Prediction errors in surface segmentation are reflected in the visual mismatch negativity, independently of task and surface features

Abstract

The visual system quickly registers perceptual regularities in the environment and responds to violations in these patterns. Errors of perceptual prediction are associated with electrocortical modulation, including the visual mismatch negativity (vMMN) and P2 event-related potential. One relatively unexplored question is whether these prediction error signals can encode higher-level properties such as surface segmentation, or whether they are limited to lower-level perceptual features. Using a roving standard paradigm, a triangle surface appeared either behind (featuring amodal contours) or in front of (featuring real contours) a second surface with hole-like windows. A surface layout appeared for 2-5 repetitions before switching to the other "deviant" layout; lighting and orientation of stimuli varied across presentations while remaining isoluminant. Observers responded when they detected a rare "pinched" triangle which occasionally appeared. Cortical activity - reflected in mismatch responses affecting the P2-N2 and P300 amplitudes - was sensitive to a change in stimulus layout, when surfaces shifted position in depth, following several repetitions. Specifically, layout deviants led to a more negative P2-N2 complex at posterior electrodes, and greater P300 positivity at central sites. Independently of these signals of a deviant surface layout, further modulations of the P2 encoded differences between layouts and detection of the rare target stimulus. Comparison of the effect of preceding layout repetitions on this prediction error signal suggests that it is all-or-none and not graded with respect to the number of previous repetitions. We show that within the visual domain, unnoticed and task-irrelevant changes in visual surface segmentation leads to observable electrophysiological signals of prediction error that are dissociable from stimulus-specific encoding and lower-level perceptual processing.

The N300: An Index for Predictive Coding of Complex Visual Objects and Scenes

“…Of particular relevance to PHT is the vMMN which, as overviewed in the introduction, temporally precedes the N300 and has been observed in experimental contexts wherein a stream of standard stimuli that share particular low-level visual features (e.g., orientation and color) is occasionally interrupted by the presentation of a target stimulus that carries a featural difference ( Stefanics et al. 2014 ; Oxner et al. 2019 ).…”

“…The vMMN has sometimes been associated with predictive coding ( Stefanics et al. 2014 ; Oxner et al. 2019 ).…”

The N300: An Index For Predictive Coding Of Complex Visual Objects and Scenes

“…For example, a component known as the visual mismatch negativity (vMMN) occurs between 100-160 ms in target-oddball paradigms, where it is larger for the visual oddball stimuli. The vMMN has sometimes been associated with predictive coding (Stefanics et al 2014;Oxner et al 2019). However, given its sensitivity to the current experimental context -and, importantly, not to statistical regularities built up over a lifetime -as well as its source location to occipital cortex (Susac et al 2014;File et al 2017), the vMMN would be classified as indexing early stage PHT processing.…”

“…objects (Schendan et al 1998) -category comparisons that are thus at a much higher taxonomy than within objects or scenes. Of particular relevance to PHT is the vMMN which, as overviewed in the introduction, temporally precedes the N300 and has been observed in experimental contexts wherein a stream of standard stimuli that share particular low-level visual features (e.g., orientation, color) is occasionally interrupted by the presentation of a target stimulus that carries a featural difference (Stefanics et al 2014;Oxner et al 2019). Thus, the vMMN is sensitive to the context of recent exposure to low-level visual information, possibly reflecting PHT processes at that lower level.…”

Introduction to special issue on “Prediction in Perception and Action”

“…Two articles in the Special Issue provide evidence for high-level predictive representations using EEG. Oxner et al (2019) show that prediction errors in surface segmentation are associated with visual mismatch negativity and with the P2 wave in the event-related potential. Based on amplitude differences in the error-related negativity, Maurer et al (2019) suggest that the brain generates error predictions that can dissociate relevant from irrelevant errors and that relevant errors lead to larger behavioral adjustments than irrelevant ones.…”