Smooth versus Textured Surfaces: Feature-Based Category Selectivity in Human Visual Cortex.

In fMRI studies, human lateral occipital (LO) cortex is thought to respond selectively to images of objects, compared with nonobjects. However, it remains unresolved whether all objects evoke equivalent levels of activity in LO, and, if not, which image features produce stronger activation. Here, we used an unbiased parametric texture model to predict preferred versus nonpreferred stimuli in LO. Observation and psychophysical results showed that predicted preferred stimuli (both objects and nonobjects) had smooth (rather than textured) surfaces. These predictions were confirmed using fMRI, for objects and nonobjects. Similar preferences were also found in the fusiform face area (FFA). Consistent with this: (1) FFA and LO responded more strongly to nonfreckled (smooth) faces, compared with otherwise identical freckled (textured) faces; and (2) strong functional connections were found between LO and FFA. Thus, LO and FFA may be part of an information-processing stream distinguished by feature-based category selectivity (smooth > textured).

A problem of overlap.

Here we propose that earlier-demonstrated details in the primate visual cortical map may account for an otherwise puzzling (and problematic) finding in the current human fMRI literature. Specifically, the well-known regions LO and MT(+) reportedly overlap in the human cortical visual map, when those two regions are localized using standard stimulus comparisons in conventional fMRI experiments. Here we describe evidence supporting the idea that the apparent functional overlap between LO and MT arises from a third area (the MT crescent: "MTc"), which is well known to surround posterior MT based on earlier histological, neuroanatomical, and electrophysiological studies in nonhuman primates. If we assume that MTc also exists in human visual cortex, and that it has a location and functional properties intermediate to those in LO and MT, simplistic modeling confirmed that this arrangement could produce apparent overlap between localizers for LO and MT in conventional fMRI maps in human visual cortex.

Thinking outside the box: rectilinear shapes selectively activate scene-selective cortex.

Fifteen years ago, an intriguing area was found in human visual cortex. This area (the parahippocampal place area [PPA]) was initially interpreted as responding selectively to images of places. However, subsequent studies reported that PPA also responds strongly to a much wider range of image categories, including inanimate objects, tools, spatial context, landmarks, objectively large objects, indoor scenes, and/or isolated buildings. Here, we hypothesized that PPA responds selectively to a lower-level stimulus property (rectilinear features), which are common to many of the above higher-order categories. Using a novel wavelet image filter, we first demonstrated that rectangular features are common in these diverse stimulus categories. Then we tested whether PPA is selectively activated by rectangular features in six independent fMRI experiments using progressively simplified stimuli, from complex real-world images, through 3D/2D computer-generated shapes, through simple line stimuli. We found that PPA was consistently activated by rectilinear features, compared with curved and nonrectangular features. This rectilinear preference was (1) comparable in amplitude and selectivity, relative to the preference for category (scenes vs faces), (2) independent of known biases for specific orientations and spatial frequency, and (3) not predictable from V1 activity. Two additional scene-responsive areas were sensitive to a subset of rectilinear features. Thus, rectilinear selectivity may serve as a crucial building block for category-selective responses in PPA and functionally related areas.