The temporal and spectral characteristics of expectations and prediction errors in pain and thermoception
In the context of a generative model, such as predictive coding, pain and heat perception can be construed as the integration of expectation and input with their difference denoted as a prediction error. In a previous neuroimaging study (Geuter et al., 2017) we observed an important role of the insula in such a model, but could not establish its temporal aspects. Here we employed electroencephalography to investigate neural representations of predictions and prediction errors in heat and pain processing. Our data show that alpha-to-beta activity was associated with stimulus intensity expectation, followed by a negative modulation of gamma band activity by absolute prediction errors. This is in contrast to prediction errors in visual and auditory perception, which are associated with increased gamma band activity, but is in agreement with observations in working memory and word matching, which show gamma band activity for correct, rather than violated predictions.
Data for this study are available on https://osf.io/f2mua/
The temporal and spectral characteristics of expectations and prediction errors in pain and thermoceptionOpen Science Framework, F2MUA.
Article and author information
Deutsche Forschungsgemeinschaft (SFB 289)
- Christian Büchel
Deutsche Forschungsgemeinschaft (SFB TR 169 project B3)
- Michael Rose
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: All volunteers gave their informed consent. The study was approved by the Ethics board of the Hamburg Medical Association (PV4745).
- Peter Kok, University College London, United Kingdom
- Received: September 10, 2020
- Accepted: February 16, 2021
- Accepted Manuscript published: February 17, 2021 (version 1)
- Version of Record published: March 2, 2021 (version 2)
© 2021, Strube et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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