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Face processing is a function that is highly lateralized in humans, as supported by original evidence from brain lesion studies (Hecaen & Anguerlergues, 1962), followed by studies using divided visual field presentations (Heller & Levy, 1981), neuroimaging (Sergent et al., 1992) and event-related potentials (Bentin et al., 1996). Studies in non-human primates (Perrett et al., 1988; Zangenehpour & Chaudhuri, 2005), or other mammals (Peirce & Kendrick, 2001) support the right lateralization of the function, which may be related to a dominance of the right hemisphere in global visual processing. However, in humans there is evidence that manual preference may shift or qualify the pattern of lateralization for faces in the visual cortex: face recognition impairments following unilateral left hemisphere brain damage have been found only in a few left-handers (e.g., Mattson et al., 1992; Barton, 2009). Here we measured the pattern of lateralization in the entire cortical face network in right and left-handers (12 subjects in each group) using a well-balanced face-localizer block paradigm in fMRI (faces, cars, and their phase-scrambled versions). While the FFA was strongly right lateralized in right-handers, as described previously, it was equally strong in both hemispheres in left-handers. In contrast, other areas of the face-sensitive network (posterior superior temporal sulcus, pSTS; occipital face area, OFA; anterior infero-temporal cortex, AIT; amygdala) remained identically right lateralized in both left- and right-handers. Accordingly, our results strongly suggest that the face-sensitive network is equally lateralized for left- and right-handers, and thus the face processing is not influenced by handedness. However, the FFA is an important exception since it is right-lateralized for right-handers but its recruitment is more balanced between hemispheres for left-handers. These observations carry important theoretical and clinical implications for the aetiology of brain lateralization depending on the left- or right-handedness and the neuropsychological undertaking of prosopagnosic patients.

A whole network of brain areas showing larger response to faces than other visual stimuli has been identified in the human brain using fMRI (Sergent, 1992; Haxby, 2000). Most studies identify only a subset of this network, by comparing the presentation of face pictures to all kinds of object categories mixed up (e.g., Kanwisher, 1997), or to scrambled faces (e.g., Ishaï, 2005), using different statistical thresholds. Given these differences of approaches, the (sub)cortical face network can be artificially overextended (Downing & Wiggett, 2008), or minimized in different studies, both at the local (size of regions) and global (number of regions) levels. Here we conducted an analysis of a large set of right-handed subjects (40), tested with a new whole-brain localizer to control for both high-level and low-level differences between faces and objects. Pictures of faces, cars and their phase-scrambled counterparts were used in a 2x2 block design. Group-level (random effect) and single subject (ROI) analyses were made. A conjunction of two contrasts (F-SF and F-C) identified 6 regions: FFA, OFA, amygdala, pSTS, AIT and thalamus. All these regions but the amygdala showed clear right lateralization. Interestingly, the FFA showed the least face-selective response among the cortical face network: it presented a significantly larger response to pictures of cars than scrambled cars [t=9.3, much more than amygdala (t=2.6), AIT (t=2.1) and other regions (NS)], and was also sensitive to low-level properties of faces [SF - SO; t=5.1; NS in other areas]. These observations suggest that, contrary to other areas of the network, including the OFA, the FFA is a region that may contain populations of neurons that are specific to faces intermixed with populations responding more generally to object categories. More generally, this study helps understanding the extent and specificity of the network of (sub)cortical areas particularly involved in face processing.