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Poster C87 in Poster Session C - Friday, August 9, 2024, 11:15 am – 1:15 pm, Johnson Ice Rink
Expectation generation and its effect on subsequent perception in pain and vision
Rotem Botvinik-Nezer1,2 (), Stephan Geuter3, Martin Lindquist3, Tor Wager1; 1Dartmouth College, 2The Hebrew University of Jerusalem, 3Johns Hopkins University
In line with Bayesian predictive coding theories of brain function, cue-based expectations affect perception. However, it remains unclear how multiple cues are integrated into expectations, how these expectations affect subsequent perception, and if these processes are modality-specific or modality-general. Here, 45 participants observed multi-value cues and reported their expectations regarding the painfulness of thermal stimuli or visual contrast of flickering checkerboards. The mean, variance, and skewness of the cues were experimentally manipulated. Then, participants observed the same cues, followed by thermal and visual stimuli, during an fMRI scan. Expected and perceived stimuli were indeed higher following cues with higher mean in both modalities, but the effects of cue variance were mostly not consistent with Bayesian or other previous theories. Instead, computational models indicated that people placed a larger weight on extreme values in both modalities, particularly low-pain cues. fMRI analysis showed that the effect of expectations on pain ratings was mostly mediated by brain systems related to cognitive and affective processing, rather than nociceptive pain. Our findings suggest that people’s expectations and perception are affected by extreme values, with some similarities and some differences across modalities.
Keywords: Bayesian Expectations fMRI Pain