Face_perception

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Face perception

Face perception is the process by which the brain and mind understand and interpret the face, particularly the human face.

The face is an important site for the identification of others and conveys significant social information. Probably because of the importance of its role in social interaction, psychological processes involved in face perception are known to be present from birth, to be complex, and to involve large and widely distributed areas in the brain. These parts of the brain can be damaged to cause a specific impairment in understanding faces known as prosopagnosia.

Development

While there is no question that the majority of face perception skills developed by adults are not present in babies, there is evidence of an innate tendency to pay attention to faces from birth. It is known that early perceptual experience is crucial to the development of visual perception and this orienting response undoubtedly encourages the rapid development of face specific skills such as the ability to identify friendly others and relatively complex pre-verbal communication. By two months of age face perception has developed so specific areas of the brain are known to be activated by viewing faces.

Adult face perception

Theories about the processes involved in adult face perception have largely come from two sources: research on normal adult face perception and the study of impairments in face perception that are caused by brain injury or neurological illness.

One of the most widely accepted theories of face perception argues that understanding faces involves several stages: from basic perceptual manipulations on the sensory information to derive details about the person (such as age, gender or attractiveness), to being able to recall meaningful details such as their name and any relevant past experiences of the individual.

This model (developed by psychologists Vicki Bruce and Andrew Young) argues that face perception might involve several independent sub-processes working in unison.

A 'view centred description' is derived from the perceptual input. Simple physical aspects of the face are used to work out age, gender or simple facial expressions. Most analysis at this stage is on feature-by-feature basis.
This initial information is used to create a structural model of the face, which allows it to be compared to other faces in memory, and across views. This explains why the same person seen from a novel angle can still be recognised. This structural encoding can be seen to be specific for upright faces as demonstrated by the Thatcher effect.
The structurally encoded representation is transferred to notional 'face recognition units' which in conjunction with 'person identity nodes' allow the person to be identified by information from semantic memory. Interestingly, the ability to produce someone's name when presented with their face has been shown to be selectively damaged in some cases of brain injury, suggesting that naming may be a separate process from being able to produce other information about a person.

The study of prosopagnosia (an impairment in recognising faces which is usually caused by brain injury) has been particularly helpful in understanding how normal face perception might work. Individuals with prosopagnosia may differ in their abilities to understand faces, and it has been the investigation of these differences which has suggested that several stage theories might be correct.

Face perception is an ability which involves a great deal of the brain, however some areas have been shown to be particularly important. Brain imaging studies typically show a great deal of activity in an area of the temporal lobe known as the fusiform gyrus, an area also known to cause prosopagnosia when damaged (particularly when damage occurs on both sides). This evidence has led to a particular interest in this area and it is sometimes referred to as the fusiform face area for that reason.

Neuroanatomy of facial processing

Facial perception has well identified, neuroanatomical correlates in the brain. Most scientists agree that during the perception of faces, major activations occur in the extrastriate areas bilaterally, particularly in the fusiform gyri and in the inferior temporal gyri. Others have shown that the fusiform gyri are preferentially responsive to faces, whereas the parahippocampal/lingual gyri are responsive to buildings. Ishai and colleagues have proposed the object form topology hypothesis, which posits that there is a topological organisation of neural substrates for object and facial processing. However, Gauthier disagrees and suggests that the category-specific and process-map models could accommodate most other proposed models for the neural underpinnings of facial processing. Most neuroanatomical substrates for facial processing are perfused by the middle cerebral artery (MCA). Therefore, facial processing has been studied using measurements of mean cerebral blood flow velocity in the middle cerebral arteries bilaterally. During facial recognition tasks, greater changes in the right middle cerebral artery (RMCA) than the left (LMCA) have been observed. It has been demonstrated that men were right lateralised and women left lateralised during facial processing tasks.

Gender-related asymmetry in facial processing

The mechanisms underlying gender-related differences in facial processing have not been studied extensively. Studies using electrophysiological techniques have demonstrated gender-related differences during a face recognition memory (FRM) task and a facial affect identification task (FAIT). The male subjects used a right, while the female subjects used a left, hemisphere neural activation system in the processing of faces and facial affect. Moreover, in facial perception there was no association to estimated intelligence, suggesting that face recognition performance in women is unrelated to several basic cognitive processes. Gender-related differences may suggest a role for sex hormones. In females there may be variability for psychological functions related to differences in hormonal levels during different phases of the menstrual cycle. Data obtained in norm and in pathology support asymmetric face processing. Gorno-Tempini and others in 2001, suggested that the left inferior frontal cortex and the bilateral occipitotemporal junction respond equally to all face conditions. Some neuroscientists contend that both the left inferior frontal cortex (Brodman area 47) and the occipitotemporal junction are implicated in facial memory. The right inferior temporal/fusiform gyrus responds selectively to faces but not to non-faces. The right temporal pole is activated during the discrimination of familiar faces and scenes from unfamiliar ones. Right asymmetry in the mid temporal lobe for faces has also been shown using 133-Xenon measured cerebral blood flow (CBF). Other investigators have observed right lateralisation for facial recognition in previous electrophysiological and imaging studies.

The implication of the observation of asymmetry for facial perception would be that different hemispheric strategies would be implemented. The right hemisphere would be expected to employ a holistic strategy, and the left an analytic strategy. In 2007, Philip Njemanze using a novel functional transcranial Doppler (fTCD)] technique called functional transcranial Doppler spectroscopy (fTCDS) demonstrated that men were right lateralised for object and facial perception, while women were left lateralised for facial tasks but showed a right tendency or no lateralisation for object perception. Njemanze demonstrated using fTCDS, summation of responses related to facial stimulus complexity, which could be presumed as evidence for topological organisation of these cortical areas in men. It may suggest that the latter extends from the area implicated in object perception to a much greater area involved in facial perception. This agrees with the object form topology hypothesis proposed by Ishai and colleagues in 1999. However, the relatedness of object and facial perception was process based, and appears to be associated with their common holistic processing strategy in the right hemisphere. Moreover, when the same men were presented with facial paradigm requiring analytic processing, the left hemisphere was activated. This agrees with the suggestion made by Gauthier in 2000, that the extrastriate cortex contains areas that are best suited for different computations, and described as the process-map model. Therefore, the proposed models are not mutually exclusive, and this underscores the fact that facial processing does not impose any new constraints on the brain other than those used for other stimuli. It may be suggested that each stimulus was mapped by category into face or non-face, and by process into holistic or analytic. Therefore, a unified category-specific process-mapping system was implemented for either right or left cognitive styles. Njemanze in 2007, concluded that, for facial perception, men used a category-specific process-mapping system for right cognitive style, but women used same for the left.

Controversies

While a great deal of resources seem to be used by the mind and brain to understand the face, opinion is divided as to whether we genuinely develop specific skills for understanding faces, or whether face perception is just part of a general skill for making within-category discriminations, such as recognising and differentiating between similar animals or plants. Recognising a face involves a process of analogy.

Proponents of this view argue that the differences seen between faces and non-face objects in experimental studies are due to faces being particularly difficult to distinguish and observers having acquired expertise at making these discriminations. Although we often assume that faces are relatively unique, statistically they are quite similar, so a great deal of cognitive effort is needed to differentiate them. According to this view, faces are nothing more than a particularly difficult class of perceptual object which we have learned to distinguish at the expert level, much as we would learn to distinguish between other similar objects if much of our communication and survival depended on it.

Cognitive Neuroscientists Isabel Gauthier and Michael Tarr are two of the major proponents of the view that face recognition involves expert discrimination of similar objects (See the Perceptual Expertise Network). Other scientists, in particular Nancy Kanwisher and her colleagues, argue that face recognition involves processes that are face-specific and that are not recruited by expert discriminations in other object classes (See the domain specificity).

Studies by Gauthier have shown that an area of the brain known as the fusiform gyrus (sometimes called the 'fusiform face area' because it is active during face recognition) is also active when study participants are asked to discriminate between different types of birds and cars, and even when participants become expert at distinguishing computer generated nonsense shapes known as greebles. This suggests that the fusiform gyrus may have a general role in the recognition of similar visual objects. Yaoda Xu, then a post doctoral fellow with Nancy Kanwisher, replicated the car and bird expertise study using an improved fMRI design that was less susceptible to attentional accounts.

The activity found by Gauthier when participants viewed non-face objects was not as strong as when participants were viewing faces, however this could be because we have much more expertise for faces than for most other objects. Furthermore, not all of findings of this research have been successfully replicated, for example, other research groups using different study designs have found that the fusiform gyrus is specific to faces and other nearby regions deal with non-face objects.

However, these failures to replicate are difficult to interpret, because studies vary on too many aspects of the method. It has been argued that some studies test experts with objects that are slightly outside of their domain of expertise. More to the point, failures to replicate are null effects and can occur for many different reasons. In contrast, each replication adds a great deal of weight to a particular argument. With regard to "face specific" effects in neuroimaging, there are now multiple replications with Greebles, with birds and cars, and two unpublished studies with chess experts.

Although it is sometimes found that expertise recruits the FFA (e.g. as hypothesized by a proponent of this view in the preceding paragraph), a more common and less controversial finding is that expertise leads to focal category-selectivity in the fusiform gyrus - a pattern similar in terms of antecedent factors and neural specificity to that seen for faces. As such, it remains an open question as to whether face recognition and expert-level object recognition recruit similar neural mechanisms across different subregions of the fusiform or whether the two domains literally share the same neural substrates. Moreover, at least one study argues that the issue as to whether expertise-predicated category-selective areas overlap with the FFA is nonsensical in that multiple measurements of the FFA within an individual person often overlap no more with each other than do measurements of FFA and expertise-predicated regions. At the same time, such expertise effects have been characterized as extremely small, and numerous well done studies have failed to replicate them altogether. For example, four published fMRI studies have asked whether expertise has any specific connection to the FFA in particular, by testing for expertise effects in both the FFA and a nearby but not face-selective region called LOC (Rhodes et al., JOCN 2004; Op de Beeck et al., JN 2006; Moore et al., JN 2006; Yue et al VR 2006). In all four studies, expertise effects are significantly stronger in the LOC than in the FFA, and indeed expertise effects were only borderline significant in the FFA in two of the studies, while the effects were robust and significant in the LOC in all four studies. Thus, there is no evidence that increased fMRI activations due to perceptual expertise affect the FFA in particular, as opposed to nearby cortex.

Therefore, it is still not clear in exactly which situations the fusiform gyrus becomes active, although it is certain that face recognition relies heavily on this area and damage to it can lead to severe face recognition impairment.

Race

Differences in own- versus other-race face recognition and perceptual discrimination have been shown across a series of studies. This phenomenon is often referred to as the own-race effect, cross-race face effect, other-race effect, or own race bias.

A meta-analysis, Mullen found evidence that the other-race effect is larger among White subjects than among African American subjects, whereas Brigham and Williamson (1979, cited in Shepherd, 1981) obtained the opposite pattern. Shepherd also reviewed studies that found a main effect for race efface like that of the present study, with better performance on White faces (Malpass & Kravitz, 1969; Cross, Cross, & Daly, 1971; Shepherd, Deregowski, & Ellis, 1974; all cited in Shepherd, 1981), other studies in which no difference was found (Chance, Goldstein, & McBride, 1975; Feinman & Entwistle, 1976; cited in Shepherd, 1981), and yet other studies in which performance was better on African American faces (Brigham & Karkowitz, 1978; Brigham & Williamson, 1979; cited in Shepherd, 1981).Overall, Sheperd reports a reliable positive correlation between the size of the effect of target race (indexed by the difference in proportion correct on same- and other-race faces) and self-ratings of amount of interaction with members of the other race, r(30) = .57, p < .01. This correlation is at least partly an artifact of the fact that African American subjects, who performed equally well on faces of both races, almost always responded with the highest possible self-rating of amount of interaction with White people (M = 4.75), whereas their White counterparts both demonstrated an other-race effect and reported less other-race interaction (M= 2.13); the difference in ratings was reliable, £(30) = 7.86, p < .01

Further research points to the importance of other-race experience in own-versus other-race face processing (O'Toole et al., 1991; Slone et al., 2000; Walker & Tanaka, 2003). In a series of studies, Walker and colleagues showed the relationship between amount and type of other-race contact and the ability to perceptually differentiate other-race faces (Walker & Tanaka, 2003; Walker & Hewstone, 2006a,b; 2007). Participants with greater other-race experience were consistently more accurate at discriminating between other-race faces than were participants with less other-race exprience.

In addition to other-race contact, there is suggestion that the own-race effect is linked to increased ability to extract information about the spatial relationships between different features. Richard Ferraro writes that facial recognition is an example of a neuropsychological measure that can be used to assess cognitive abilities that are salient within African-American culture. Daniel T. Levin writes that the deficit occurs because people emphasize visual information specifying race at the expense of individuating information when recognizing faces of other races. Further research using perceptual tasks could shed light on the specific cognitive processes involved in the other-race effect. The question if the own-race effect can be overcome was already indirectly answered by Ekman & Friesen in 1976 and Ducci, Arcuri, Georgis & Sineshaw in 1982. They had observed that people from New Guinea and Ethopia who had had contact to white people before had a significantly better emotional recognition rate. The German university spin-off company Global Emotion uses this knowledge to overcome the Caucasian-Asian other-race effect with an online-training.

Studies on adults have also shown sex differences in face recognition. Men tend to recognise fewer faces of women than women do, whereas there are no sex differences with regard to male faces.

Artificial face perception

A great deal of effort has been put into developing software that can recognise human faces; see facial recognition system. Much of the work has been done by a branch of artificial intelligence known as computer vision which uses findings from the psychology of face perception to inform software design. Recent breakthroughs using noninvasive functional transcranial Doppler spectroscopy as demonstrated by Njemanze, 2007, to locate specific responses to facial stimuli have lead to improved systems for facial recognition. The new system uses input responses called cortical long-term potentiation (CLTP) derived from Fourier analysis of mean blood flow velocity to trigger target face search from a computerized face database system. Such a system provides for brain-machine interface for facial recognition, and the method has been referred to as cognitive biometrics.

References

External links

Science Aid: Face Recognition
FaceResearch – Scientific research and online studies on face perception
Face Blind Prosopagnosia Research Centers at Harvard and University College London
Face Recognition Tests - online tests for self-assessment of face recognition abilities.
Perceptual Expertise Network (PEN) Collaborative group of cognitive neuroscientists studying perceptual expertise, including face recognition.
Face Lab at the University of Western Australia
Perception Lab at the University of St Andrews, Scotland
The effect of facial expression and identity information on the processing of own and other race faces by Yoriko Hirose, PhD thesis from the University of Stirling
Global Emotion Online-Training to overcome Caucasian-Asian other-race effect