Similarities and differences in the spatio-temporal neural dynamics underlying the recognition of natural images and line drawings

Humans effortlessly recognize line drawings of objects, indicating the robustness of our visual system to the abstraction of substantial amounts of visual information. Previous work has demonstrated that recognition of line drawings engages the same brain regions that support natural object recognition. Yet, it remains unknown if the spatial and temporal representational dynamics of object recognition are similar for photos and drawings, or, alternatively, whether distinct mechanisms are recruited for drawings, leading to different representational structure across space and time. To address this question, we collected MEG (N=22) and fMRI (N=23) data while participants passively viewed the same object images depicted as either photographs, line drawings or sketch-like drawings - with each type of depiction representing one level of visual abstraction. Using multivariate pattern analysis, we demonstrate that, regardless of the level of visual abstraction, information about the category of an object can be read out from MEG data rapidly after stimulus onset. For the fMRI data we found significant above-chance decoding accuracies in overlapping parts of the occipital and ventral-temporal cortex for all types of depiction. In addition, object category information generalized strongly between types of depiction, beginning already in early visual processing and persisting in later processing stages. MEG-fMRI fusion based on representational similarity analysis revealed a largely similar spatio-temporal pattern for all types of depiction, first reaching early visual cortex and later high-level object-selective regions. Despite these similarities, photos showed overall stronger effects. Together, our findings reveal broad commonalities in the spatio-temporal representational dynamics of object recognition for natural images and drawings. These results constrain potential models of object recognition by demonstrating that the same mechanisms our brains use to resolve object recognition for natural object images may also hold for object drawings, from the earliest processing stages.