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

Marianne C Reddan

doi:10.3389/fneur.2021.700833

Abstract

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.

Highlights

Neuroimaging models have significantly expanded our understanding of the neural processes that instantiate a person’s subjective pain experience [for reviews see [1,2,3]]
The combinatorial model performed with high accuracy within the study it was developed, Combining models like this may be prone to overfitting, so the it is unknown how it performs in external data sets. preregistration of model combinations is recommended
Pain is a personal experience instantiated by biological processes and situated within one’s socioeconomic conditions

Summary

INTRODUCTION

Neuroimaging models have significantly expanded our understanding of the neural processes that instantiate a person’s subjective pain experience [for reviews see [1,2,3]]. New pain components developed in easier to collect (i.e., evoked pain in healthy controls) diverse populations can be validated in clinically-relevant samples to improve translation and impact. Individual differences in pain expression have made it difficult for biomarkers to be developed on lower dimensional data like facial expressions, skin conductance responses, and heart rate, recent idiographic approaches to modeling these types of data have significantly improved their predictive power [45,46,47] In the clinic, such models may provide objective assessments of disease progression and treatment progress. The first step is to collect survey data assessing an individual’s socioeconomic conditions and subjective experience of social status This multidimensional assay can be applied to pain-related brain activity to develop a neuroimaging model of socioeconomic contributions to chronic pain (Figure 1C). A major barrier to the study of socioeconomic factors in chronic pain is the lack of a standardized assessment of TABLE 1 | Socioeconomic Pain-Predispositions Profile Survey

Objective

Findings

DISCUSSION