A general-purpose mechanism of visual feature association in visual word identification and beyond


Current Biology


January, 2021


Yamil Vidal, Eva Viviani, Davide Zoccolan and Davide Crepaldi

As writing systems are a relatively novel invention (slightly over 5 kya), they could not have influenced the evolution of our species. Instead, reading might recycle evolutionary older mechanisms that originally supported other tasks and preceded the emergence of written language. Accordingly, it has been shown that baboons and pigeons can be trained to distinguish words from nonwords based on orthographic regularities in letter co-occurrence. This suggests that part of what is usually considered reading-specific processing could be performed by domain-general visual mechanisms. Here, we tested this hypothesis in humans: if the reading system relies on domain-general visual mechanisms, some of the effects that are often found with orthographic material should also be observable with non-orthographic visual stimuli. We performed three experiments using the same exact design but with visual stimuli that progressively departed from orthographic material. Subjects were passively familiarized with a set of composite visual items and tested in an oddball paradigm for their ability to detect novel stimuli. Participants showed robust sensitivity to the co-occurrence of features (‘‘bigram’’ coding) with strings of letter-like symbols but also with made-up 3D objects and sinusoidal gratings. This suggests that the processing mechanisms involved in the visual recognition of novel words also support the recognition of other novel visual objects. These mechanisms would allow the visual system to capture statistical regularities in the visual environment. We hope that this work will inspire models of reading that, although addressing its unique aspects, place it within the broader context of vision.

The paper is published in Current Biology. A pre-print is also available on biorXiv. An author-formatted post-print is also available here below.