Sensitivity to pain expectations: A Bayesian model of individual differences
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Abstract
The thoughts and feelings people have about pain (referred to as 'pain expectations') are known to alter the perception of pain. However little is known about the cognitive processes that underpin pain expectations, or what drives the differing effect that pain expectations have between individuals. This paper details the testing of a model of pain perception which formalises the response to pain in terms of a Bayesian prior-to-posterior updating process. Using data acquired from a short and deception-free predictive cue task, it was found that this Bayesian model predicted ratings of pain better than other, simpler models. At the group level, the results confirmed two core predictions of predictive coding; that expectation alters perception, and that increased uncertainty in the expectation reduces its impact on perception. The addition of parameters relating to trait differences in pain expectation improved the fit of the model, suggesting that such traits play a significant role in perception above and beyond the influence of expectations triggered by predictive cues. When the model parameters were allowed to vary by participant, the model's fit improved further. This final model produced a characterisation of each individual's sensitivity to pain expectations. This model is relevant for the understanding of the cognitive basis of pain expectations and could potentially act as a useful tool for guiding patient stratification and clinical experimentation.
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Theoretical models of the influence of expectation on perception refer to the instantaneous perceptual response to a sensory stimulus.
“Theoretical models of the influence of expectation on perception refers to the instantaneous perceptual response to a sensory stimulus10,22.”
From Boundary effects of expectation in human pain perception (2019) · cites this paper as [22]
Individual differences account for variation in pain expectation effects on pain experience.
“It was important to consider individual differences here especially because we previously showed that they account for variation in pain expectation effects on pain experience22.”
From Boundary effects of expectation in human pain perception (2019) · cites this paper as [22]
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- Authors
- Hoskin, R., Berzuini, C., Acosta-Kane, D., El-Deredy, W., Guo, H., & Talmi, D.
- Affiliations
- University of Manchester (GB)
- Princeton University (US)
- Corresponding author
- Talmi, D.
- Venue
- Cognition
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 182
- Pages
- 127-139
- ISSN
- 0010-0277 (ISSN-L)
- OpenAlex
- W2951773365
- Cited by
- 87
- References
- 63
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 13 · 2023: 19 · 2022: 11 · 2021: 8 · 2020: 7 · 2019: 5 · 2018: 1
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cognition (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion, cc-by-nc)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- Medical Research Council
- Economic and Social Research Council (ES/I010424/1)
- Fondo Nacional de Desarrollo Científico y Tecnológico (FB0008, 1161378)
- Comisión Nacional de Investigación Científica y Tecnológica
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Pain Management and Placebo Effect
- Health Sciences › Medicine › Physiology › Pain Mechanisms and Treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Keywords
- pain anticipation, pain perception, Bayesian model, predictive coding, individual differences, trait differences, predictive cues, uncertainty, patient stratification
- MeSH terms
- Adult, Aged, Bayes Theorem, Cues, Female, Humans, Individuality, Male, Models, Psychological, Uncertainty, Young Adult, Pain Perception, Anticipation, Psychological
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