Neurons that keep a straight face

Abstract

Recognizing a person we know seems like an unremarkable occurrence within the stream of everyday events. However, the ease with which most of us recognize a familiar face belies the daunting complexity of the underlying computational challenges—challenges that become apparent in the not so rare cases of face-blindness and in attempts to develop computational models that mimic human face recognition performance. Neuroscience has shown, since the discovery of face-selective cells in the early 1970s, that face recognition is a highly evolved ability in primates that relies on very specialized hardware: we now know that millions of face cells exist in the primate brain, that they are specialized for the processing of particular facial dimensions depending on which area they are located in, and that this spatial segregation of function is maintained within a network of highly interconnected face areas. Even some of the algorithms by which face cells detect and analyze faces are becoming clear. How this highly sophisticated face-processing system comes about, and how individual cells acquire their selectivity, is still the matter of much debate, yet it is clear that experience with the visual world, and with faces in particular, must play an important role. In PNAS, McMahon et al. (1) now provide an entirely new perspective on the question of plasticity in face recognition. With a new technical approach that allows for the activity of face cells to be monitored over days, weeks, months, and, in rare cases, even a year, they determined the selectivity of face cells in one part of the brain and found it to be remarkably stable over these long periods of time. This finding comes as a great surprise to a field that has gotten used to the notion of plasticity, and might indicate a hitherto unrealized form of functional specialization within the primate face-recognition system.

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