The neural processes of illusory occlusion in object recognition

Fast and accurate object recognition is crucial for effective behaviour in dynamic visual environments. In some cases, the visual system must overcome ambiguity in visual input during object recognition, such as when an object is partially hidden behind another. Recurrent processing between higher- and lower-order areas is thought to play a role in resolving such ambiguity, enabling the filling in of missing visual information. Here we examined this claim using a novel paradigm in which partial object images appear ‘occluded’ by an illusory Kanizsa figure, perception of which also depends on recurrent processing by the grouping of Pacmen inducers. If both recognising the partial object and perceiving the illusory shape depend on recurrent processing, object recognition should vary as a function of the presence of illusory shape. Across two behavioural experiments and a separate EEG decoding study, we found no evidence for an interaction between illusion perception and object recognition, and different neural time courses for the illusory figures alone compared to those of the partial objects, which were decoded earlier. Ultimately, our study highlights the robustness of the visual system to solve the identity of the ambiguous object, independently from the processing of different ambiguities occurring at the same time, providing new insights into the mechanisms of recurrence in the early and late stages of information processing and its application to ambiguous object recognition.