Brain Imaging and Pain: Analysis of Placebo Analgesia

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DESCRIPTION (provided by applicant): In this competitive renewal application, we propose to extend our research on the underlying mechanisms of endogenous pain modulation via placebo analgesia. Specifically, we aim to investigate the temporal characteristics of the neural networks associated with processing different aspects of pain related information. Previous funding allowed us to develop and refine the ecologically valid techniques and brain imaging protocols routinely used to study pain in asymptomatic and clinical populations. With these tools, we have shown that the brain regions within a general cognitive/affective network have distinct interaction profiles in painful and placebo analgesic conditions. In this proposal, we will refine these techniques to improve the identification of brain regions (i.e., neural networks) associated with processing specific facets of pain related information, and how that information is processed over time (i.e., modeling the temporal characteristics of information processing within and between conditions, and across different neural networks). The three specific aims of this proposal will allow us to reach these goals. In Aim 1, we will differentiate the neural networks primarily associated with afferent pain processing from cognitive-affective pain modulation using behavioral, psychophysical, and fMRI data. For Aim 2, we will detail the brain regions that comprise the neural networks involved with specific facets of pain and pain modulation (e.g., anxiety and expectation). Once the neural networks have been identified, in Aim 3, we will describe the temporal characteristics and interactions of these networks as they process information within and between conditions. The results from Aim 3 will help clarify and account for the changes in neural networks that accompany changes in behavioral pain ratings. These aims require the combination of psychological, psychophysical, structural and functional MRI data and advanced statistical analyses, all of which we have extensive experience and expertise with, and thus are confident in the success of this project.