Dang, P. N. U.; Mattingley, J. B.; Moore, M. J.

According to predictive processing theories, the brain achieves efficiency in perception by comparing current sensory inputs with stored representations of the external world. Previous research has shown that manipulations of expectation can alter neural processing of low-level visual features as well as more complex, naturalistic objects. It remains unclear, however, precisely how the effects of expectancy are altered through learning and changes in stimulus fidelity. Here, we characterised behaviour and neural activity patterns while systematically varying individuals' prior exposure to object sequences and the quality of the stimuli therein. Participants viewed rapid image sequences while we recorded their brain activity using electroencephalography (EEG). The stimulus sequences were probabilistically structured such that the appearance of each object was either expected, unexpected, or random. Participants were faster and more accurate in detecting cued target stimuli when these were expected relative to unexpected or random. Multivariate analysis of EEG activity patterns time-locked to the appearance of object images revealed reliably reduced decoding accuracy for both expected and unexpected stimuli relative to random stimuli. These patterns were consistent across exposure and image quality conditions, though exploratory analyses suggested that subtle changes in neural prediction effects may be linked to exposure. The findings do not provide strong support that the brain differentially represents expected versus unexpected object information and suggest that exposure and image quality do not reliably interact with predictive processes in object recognition.