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Applications of dynamic functional connectivity to pain and its modulation
Journal article   Open access   Peer reviewed

Applications of dynamic functional connectivity to pain and its modulation

Elizabeth A. Necka, In-Seon Lee, Aaron Kucyi, Joshua C. Cheng, Qingbao Yu and Lauren Y. Atlas
Pain reports, v 4(4), pp e752-e752
01 Jul 2019
PMID: 31579848
url
https://doi.org/10.1097/PR9.0000000000000752View
Published, Version of Record (VoR) Open

Abstract

Life Sciences & Biomedicine Neurosciences Neurosciences & Neurology Science & Technology
Since early work attempting to characterize the brain's role in pain, it has been clear that pain is not generated by a specific brain region, but rather by coordinated activity across a network of brain regions, the "neuromatrix." The advent of noninvasive whole-brain neuroimaging, including functional magnetic resonance imaging, has provided insight on coordinated activity in the pain neuromatrix and how correlations in activity between regions, referred to as "functional connectivity," contribute to pain and its modulation. Initial functional connectivity investigations assumed interregion connectivity remained stable over time, and measured variability across individuals. However, new dynamic functional connectivity (dFC) methods allow researchers to measure how connectivity changes over time within individuals, permitting insights on the dynamic reorganization of the pain neuromatrix in humans. We review how dFC methods have been applied to pain, and insights afforded on how brain connectivity varies across time, either spontaneously or as a function of psychological states, cognitive demands, or the external environment. Specifically, we review psychophysiological interaction, dynamic causal modeling, state-based dynamic community structure, and sliding-window analyses and their use in human functional neuroimaging of acute pain, chronic pain, and pain modulation. We also discuss promising uses of dFC analyses for the investigation of chronic pain conditions and predicting pain treatment efficacy and the relationship between state- and trait-based pain measures. Throughout this review, we provide information regarding the advantages and shortcomings of each approach, and highlight potential future applications of these methodologies for better understanding the brain processes associated with pain.

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33 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Neurosciences
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