TY - JOUR T1 - Shape coding in occipito-temporal cortex relies on object silhouette, curvature and medial-axis JF - bioRxiv DO - 10.1101/814251 SP - 814251 AU - Paolo Papale AU - Andrea Leo AU - Giacomo Handjaras AU - Luca Cecchetti AU - Pietro Pietrini AU - Emiliano Ricciardi Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/10/22/814251.abstract N2 - Object recognition relies on different transformations of the retinal input, ranging from local contrast to object shape and category. While some of those representations are thought to occur at specific stages of the visual hierarchy, many of them are correlated (e.g., object shape and identity) and can be retrieved from the activity of several brain regions. This overlap may be explained either by collinearity across representations, or may instead reflect the coding of multiple dimensions by the same cortical population. Moreover, orthogonal and shared components may differently impact on distinctive stages of the visual hierarchy. We recorded functional MRI (fMRI) activity while participants passively attended to objects, and employed a statistical approach that partition orthogonal and shared object representations to reveal their relative impact on brain processing. Orthogonal shape representations (i.e., silhouette, curvature and medial-axis) independently explain distinct and overlapping clusters of selectivity in occitotemporal (OTC) and parietal cortex. Moreover, we showed that the relevance of shared representations linearly increases moving from posterior to anterior regions. These results indicate that the visual cortex encodes shared relations between different features in a topographic fashion and that object shape is encoded along different dimensions, each representing orthogonal features.New & Noteworthy While we always have available a general sense of what ‘a shape is’, what is the computational counterpart of this immediate percept? Here, we employed three competing shape models to explain brain representations when viewing real objects. We found that object shape is encoded in a multi-dimensional fashion and thus defined by the interaction of multiple features. ER -