Precision Functional Mapping of Imagined and Experienced Pain

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Imagination is a principal human capacity, enabling simulation of sensations and situations for planning, learning, and empathy. We examined neural representations of experienced and imagined pain across eight body sites using deep-phenotyping, precision functional MRI with over seven hours of scanning per participant (N = 9). Conventional mapping, pattern classification, and representational similarity analyses converged to show that both imagined and experienced pain activated nociceptive regions (e.g., dorsoposterior insula) and non-nociceptive regions (e.g., supplementary motor area). However, imagined pain did not reliably reactivate body site-selective nociceptive patterns in any region. Instead, imagined and experienced pain shared multivariate representations across widespread cortical and subcortical regions, particularly transmodal cortical areas including dorsomedial and lateral prefrontal cortex, hippocampus, and thalamus. These findings suggest that imagination generates distributed pain-like activity while preserving a neural distinction from verum pain. This distinction may explain the difficulty of vividly imagining pain and underlie its role in empathy, planning, and pain vulnerability.

Author Note

We are grateful for assistance from Terry Sackett, Maryam Amini, Melanie Kos, Stephanie Sun, Eilis Murphy, Samuel Bergerson, Kristoffer Mansson, Sreekar Kasturi, Jason Davis, and Charles Mazof for assistance in data collection for this study. We thank Byeol Kim, Ben Graul, Li-Bo Zhang, and Zhaoxing Wei for comments on the manuscript, and Luke Chang and Marianne Reddan for insightful discussion. This work was funded by a grant from the Hitchcock Foundation and grant R37MH076136 from the National Institutes of Mental Health. Code for analyses are available at https://github.com/canlab/ .

Article activity feed