures of structural connectivity via the degree of integrity of WM tracts.