Abstract
Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity) in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion) in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG) from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60–150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus.
Highlights
IntroductionWhile debates about the modularity of face processing continue [26,27] there is consensus in the notion of a faceprocessing system that encompasses specific sectors of temporal visual cortex
Faces are processed by a relatively dedicated but anatomically distributed system
We analyzed the intracranial ECoG with a decoding technique and found that 1) the best discrimination of faces from checkerboards arose within a critical frequency band of 50–150 Hz in the ventral temporal cortex, 2) this held for both static and dynamic stimuli, 3) the accuracy of decoding was much better in ventral as compared to lateral temporal cortex, for faces vs. checkerboards, and for happiness vs. fear, 4) in the ventral temporal cortex, task-relevant attention improved the decoding accuracy for stimulus category (A’fc) across wide frequencies by as much as 11%, but it did not improve decoding accuracy for emotion (A’em) and gender (A’gn), and 5) the anterior superior temporal sulcus (STS) and the ventral temporal cortex showed evidence for hemispheric specialization of face processing
Summary
While debates about the modularity of face processing continue [26,27] there is consensus in the notion of a faceprocessing system that encompasses specific sectors of temporal visual cortex Distinct facial attributes, such as emotional expression, gender, and identity, are extracted through this face processing system in partly segregated functional streams [28,29,30,31]. It is thought that while static aspects of a face, such as its gender and identity, are encoded primarily in the ventral temporal regions, dynamic information, such as emotional expression, depends on the lateral and superior regions in the superior temporal sulcus and gyrus [9,24,25,28]. It is of special interest to contrast the information represented within the ventral temporal cortex with that represented in the lateral temporal cortex, and to examine the issue at a more precise resolution in time and frequency
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