Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain
Edited by Peter Strick, Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA; received September 10, 2021; accepted November 22, 2021
Significance
Pain is not only shaped by sensory information but also by an individual’s expectations. Here, we investigated how commonly analyzed electroencephalography (EEG) responses to pain signal sensory information, expectations, and discrepancies thereof (prediction errors) in the processing of pain. Bayesian analysis confirmed that pain perception was shaped by objective sensory information and expectations. In contrast, EEG responses at different latencies (including the N1, N2, and P2 components) and frequencies (including alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Thus, EEG responses to pain are more involved in signaling sensory information than in signaling expectations or prediction errors. Expectation effects are obviously mediated by other brain mechanisms than the effects of sensory information on pain.
Abstract
The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual’s expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.
Data Availability
All data in EEG-BIDS format (87) and code are available at the Open Science Framework (https://osf.io/jw8rv/).
Acknowledgments
The study was supported by the Deutsche Forschungsgemeinschaft (PL 321/14-1) and the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 758974).
Supporting Information
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Copyright © 2021 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).
Data Availability
All data in EEG-BIDS format (87) and code are available at the Open Science Framework (https://osf.io/jw8rv/).
Submission history
Accepted: November 22, 2021
Published online: December 30, 2021
Published in issue: January 5, 2022
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Acknowledgments
The study was supported by the Deutsche Forschungsgemeinschaft (PL 321/14-1) and the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 758974).
Notes
This article is a PNAS Direct Submission.
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The authors declare no competing interest.
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Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain, Proc. Natl. Acad. Sci. U.S.A.
119 (1) e2116616119,
https://doi.org/10.1073/pnas.2116616119
(2022).
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