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Neural Mechanisms Supporting Default Mode Network Regulation of Pain Sensitivity

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abstract
Pain is a highly personal experience that is constructed by complex interactions between sensory, cognitive, affective, and genetic factors. The multi-factorial nature of pain produces substantial variations in subjective pain reports that are reflected in functional brain activity. The neural mechanisms underlying these inter-individual differences in pain sensitivity are not fully understood, however, recent evidence suggests a possible role for the default mode network (DMN) both in pain and pain sensitivity. The present thesis aimed to determine the underlying neural mechanisms of DMN involvement in pain and whether the DMN contributes to inter-individual differences in pain sensitivity. Relationships between pain sensitivity and DMN structure, as well as functional connectivity (FC) were examined. Specifically, a voxel-based morphometric (VBM) analysis was employed to determine the relationship between grey matter density across the whole brain and inter-individual differences in pain sensitivity. Additionally, psychophysiological interaction (PPI) analyses were employed to determine the FC of DMN regions during pain and how functional connections of the DMN relate to intra and inter-individual differences in pain sensitivity.
subject
Default Mode Network
Functional Connectivity
Pain
Voxel-Based Morphometry
contributor
Emerson, Nichole (author)
Coghill, Robert (committee chair)
Hugenschmidt, Christina (committee member)
Hayasaka, Satoru (committee member)
Houle, Timothy (committee member)
Kraft, Robert (committee member)
date
2017-01-14T09:35:15Z (accessioned)
2019-01-13T09:30:12Z (available)
2016 (issued)
degree
Neuroscience (discipline)
embargo
2019-01-13 (terms)
identifier
http://hdl.handle.net/10339/64169 (uri)
language
en (iso)
publisher
Wake Forest University
title
Neural Mechanisms Supporting Default Mode Network Regulation of Pain Sensitivity
type
Dissertation

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