Evaluating the Evidence for Expectation Suppression in the Visual System

Expectation suppression is defined as a reduction in a measure of neural activity following an expected stimulus compared to a stimulus that is neither expected nor surprising. Reports of expectation suppression have shaped the development of several influential predictive coding-based theories of visual perception. However recent work has highlighted multiple confounding factors that may mimic or inflate observed expectation suppression effects. In this review, we describe four confounds that are prevalent across studies that have tested for expectation suppression: surprise-related response modulations, effects of attention, stimulus repetition and adaptation, and effects of stimulus novelty. With these confounds in mind we then critically review the evidence for expectation suppression across probabilistic cueing, statistical learning, oddball, action-outcome learning and apparent motion designs. We report that there is evidence for expectation suppression within a specific subset of statistical learning designs that involved weeks of sequence learning prior to neural activity measurement. However, across other experimental contexts, whereby stimulus appearance probabilities were learned within one or two testing sessions, there was a lack of consistent evidence for genuine expectation suppression within the visual system that cannot be accounted for by confounding factors. To underline the importance of devising more appropriate tests for expectation suppression we discuss how an absence of this effect would inform models of predictive processing, repetition suppression and perceptual decision-making. We also provide suggestions for designing experiments that may better test for stimulus expectation effects in future work.