What makes faces special?

Abstract

What may be special about faces, compared to non-face objects, is that their neural representation may be fundamentally spatial, e.g., Gabor-like. Subjects matched a sequence of two filtered images, each containing every other combination of spatial frequency and orientation, of faces or non-face 3D blobs, judging whether the person or blob was the same or different. On a match trial, the images were either identical or complementary (containing the remaining spatial frequency and orientation content). Relative to an identical pair of images, a complementary pair of faces, but not blobs, reduced matching accuracy and released fMRI adaptation in the fusiform face area.

Fig. 1

Generation of visual stimuli. (a) Blobs were generated by combining the 2nd and 3rd harmonics of a sphere in eight different orientations. (b) Blob space produced by combining different orientations of the 2nd and 3rd harmonics, as shown by the orientations shown above and to the left of the blob space. Proximate blobs were highly similar in shape and those distant were less similar, as confirmed by a Gabor-jet similarity measure. The four circled blobs were the seeds used to generate the blob spaces, defined by variation in the sizes of the 2nd and 3rd harmonics. (c) A blob space generated by holding constant the orientation of the harmonics but only varying their size, as shown above and to the left of the blob space. The illustrated space is generated from the upper left circled blob in (b). The variations in sizes of the harmonics are taken to mimic the variation in the sizes and distances of facial parts. Both experts and novices were tested with one of the four spaces, but the experts gained their expertise on a space defined by a seed diagonally opposite to their test space. Numbers along arrowed lines pointing to pairs of blobs show the Gabor-jet similarity values for those pairs as a percent of an identity match ( = 100).

Fig. 2

Complementary images were created by filtering an image in the Fourier domain into 8 orientations by 8 spatial frequencies. The content of every other 32 frequency-orientation combinations, as illustrated by the circular checkerboards, was assigned to one image of a complementary pair and the remaining content to the other member of that pair. Each member of a complementary pair thus had all 8 orientations and all 8 frequencies but in different combinations. The Fourier-domain images were then converted to images in the spatial domain by inverse FFT. (a) An example with a face. (b) An example with a blob.

Fig. 3

Localizer images and BOLD responses at the right FFA and LOC. (a) Examples of images were used in the localizer runs. (b) The left panel shows one subject's right FFA defined by a conjunction of Faces minus Object and Faces minus Scrambled-faces projected to an inflated brain. The right panel shows the event-related average percent BOLD signal change for the five classes of images. The colours of the lines are indicated in (a). (c) The left panel shows one subject's right LOC defined by a conjunction of Objects minus Textures and Blobs minus Textures. The right panel shows event-related average BOLD response for five classes of images. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this paper.)

Fig. 4

Same-different proportion error rates for matching Identical and Complementary faces and blobs for (a) novices, (b) experts, and (c) the Ideal Observer. Error bars are SEM. Because the main effect of identity (same vs. different person/blob) was not significant, they were combined in these figures.

Fig. 5

Hemodynamic response functions of blob experts and blob novices to blobs and faces at FFA (left and right hemispheres combined). (a) Hemodynamic response functions of blob experts to faces (left) and blobs (right). (b) Hemodynamic response functions of blob novices to faces (left) and blobs (right). Labels: Ps-FOCs, person same and frequency-orientation combination same; Ps-FOCd, person same and frequency-orientation combination different; Pd-FOCs, person different and frequency-orientation combination same; Pd-FOCd, person different and frequency-orientation combination different; Bs-FOCs, blob same and frequency-orientation combination same; Bs-FOCd, blob same and frequency-orientation combination different; Bd-FOCs, Blob different and frequency-orientation combination same; Bd-FOCd, blob different and frequency-orientation combination different.

Fig. 6

Hemodynamic response functions for correct trials when matching faces in right FFA, combined across blob experts and novices, showing a release from adaptation for a change in the person (identity) or a change in the frequency-orientation combination.

Fig. 7

Hemodynamic response functions in LOC for changes in Identity and frequency-orientation combinations when matching faces. As there were no differences between left and right LOC and blob experts and novices, the data are shown collapsed over these variables. Neither person nor spatial content produced a release from adaptation (in contrast to the pattern produced in right FFA for faces shown in Fig. 6).

Fig. 8

Hemodynamic response functions in LOC for blob experts and novices. Blob experts (left) showed larger response to blobs than blob novices (right) in all conditions.

Fig. 9

Hemodynamic response functions in the right LOC for blob experts when matching blobs. There was a significant release from adaptation with a change in blob identity, but the apparent release with a change in frequency-orientation content was non-significant.