Ghosts in the machine. Interoceptive modeling for chronic pain treatment

Daniele Di Lernia, Silvia Serino, Pietro Cipresso, Giuseppe Riva

Research output: Contribution to journalArticle

Abstract

Pain is a complex and multidimensional perception, embodied in our daily experiences through interoceptive appraisal processes. The article reviews the recent literature about interoception along with predictive coding theories and tries to explain a missing link between the sense of the physiological condition of the entire body and the perception of pain in chronic conditions, which are characterized by interoceptive deficits. Understanding chronic pain from an interoceptive point of view allows us to better comprehend the multidimensional nature of this specific organic information, integrating the input of several sources from Gifford's Mature Organism Model to Melzack's neuromatrix. The article proposes the concept of residual interoceptive images (ghosts), to explain the diffuse multilevel nature of chronic pain perceptions. Lastly, we introduce a treatment concept, forged upon the possibility to modify the interoceptive chronic representation of pain through external input in a process that we call interoceptive modeling, with the ultimate goal of reducing pain in chronic subjects.

Original languageEnglish
Article number314
JournalFrontiers in Neuroscience
Volume10
Issue numberJUN
DOIs
Publication statusPublished - Jun 30 2016

Keywords

  • Chronic pain
  • Free energy
  • Interoception
  • Interoceptive modeling
  • Predictive coding

ASJC Scopus subject areas

  • Neuroscience(all)

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