Abstract
Faces convey rich information including identity, gender and expression. Current neural models of face processing suggest a dissociation between the processing of invariant facial aspects such as identity and gender, that engage the fusiform face area (FFA) and the processing of changeable aspects, such as expression and eye gaze, that engage the posterior superior temporal sulcus face area (pSTS-FA). Recent studies report a second dissociation within this network such that the pSTS-FA, but not the FFA, shows much stronger response to dynamic than static faces. The aim of the current study was to test a unified model that accounts for these two functional characteristics of the neural face network. In an fMRI experiment, we presented static and dynamic faces while subjects judged an invariant (gender) or a changeable facial aspect (expression). We found that the pSTS-FA was more engaged in processing dynamic than static faces and changeable than invariant aspects, whereas the OFA and FFA showed similar response across all four conditions. These findings support an integrated neural model of face processing in which the ventral areas extract form information from both invariant and changeable facial aspects whereas the dorsal face areas are sensitive to dynamic and changeable facial aspects.
Highlights
Faces generate highly selective responses in high-level visual cortex
We ran an ANOVA with Hemisphere, Motion (Dynamic, Static) and Task (Expression, Gender) as repeated measures to assess whether there was a significant interaction of the effects of interest with hemisphere. This analysis was conducted separately for each ROI (FFA, occipital face area (OFA), posterior superior temporal sulcus face area (pSTS-FA) and MT) to maximize the number of subjects that can be included in the analysis
To assess whether the patterns of response that we found are significantly different between the dorsal and ventral face areas, we combined the data from the pSTS-FA and fusiform face area (FFA) and added ROI as a within subject factor in the ANOVA (n = 17)
Summary
Faces generate highly selective responses in high-level visual cortex. In particular, three face-selective areas are typically revealed, the occipital face area (OFA), the fusiform face area (FFA) and the posterior superior temporal sulcus face area (pSTS-FA)[1]. To integrate these two related functional characterizations of the face network, we have recently proposed a comprehensive neural model of face processing[2,9] (Fig. 2) according to which the dorsal face areas, including the pSTS-FA and IFG-FA, are engaged in the processing of facial motion and in the processing of changeable facial aspects This suggestion is based on behavioral studies showing that expression processing benefits from dynamic information more than identity processing[10,11,12,13]. To assess the proposed links between the face areas for the processing of dynamic faces, we examined the functional connectivity among the face areas and with the motion area, MT
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