Abstract
Three-dimensional environmental boundaries fundamentally define the limits of a given space. A body of research employing a variety of methods points to their importance as cues in navigation. However, little is known about the nature of the representation of scene boundaries by high-level scene cortices in the human brain (namely, the parahippocampal place area (PPA) and retrosplenial complex (RSC)). Here we use univariate and multivoxel pattern analysis to study classification performance for artificial scene images that vary in degree of vertical boundary structure (a flat 2D boundary, a very slight addition of 3D boundary, or full walls). Our findings present evidence that there are distinct neural components for representing two different aspects of boundaries: 1) acute sensitivity to the presence of grounded 3D vertical structure, represented by the PPA, and 2) whether a boundary introduces a significant impediment to the viewer's potential navigation within a space, represented by RSC.