Tsantani, M. | bioRxiv Science

bioRxiv2020

FFA and OFA encode distinct types of face identity information

Faces of different people elicit distinct functional MRI (fMRI) patterns in several face-selective brain regions. Here we used representational similarity analysis to investigate what type of identity-distinguishing information is encoded in three face-selective regions: fusiform face area (FFA), occipital face area (OFA), and posterior superior temporal sulcus (pSTS). We used fMRI to measure brain activity patterns elicited by naturalistic videos of famous face identities, and compared their representational distances in each region with models of the differences between identities. Models included low-level to high-level image-computable properties and complex human-rated properties. We found that the FFA representation reflected perceived face similarity, social traits, and gender, and was well accounted for by the OpenFace model (deep neural network, trained to cluster faces by identity). The OFA encoded low-level image-based properties (pixel-wise and Gabor-jet dissimilarities). Our results suggest that, although FFA and OFA can both discriminate between identities, the FFA representation is further removed from the image, encoding higher-level perceptual and social face information.

neuroscience↗

bioRxiv2018

Faces and voices in the brain: a modality-general person-identity representation in superior temporal sulcus

Face-selective and voice-selective brain regions have been shown to represent face-identity and voice-identity, respectively. Here we investigated whether there are modality-general person-identity representations in the brain that can be driven by either a face or a voice, and that invariantly represent naturalistically varying face and voice tokens of the same identity. According to two distinct models, such representations could exist either in multimodal brain regions (Campanella and Belin, 2007) or in face-selective brain regions via direct coupling between face- and voice-selective regions (von Kriegstein et al., 2005). To test the predictions of these two models, we used fMRI to measure brain activity patterns elicited by the faces and voices of familiar people in multimodal, face-selective and voice-selective brain regions. We used representational similarity analysis (RSA) to compare the representational geometries of face- and voice-elicited person-identities, and to investigate the degree to which pattern discriminants for pairs of identities generalise from one modality to the other. We found no matching geometries for faces and voices in any brain regions. However, we showed crossmodal generalisation of the pattern discriminants in the multimodal right posterior superior temporal sulcus (rpSTS), suggesting a modality-general person-identity representation in this region. Importantly, the rpSTS showed invariant representations of face- and voice-identities, in that discriminants were trained and tested on independent face videos (different viewpoint, lighting, background) and voice recordings (different vocalizations). Our findings support the Multimodal Processing Model, which proposes that face and voice information is integrated in multimodal brain regions.\n\nSignificance statementIt is possible to identify a familiar person either by looking at their face or by listening to their voice. Using fMRI and representational similarity analysis (RSA) we show that the right posterior superior sulcus (rpSTS), a multimodal brain region that responds to both faces and voices, contains representations that can distinguish between familiar people independently of whether we are looking at their face or listening to their voice. Crucially, these representations generalised across different particular face videos and voice recordings. Our findings suggest that identity information from visual and auditory processing systems is combined and integrated in the multimodal rpSTS region.

neuroscience↗