To help them do that, the researchers created a continuum of images ranging from those that look nothing like faces to genuine faces. They found images that very closely resemble faces by examining photographs that machine vision systems had falsely tagged as faces. Human observers then rated how facelike each of the images were by doing a series of one-to-one comparisons; the results of those comparisons allowed the researchers to rank the images by how much they resembled a face.
The research team then used functional magnetic resonance imaging (fMRI) to scan the brains of research subjects as they categorized the images. Unexpectedly, the scientists found different activity patterns on each side of the brain: On the right side, activation patterns within the fusiform gyrus remained quite consistent for all genuine face images, but changed dramatically for all nonface images, no matter how much they resembled a face. This suggests that the right side of the brain is involved in making the categorical declaration of whether an image is a face or not.
Meanwhile, in the analogous region on the left side of the brain, activity patterns changed gradually as images became more facelike, and there was no clear divide between faces and nonfaces. From this, the researchers concluded that the left side of the brain is ranking images on a scale of how facelike they are, but not assigning them to one category or another.
"From the computational perspective, one speculation one can make is that the left does the initial heavy lifting," Sinha says. "It tries to determine how facelike is a pattern, without making the final decision on whether I'm going to call it a face."
Key to the research was imaging-analysis technology that allowed the scientists to look at patterns of activity across the fusiform gyrus.
Timing is instructive
The researchers found that activation in the le
|Contact: Caroline McCall|
Massachusetts Institute of Technology