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Related Experiment Video

Updated: Nov 17, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

Published on: January 27, 2010

Predictive coding models for pain perception.

Yuru Song^1,2, Mingchen Yao^1,3, Helen Kemprecos⁴

¹Department of Psychiatry, New York University School of Medicine, New York, USA.

Journal of Computational Neuroscience

|February 17, 2021

Summary

This summary is machine-generated.

This study models pain perception using predictive coding, analyzing brain activity in rats to understand sensory and emotional pain processing. The findings offer insights into chronic pain and placebo effects.

Keywords:

Anterior cingulate cortex Chronic pain Mean field model Pain perception Placebo Predictive coding Somatosensory cortex

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Last Updated: Nov 17, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP

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Published on: January 27, 2010

Determining Pain Detection and Tolerance Thresholds Using an Integrated, Multi-Modal Pain Task Battery

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Published on: April 14, 2016

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Published on: April 5, 2019

Area of Science:

Neuroscience
Computational Neuroscience

Background:

Pain is a complex, variable experience influenced by sensory-discriminative and affective-emotional factors.
Predictive coding offers a framework for understanding perception as an inference problem.

Purpose of the Study:

To characterize evoked and non-evoked pain using a predictive coding paradigm.
To investigate the temporal coordination of brain activity between key pain-processing regions.

Main Methods:

Recorded local field potentials (LFPs) from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) in freely behaving rats.
Developed phenomenological and biophysical neural mass models based on predictive coding principles.
Analyzed neural dynamics in both naive and chronic pain-treated animals.

Main Results:

The predictive coding models successfully replicated key experimental findings in pain processing.
Models provide new predictions regarding the influence of parameters on physiological and behavioral outcomes.
Demonstrated temporal coordination of oscillatory activity between S1 and ACC.

Conclusions:

The predictive coding framework offers mechanistic insights into pain perception.
The models illuminate the roles of expectation, placebo/nocebo effects, and chronic pain.
This approach advances our understanding of pain's subjective and objective dimensions.