Brain Imaging and Pain: Analysis of Placebo Analgesia

描述（由申请人提供）：在本竞争性更新申请中，我们建议扩展我们对通过安慰剂镇痛进行内源性疼痛调节的潜在机制的研究。具体来说，我们的目标是研究与处理不同方面的疼痛相关信息的神经网络的时间特性。之前的资金使我们能够开发和完善常规用于研究无症状和临床人群疼痛的生态有效技术和脑成像协议。有了这些工具，我们已经表明，在一个一般的认知/情感网络的大脑区域有不同的互动配置文件在疼痛和安慰剂镇痛条件。在这项提案中，我们将改进这些技术，以提高大脑区域的识别（即，神经网络），以及如何随时间处理该信息（即，对条件内和条件之间以及跨不同神经网络的信息处理的时间特性进行建模）。这项建议的三个具体目标将使我们能够实现这些目标。在目标1中，我们将使用行为、心理物理和功能磁共振成像数据区分主要与传入疼痛处理和认知-情感疼痛调制相关的神经网络。对于目标2，我们将详细描述包括与疼痛和疼痛调制的特定方面相关的神经网络的大脑区域（例如，焦虑和期待）。一旦神经网络被识别出来，在目标3中，我们将描述这些网络在处理条件内和条件之间的信息时的时间特征和相互作用。目标3的结果将有助于澄清和解释伴随行为疼痛评级变化的神经网络变化。这些目标需要结合心理，心理物理，结构和功能MRI数据和先进的统计分析，所有这些我们都有丰富的经验和专业知识，因此对该项目的成功充满信心。

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.