Ghosts in the Machine. Interoceptive Modeling for Chronic Pain Treatment

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 physiologic...

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Published in:Frontiers in neuroscience Vol. 10; p. 314
Main Authors: Di Lernia, Daniele, Serino, Silvia, Cipresso, Pietro, Riva, Giuseppe
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 30.06.2016
Frontiers Media S.A
Subjects:
Chronic pain
Coding theory
Emotions
Homeostasis
Metacognition
Neural coding
Neurology
Pain
Pain perception
Physiology
Trends
Italy
chronic pain
interoceptive modeling
interoception
free energy
predictive coding
ISSN:1662-453X, 1662-4548, 1662-453X
Online Access:Get full text
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Summary: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.
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Reviewed by: Karl Friston, University College London, UK; Fernand Anton, University of Luxembourg, Luxembourg
This article was submitted to Autonomic Neuroscience, a section of the journal Frontiers in Neuroscience
Edited by: Erwin Lemche, King's College London, UK
ISSN:1662-453X
1662-4548
1662-453X
DOI:10.3389/fnins.2016.00314