Abstract
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.
Highlights
It has been shown that physically identical nociceptive input can lead to variable sensations of pain, depending on contextual factors (Tracey and Mantyh, 2007)
We investigated oscillatory activity related to stimulus intensity, expectation, and prediction errors (Figure 2)
We considered a one-sided prediction error factor (PE), where a prediction error is only signaled when the stimulus is more intense as expected, which is motivated by previous work (Egner et al, 2010; Summerfield and de Lange, 2014; Geuter et al, 2017)
Summary
It has been shown that physically identical nociceptive input can lead to variable sensations of pain, depending on contextual factors (Tracey and Mantyh, 2007). Previous functional magnetic resonance imaging (fMRI) studies have suggested an important role of the anterior insular cortex for mediating expectation effects and the integration of prior expectation and prediction errors in the context of pain (Ploghaus et al, 1999; Koyama et al, 2005; Atlas et al, 2010; Geuter et al, 2017; Fazeli and Buchel, 2018). Based on the functional neuroanatomy of cortical microcircuits (Bastos et al, 2012), with feedforward connections predominately originating from superficial layers and feedback connections from deep layers, we expect that prediction error signals should be related to higher frequencies (e.g. gamma band) than prediction signals (Todorovic et al, 2011; Arnal and Giraud, 2012)
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