More recent studies have suggested that there may even be particular neurons tuned to the identity of one particular person. These neurons, according to that theory, lie in the "fusiform face area," FFA, known to be particularly active when a person encounters a face.
However, in the April 6, 2006 issue of Neuron, Maximilian Riesenhuber of Georgetown University Medical Center and his colleagues (Jiang et al.) report evidence for a theory that the FFA, instead, contains tightly integrated circuitry that recognizes faces based on selective processing of shapes of facial features.
In their studies, the researchers first constructed a computational model that represented how their hypothesized neuronal circuitry would work. This model aimed at predicting how the circuitry could give rise to the perception of faces. Such perception includes the shape of specific features--eyes, noses, and mouths--as well as the "configuration" of those features--their position on the face.
The researchers found that their model captured such aspects of face perception, even though the circuitry in their model had not explicitly coded them. To demonstrate that their model could also account for how other neuronal circuitry could be similarly tuned to other objects, they also tested how it might behave when it encountered images of cars. They found that model worked just as well to produce the same recognition characteristics as in faces.
Riesenhuber and his colleagues tested their "shape-based" model experimentally by exposing volunteers to images of faces that could be precisely "morphed" with a c
Contact: Heidi Hardman