The roles of the fusiform face area have received much debate in the past literature over the years. Researchers have been actively measuring the function of the fusiform face area (FFA) using functional magnetic resonance imaging (fMRI) and behavioral outcome in perceptual task to explore the roles of FFA in the detection and identification of face and object (Grill-Spector, 2004). However, FFA was not only active during face viewing & object viewing, but also evolved for processing of extremely familiar object where face was the more prominent for majority of normal individual (Gauthier, Skudlarski, Gore & Anderson, 2000).
Many researchers have been debating whether face perception was domain-specific or domain-general as the face-specificity remains controversial. Yet, many researchers have selectively favored alternative ‘domain-general’ which generally argue that mechanisms engaged by faces were not normally specific for a particular stimulus class, but for certain particular process that may runs on multiple stimulus classes (Yovel & Kanwisher, 2004). In neurological patient who has prosopagnosia, losing ability to recognize face after brain damages suggested that face perception engages specialized machinery distinct from when engaged during object perception. This impairment in face recognition was often followed by deficits in other related tasks such as object recognition due to large size of lesion comparative to functional subdivision of the cortex. Nevertheless, some prosopagnosia patients shows slightly selective impairment in which face-recognition abilities were misperceived despite the lack of visible deficits in the recognition of non- face object (Wada & Yamamoto 2001). Literature further suggested that there were still selective people with acquired prosopagnosia having apparently normal object recognition (Wada & Yamamoto 2001; Humphreys 2005), showed that cortical regions that were necessary for face recognition but not necessary for object recognition.
Some classic behavioral work in normal subjects has also shown dissociations between the recognition of faces and objects by exhibiting a number of differences in the ways that faces and objects were being processed. A common known example among these signatures of face-specific processing was face-inversion effect, in which the reduction in performance that occurs when stimuli were being inverted much more in faces stimuli than for non-face stimuli (Yin, 1969). This display certain degrees of consistency with the holistic hypothesis as these effects proposed that upright faces were processed in a unique ‘holistic’ manner (McKone, Martini, & Nakayama, 2001; Tanaka & Farah, 2003).Thus, despite the divergent widespread claims, behavioral data from normal subjects do not support the expertise hypothesis. Instead, behavioral signatures of configural/holistic processing in the inversion effect were partially/completely reduced or absent in the composite effect for non-face stimuli, including objects of expertise. These findings support the face-specificity hypothesis and disagree against each of its domain-general alternatives.
Although the most consistent and robust face selective fMRI activation was located on the lateral side of the mid-fusiform gyrus in a region named the ‘fusiform face area’ or FFA (Kanwisher, McDermott & Chun, 1997), face-specific fMRI activations were usually in the region of the superior temporal sulcus (fSTS) and in the occipital lobe – ‘occipital face area’ (OFA). Fusiform face area responds intensely and commonly to a wide variety of faces stimuli that would appears to have low-level feature in general with more greatly in upright when compared to inverted mooney face even though both picture was identical and when the face was perceived than when face was not perceived even though the retinal stimulation was unchanged. Evidently, it shows impossibility to engage the FFA on non-face stimuli by inducing subjects to process those stimuli like faces. On the other hand, it remains an open question whether there was any way to induce face-like holistic processing on non-face stimuli, and whether such processing would triggers the FFA (Tanaka & Farah, 2003).
In a modular view of face and object processing, Haxby, Gobbini, Furey, Ishai, Schouten & Pietrini (2001) argued that via the various profile of responses across ventral visual pathway, objects and faces were being coded. Haxby and colleagues (2001) suggested that ‘non-preferred’ responses to objects in the FFA may form a significant part of the neural code for those objects. Nonetheless, two studies on humans (Spiridon & Kanwisher 2002) and monkeys (Tsao, Freiwald, Knutsen, Mandeville & Tootell, 2003) have found that the profile of response across the voxels within face-selective patches in humans or in the monkeys does not contain information enabling discrimination between different non-faces. Even if some discriminative information about non-face objects were present in the FFA, perhaps it could only be explored at a much higher resolution in perceptual performance. In Tsao and colleagues’ (Tsao, Freiwald, Tootell & Livingstone, 2006) single-unit recording on monkey from face- selective patches, results denoted that non-preferred response were virtually non-existent. It suggested that observed responses maybe causes from blurring responses from a particularly face selective FFA with neighboring non-face selective cortex (Schwarzlose, Baker & Kanwisher, 2005). Therefore, it explained the non- preferred responses in the FFA play an important role in coding for non-face objects.
In Yovel & Kanwisher’s (2004) experiment to find out how do the FFA respond to faces, they found that FFA does not appear to be sensitive to only a few specific face features, but instead seems to respond generally to a wide range of features evolving around the whole face. Several studies have also found adaptation across recurring images of the same face even when those images varies in position or image size (Grill-Spector, Kushnir, Edelman, Avidan, Itzchak & Malach, 1999; Andrews & Ewbank, 2004) or even spatial scale (Eger, Schyns & Kleinschmidt, 2004).Thus, depiction in the FFA were not furrowed to very low-level image properties, but instead displayed at least partial invariance to simple image transformations. These findings proposed that long-term adaptation may reveal several invariant properties of face representation in face-selective regions, which were not present in the typically used short-term adaptation. In general, studies conducted to date congregate on the conclusion that neural representations of faces in the FFA distinguished between faces of different individuals and were partly invariant to simple image transformations as well as size, position and spatial scale. Although, these representations were not invariant to variations in viewpoint, lighting and other non-affine image transformations. These studies do not show a constantly different FFA response for familiar versus unfamiliar faces. As these results may only show that the FFA merely abstracts a perceptual representation from faces in a bottom-up fashion, with actual recognition following at a later stage of processing. It may also be possible that information about face familiarity was embodying in the FFA but not by an overall difference in the mean response. However, these studies do allow address of a different question about the FFA, regarding its role in processing of non-visual semantic information on people. Although there were some studies which displays slightly differences (Haxby, Ungerleider, Clark, Schouten, Hoffman & Martin, 1999; Kanwisher Yin & Wojciulik, 1999) or completed no difference (Aguirre, Singh & D’Esposito, 1999; Leube Yoon, Rapp, Erb, Grodd, Bartels & Kircher, 2003) in the response to upright and inverted faces.
Similarly, in the same study by Yovel & colleagues’ (2004;2005), they also show a substantially higher FFA, performance, fMR adaptation in response for upright compared with inverted faces, FFA-face-inversion effect was correlated across subjects with the behavioral face-inversion effect. It indicates that the FFA was further sensitive to identity information in upright than inverted faces. Thus, consistent with the behavioral face-inversion effect, FFA better discriminates faces when they were upright than inverted. When functional MRI studies of face expression have primarily emphasis on the amygdala (Glascher, Tuscher, Weiller & Buchel, 2004; Williams, Morris, McGlone, Abbott & Mattingley, 2004), studies investigated the response of the temporal cortex displayed higher responses to emotional than neutral faces in the fusiform gyrus (Breiter et al. 1996; Dolan, Morris & deGelder, 2001; Vuilleumier et al. 2001, 2003; Williams et al. 2004). It was proposed that this effect was modulated by connections from the amygdala (Dolan et al. 2001) as FFA may indicate a general arousal effect other than specific representation of facial expression. Indeed, a recent functional magnetic resonance adaptation (fMR-a) study (Winston, Vuilleumier & Dolan, 2003), in which expression and identity were manipulated in a factorial manner, did not display significant fMR adaptation to expression information in the fusiform gyrus, but displayed fMR adaptation to face expression in regions in the STS. These findings were consistent with the idea that the FFA was immersed in identity, but not expression processing, whereas the STS shows the opposite pattern of response (Haxby, Hoffman & Gobbini, 2000). In spite, a recent study found a higher FFA response during expression judgments than during identity judgments on faces (Ganel, Valyear, Goshen-Gottstein & Goodale, 2005), it still forms some doubt on the simple idea that the FFA was involved only in processing face identity information.
Numerous behavioral experiments have further suggested that representations of faces differ in important respects from representations of non-face objects. If the FFA plays an important role in the generation of these ‘special’ face representations, there should be parallel changes in the pattern of the blood oxygenation level dependent (BOLD) response in FFA versus response of other cortical regions intricate in representing object shape, such as the lateral occipital complex (LOC). Importantly, object-selective regions were defined as cortical regions that respond more strongly to objects than to scrambled images of objects, rather than as regions that respond more strongly to objects than faces. When a comparison was being make in some studies (Aguirre et al. 1999; Haxby et al. 1999; Andrews & Schluppeck, 2004) a functionally very different region called the parahippocampal place area (PPA; Epstein & Kanwisher, 1998) was being found but not LOC. The response to faces was very minimal to begin with in this region when the problem using the region identified with a contrast of objects greater than faces, so the absence of sensitivity to stimulus manipulations found suggested could be just due to floor effects.
In contrast, the LOC shows a high response to faces, in particular in its lateral occipital region, and it was therefore a more justifiable region to compare to the FFA. Several studies have recently reported robust dissociations between the response of the LOC and the FFA. First, the FFA and LOC display important and obvious differences in the face-inversion effect. Whereas the FFA shows a slightly higher response to upright than inverted faces, whereas, the LOC shows a directly opposite effect on higher responses in inverted faces then upright face (Yovel, Duchaine, Nakayama & Kanwisher, 2005b; Aguirre et al.1999; Haxby et al. 1999). Second, the sensitivity of FFA to identify information in face with differed in their parts or in the spacing among these parts was assessed using event related fMR-adaptation technique found that face stimuli with slightly differences between the faces creates strong adaptation for these faces in the FFA but no adaptation to faces in LOC.
These findings reverberate with theories of object recognition, which emphasize the role of parts in representations of object shape (Hoffman & Richards 1984; Biederman 1987), and contrast sharply with theories of face processing, which emphasize holistic representations. Taken together, these findings indicate that the representations in the FFA vary in many respects from the representations in LOC. Thus, the FFA was not only selective for faces, but also generates a specialized representation of faces that was qualitatively different from representations of faces in other regions.
Findings by Rotshtein, Henson, Treves, Driver & Dolan (2005) showed that the OFA was more sensitive to physical aspects of the face stimulus than the FFA. In their adapted face experiment, the OFA showed a similar response to two faces that vary physically regardless of whether the subject perceived the two stimuli as similar or different. Studies examined the response of both the FFA and the fSTS shows that the FFA but not the fSTS was correlated with successful face detection. Andrews & Schluppeck (2004) found that FFA response was stronger for face than blob percepts, the fSTS showed no variations between the two types of trials. These findings were in line with Grill-Spector (2004) study, who found that the response of the FFA was related with successful detection of faces in brief masked stimuli, but the response of the fSTS was not. The failure to find an association with successful face detection in the fSTS when stimuli were held constant was somewhat surprising, given that this region by definition responds more strongly when faces were present than when they were not. In any event, the association with successful face detection of the FFA but not fSTS, which was found in both studies, shows dissociation between the two regions. Given the findings just described, it was not surprising that the fSTS shows no sensitivity to face identity information
Taken together, these data suggested a robust dissociation between the face representations in the fSTS and the FFA, in which the FFA but not the fSTS display identity information. The evidence reviewed here suggested that the FFA differs functionally in a number of respects from both the shape-selective LOC and the two other best-known face-selective regions of cortex, the OFA and fSTS. Functional ROI analyses were however criticized for focusing narrowly on one brain region, while ignoring the rest of the brain. A functional region of interest (fROI) investigation of the FFA which was followed by similar analyses of nearby regions allows assess the extent to which the FFA response was indeed ‘special’. The clear functional dissociations between these regions also displayed the functional localizers used to define these regions indeed were picking out functionally distinct regions, reinforcing the importance of studying them independently. Many of the functional dissociations described would probably not be obvious in a group analysis, because the necessarily imperfect registration of physically different brains would blur across nearby but functionally distinct regions such as the FFA and LOC.
In conclusion, it is interesting to know that experience sure play some instructive role in the development of face areas, given the ample evidence that neurons in the ventral visual pathway are tuned by experience (Baker et al. 2002). Furthermore, observations leave open a vast space of possible scenarios in which genes and environment could interact in the construction of a selective region of cortex such as the FFA, as genetic factors may also contribute to the construction of face-processing mechanisms.