Recommendations for the Development of Socioeconomically-Situated and Clinically-Relevant Neuroimaging Models of Pain

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Pain is a complex, multidimensional experience that emerges from interactions among sensory, affective, and cognitive processes in the brain. Neuroimaging allows us to identify these component processes and model how they combine to instantiate the pain experience. However, the clinical impact of pain neuroimaging models has been limited by inadequate population sampling – young healthy college students are not representative of chronic pain patients. The biopsychosocial approach to pain management situates a person's pain within the diverse socioeconomic environments they live in. To increase the clinical relevance of pain neuroimaging models, a three-fold biopsychosocial approach to neuroimaging biomarker development is recommended. The first level calls for the development of diagnostic biomarkers via the standard population-based (nomothetic) approach with an emphasis on diverse sampling. The second level calls for the development of treatment-relevant models via a constrained person-based (idiographic) approach tailored to unique individuals. The third level calls for the development of prevention-relevant models via a novel society-based (social epidemiologic) approach that combines survey and neuroimaging data to predict chronic pain risk based on one's socioeconomic conditions. The recommendations in this article address how we can leverage pain's complexity in service of the patient and society by modeling not just individuals and populations, but also the socioeconomic structures that shape any individual's expectations of threat, safety, and resource availability.

Original languageEnglish (US)
Article number700833
JournalFrontiers in Neurology
StatePublished - Sep 7 2021
Externally publishedYes


  • biopsychosocial pain models
  • chronic pain
  • machine learning
  • neuroimaging biomarkers
  • social determinants of health
  • social epidemiology
  • translational ability

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology


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