Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula

Author: Stephan Geuter1,2,3, Sabrina Boll1,4, Falk Eippert5, Christian B├╝chel1
Affiliation: <sup>1</sup> Department of Systems Neuroscience, University Medical Center Hamburg Eppendorf, Hamburg, Germany. <sup>2</sup> Institute of Cognitive Science, University of Colorado Boulder, Boulder, United States. <sup>3</sup> Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, United States. <sup>4</sup> Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany. <sup>5</sup> Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, Oxford, United Kingdom.
Conference/Journal: Elife
Date published: 2017 May 19
Other: Volume ID: 6 , Pages: e24770 , Special Notes: doi: 10.7554/eLife.24770. , Word Count: 164


The computational principles by which the brain creates a painful experience from nociception are still unknown. Classic theories suggest that cortical regions either reflect stimulus intensity or additive effects of intensity and expectations, respectively. By contrast, predictive coding theories provide a unified framework explaining how perception is shaped by the integration of beliefs about the world with mismatches resulting from the comparison of these beliefs against sensory input. Using functional magnetic resonance imaging during a probabilistic heat pain paradigm, we investigated which computations underlie pain perception. Skin conductance, pupil dilation, and anterior insula responses to cued pain stimuli strictly followed the response patterns hypothesized by the predictive coding model, whereas posterior insula encoded stimulus intensity. This novel functional dissociation of pain processing within the insula together with previously observed alterations in chronic pain offer a novel interpretation of aberrant pain processing as disturbed weighting of predictions and prediction errors.

Keywords: expectations; fMRI; human; neuroscience; pain; predictive coding; somatosensory perception.

PMID: 28524817 PMCID: PMC5470871 DOI: 10.7554/eLife.24770