Cortical dynamics of material and shape perception across illumination and viewpoint

Navigating our dynamic world, from traversing pebbly beaches to grasping slippery objects, demands an adept interpretation of visual information. For example, information about an object’s material and shape are important for understanding its behavioral affordances. We hypothesize that cortical dynamics during object viewing will reflect visual regularities arising from the object’s intrinsic properties, independent of viewpoint and illumination. To investigate this, we recorded magnetoencephalography (MEG) data while participants viewed 256 photorealistic object stimuli as part of an n-back task. These stimuli varied in material (e.g., rock, wool) and geometry (e.g. cuboid-, dome-shaped), and were presented in natural lighting conditions from different viewpoints. As part of these manipulations, the objects’ surfaces varied in their complex mesostructure (medium-scale surface relief) and reflectance, leading to changes in in behaviorally relevant qualities, such as softness and roughness. Using the MEG sensor activation patterns and a linear classifier, we were able to decode both material and shape properties even across various viewpoints and lighting conditions. Subsequent analyses characterized links between distinct image information produced by these properties and the cortical dynamics observed. Our findings support the notion that cortical dynamics during object perception reflect affordance-related attributes inherent to an object's material and shape and enrich our understanding of how the perception of behaviorally relevant object properties unfolds.