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PLoS Comput Biol. 2012;8(10):e1002719. doi: 10.1371/journal.pcbi.1002719. Epub 2012 Oct 25.

Predictive dynamics of human pain perception.

Author information

1
Computational Biology Center, T.J. Watson IBM Research Laboratory, Yorktown Heights, New York, USA. gcecchi@us.ibm.com

Abstract

While the static magnitude of thermal pain perception has been shown to follow a power-law function of the temperature, its dynamical features have been largely overlooked. Due to the slow temporal experience of pain, multiple studies now show that the time evolution of its magnitude can be captured with continuous online ratings. Here we use such ratings to model quantitatively the temporal dynamics of thermal pain perception. We show that a differential equation captures the details of the temporal evolution in pain ratings in individual subjects for different stimulus pattern complexities, and also demonstrates strong predictive power to infer pain ratings, including readouts based only on brain functional images.

PMID:
23133342
PMCID:
PMC3486880
DOI:
10.1371/journal.pcbi.1002719
[Indexed for MEDLINE]
Free PMC Article
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