Cued probabilistic expectations do not modulate grating-evoked event-related potentials in the visual system

Abstract

AbstractWe can rapidly learn recurring patterns that occur within our sensory environments. This knowledge allows us to form expectations about future sensory events. Several influential predictive coding models posit that, when a stimulus matches our expectations, the activity of feature-selective neurons in visual cortex will be suppressed relative to when that stimulus is unexpected. However, after accounting for known critical confounds, there is currently scant evidence for these hypothesised effects from studies recording electrophysiological neural activity. To provide a strong test for expectation effects on stimulus-evoked responses in visual cortex, we performed a probabilistic cueing experiment while recording electroencephalographic (EEG) data. Participants (n=48) learned associations between visual cues and subsequently presented gratings. A given cue predicted the appearance of a certain grating orientation with 10%, 25%, 50%, 75%, or 90% validity. We did not observe any stimulus expectancy effects on grating-evoked event-related potentials. Bayes factors generally favoured the null hypothesis throughout the time-courses of the grating-evoked responses. Multivariate classifiers trained to discriminate between grating orientations also did not substantively differ in their performance across stimulus expectancy conditions. Our null findings provide further evidence against modulations of prediction error signalling by probabilistic expectations as specified in contemporary predictive coding models.