Normal human brains effortlessly decide the difference between a face and not a face, even when an object significantly resembles a human face, observes an Indian origin neuroscientist.
His team at MIT found that our brains are adept at locating images that look like faces whether it's New Hampshire's erstwhile granite "Old Man of the Mountain," or Jesus' face on a tortilla, but the normal human brain is almost never fooled into thinking such objects actually are human faces.
"You can tell that it has some 'faceness' to it, but on the other hand, you're not misled into believing that it is a genuine face," said Pawan Sinha, professor of brain and cognitive sciences at MIT.
Sinha and his colleagues reveal the brain activity that underlies our ability to make that distinction.
On the left side of the brain, the fusiform gyrus - an area long associated with face recognition - carefully calculates how "facelike" an image is.
The right fusiform gyrus then appears to use that information to make a quick, categorical decision of whether the object is, indeed, a face.
For the study, the researchers created a continuum of images ranging from those that look nothing like faces to genuine faces.
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 non-face 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 non-faces.
From this, the researchers concluded that the left side of the brain is ranking images on a scale of how face-like 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. It tries to determine how face-like is a pattern, without making the final decision on whether I'm going to call it a face," Sinha stated.
The findings were published in the Proceedings of the Royal Society B Jan. 4.