Figure 1. Stimulus and analysis paradigm.

A, 2100 facial photos from multiple face databases were used in this experiment. Three examples are shown. B, Images were presented to the animal while recording from the most anterior face patch AM (anterior medial face patch). The electrode track targeting AM is shown in coronal MRI slices from two animals. C, Each facial image was analyzed using 9 different models. The same number of features were extracted from units of different models using principal component analysis (PCA) for comparison. D, Different models were compared with respect to how well they could predict neuronal responses to faces. A 10-fold cross-validation paradigm was employed for quantification: 2100 faces were evenly distributed into 10 groups. Responses of each neuron to 9 groups were fit by linear regression using features of a particular face model, and the responses of this neuron to the remaining 210 faces were predicted using the same linear transform. To quantify prediction accuracy, we compared predicted responses to individual faces in the space of population responses to either the actual response to that face or that to a distractor face. If the angle between predicted response and target response was smaller than that between predicted response and distractor response, the prediction was considered correct. All pairs of faces were used as both target and distractor and the proportion of correct predictions was computed.