Recognition of unfamiliar face.
The ability of infants to recognise unfamiliar faces has also been investigated by several studies. Whereas in face preference studies, we typically present two faces side by side and measure looking time of an infant for each face, other methods have been used to measure recognition of a face using the novelty preference and habituation technique. In this procedure, the infant is habituated to a face followed by the presentation of two faces: the familiar face (seen in habituation) and a novel face. Young infants have a preference for novel stimuli, and it is assumed that if the infant can discriminate and recognise a familiar face, they should subsequently demonstrate greater interest (measured via looking time) in the novel stimulus. Hence, a novelty preference indicates recognition of the familiar face.
Using this technique, several researchers have examined whether infants are able to recognise a stranger’s face which does not hold significant social meaning, unlike the mother’s face. Pascalis and de Schonen (1994), using this procedure tested newborn’s recognition of female stranger’s faces. Recognition for the unfamiliar face was found immediately and after a 2-minute delay indicating that young infants can also rapidly learn and discriminate an unfamiliar face.
Other researchers have also investigated whether internal or external features of a face facilitate recognition. Turati, Cassia, Simion & Leo (2006), habituated newborns to a stranger’s face in one of three conditions (full face, internal feature or external feature condition) and then test recognition of either the internal or external feature of a face. Results of the study found that newborns can recognize a stranger’s face using external cues but can also succeed with inner features when faces shown in habituation and test are not visually distinct. While younger infants tend to focus on external regions of the face, older infants have been found to focus more on the internal regions of the face (Farroni et al., 2007; Haith et al., 1977; Maurer and Salapatek, 1976) as they grow older due to the importance of processing features of a face that brings various social meaning and communication. This shift of attention to internal regions of a face also assists in coding features of the face and increased the likelihood of better facial recognition in infants (Farroni et al., 2007). Long-term face recognition has been examined with older infants from 3 months of age and beyond. Studies (Fagan 1973, Pascalis et al., 1998, Turati et al., 2008) have shown that infants can learn and recognise a face from different points of view (i.e., habituated to a frontal face and then tested using a ¾ profile face).
Infants have also been found to be able to recognise (individuate) faces of different races and species that they have no prior experience with (Kelly et al., 2007; Pascalis, de Haan & Nelson, 2002).
Collectively, the above studies and many others (Pascalis & deSchonen, 1994; Turati et al., 2006, 2008) demonstrates that newborns are able to quickly learn and recognise a novel face from another face even when these faces are unfamiliar and hold no significant social meaning to them rapidly within the first few months of life.
While adults have been viewed as experts in processing faces, the face recognition of children are considered to be poorer due to specific deficits in face processing ability (Carey & Diamond, 1977) or due to general poorer memory capacity, attention and other general cognitive factors in children (Crookes & McKone, 2009). While we know that some face processing abilities are already present in newborns, there is a general debate about when face processing expertise develops and becomes adult-like in children. Carey & Diamond (1977, 1994) proposed (face-specific perceptual development theory) that face recognition ability in children is immature before 10 years of age and development of specific face perceptual abilities linked to expert face processing (see section 1.7 on featural vs configural processing) is only achieved in late childhood. These face processing abilities continue to develop in late childhood and adolescence before reaching full adult levels (Ericsson, Krampe, & Tesch-Römer, 1993; Mondloch, LeGrand & Maurer, 2002; Pearson & Lane, 1991). An alternative view, known as the general cognitive development theory, is that expert face processing mechanism is developed much earlier in childhood by 5 to 7-year-olds (Crookes & McKone, 2009; Want, Pascalis, Coleman and Blades, 2003) and the improvements of face recognition found in later childhood are due to improvements in general cognitive developments such as attentional, memory factors. Want et al. (2003) noted that children’s competence at face recognition increases with age and varies depending on how they are tested rather than a change in specific face-processing mechanisms in late childhood as proposed by Carey & Diamond (1977, 1994). Experiments using children-specific tasks can increase children’s performance level and even young children can show good performance using the appropriate methods of testing. For example, Bruce et al. (2000) using a forced-choice matching task found that preschool children of 4-to 5- years of age were able to achieve 80% accuracy performance. In another study using picture books, Brace et al. (2001) found that children as young as 2 – 4-year-olds can recognise faces with a 73% accuracy level, while older children 5–6-year-olds performed up to a 93% accuracy level given that the task is cognitively appropriate for children. In a study looking at face recognition of human faces relative to monkey and sheep faces, Pascalis, Demont, de Haan & Campbell (2001) found that 5-and 8-year-olds were able to discriminate human faces better than monkey and sheep faces and that 8-year-olds had better face recognition performance than 5-year-olds. Face recognition in children has been found in various studies to improve with age across children aged 5 to 10 years of age (see Want, et al., 2003 for a review) when simplified tasks appropriate for children’s cognitive capacity are used. According to Crookes & McKone, 2009, these face recognition improvements are due to the general improvements in children’s ability to attend and focus on the demands of the task. Hence, based on newer evidence, the face recognition system is present early in life and in childhood and the increased performances are due to improvement in general cognitive abilities rather than specific face processing abilities.
Recently, Weigelt et al., 2014 proposed a theory that the development of face perception and face memory are different, with face perception mechanism developing earlier than face memory. Face perception is defined as a face processing mechanism that individuates faces with minimal to no memory requirement such as those in holistic processing whereas face memory is defined as the ability to retain and remember faces in long term memory such as in tasks that identify whether a face has been previously seen (e.g., old-new paradigm).
Wiegelt et al. presented evidence (see Wiegelt et al., 2013) that the face expert processing mechanism may not be the same as the mechanism for face memory. Specifically, they noted that face perception reaches adult level early in life (i.e., 5 years of age) but memory for faces continues to improve until 10 years of age and that this developmental slope is steeper for faces than other class of stimuli indicating a domain-specific development.
While face expertise and memory continue to develop in childhood, face recognition is also influenced by several factors such as differential experience with own and other-race faces, male and female faces, and own and other age faces.
Race. Past studies have noted that we are better at recognising faces of our own race versus other races, a phenomenon known as the Other-race effect (ORE). This effect has been found to be present early in infancy and continues to adulthood. The development of this effect will be further discussed in Chapter 2.
Gender. Face recognition ability is also susceptible to the influences of male and female faces. 3-and 4-month-old infants who are primarily taken care by female caregivers recognize a familiar female face but not a familiar male face when presented with both female and male faces (Quinn et al., 2002). Quinn et al. (2002) also noted that the opposite effect has also been seen in a small number of infants who are primarily taken care by male caregivers. This differential experience with male and female faces diminishes as the infants are exposed to more different gender faces in the environment. This indicates that experience with male and female faces influences the level of human face representation in our memory leading to different recognition levels for different gender faces. Recognition of male and female faces in childhood and adolescence has been investigated. Results are inconsistent with some studies finding females having better recognition of female faces compare to male faces known as the own-gender advantage in face recognition. However, this own gender advantage in recognition was only found among females and not male children. (Cross et al., 1971; Feinman and Entwisle, 1976, Ellis et al., 1973, Ge et al. 2008, Rehman & Herlitz, 2006). Similarly, this effect has been found in some studies with adults, where women are reported to have better memory for female faces compared to men (see review by Herlitz & Loven, 2013). Some proposed explanations to this effect are 1) we have larger female than male faces experience during early years as most infants are taken care by female primary caregivers (Rennel & Davis, 2008) 2) infant girls attend and have more eye-to-eye contact than boys (Connellan et al, 2000).
Age. Own-age bias is a term that refers to better recognition memory of faces belonging to a person within the own age range compare to another age group (Rhodes & Anastasi, 2012; Wiese, Komes & Schweinberger, 2013). Children aged 5-to 8-years-olds when presented with photographs of children, younger adults, middle-aged adults and older adults were shown to have better recognition accuracy of children faces (children photographs) compare to other-age faces (Anastasi & Rhodes, 2005). Similarly, Crookes and McKone (2009) have also demonstrated similar findings among 5-to 6-year-olds and 10-to 11-years-olds, showing better recognition of own-age faces than adult faces in the study. In another study, Macchi Cassia et al. (2009) found that 3-year-old children who have younger siblings had better recognition of newborn faces than 3-year-old children without younger siblings indicating experience with a particular age range face have an impact on face recognition performance. In contrast, studies that have looked at individuals who have had extensive contact with another age group (Cassia, Kuefner, et al., 2009; Harrison & Hole, 2009; Kuefner et al., 2010) had a decrease own-age bias further supporting the role of experience in affecting memory for faces.
Understanding what disrupts face processing
In order to understand how humans, process a face, researchers have attempted to uncover what process disrupts these processes. Understanding what causes the system to fail can provide important clues on how face processing is optimized.
One important aspect of when face recognition is disrupted is when viewing an inverted (upside-down) face. Studies have found that accuracy and reaction time in recognising an inverted face is poorer but not for other non-face objects such as cars, furniture or houses (Yin 1969; Leder & Bruces 2000). This phenomenon where identifying an inverted face is more difficult than inverted objects is known as the face-inversion effect. The inversion effect states that faces are identified and distinguish more accurately and faster when presented in an upright orientation compare to an upside-down orientation (Yin, 1969). Yin (1969) found that adults generally had more difficulty viewing mono-oriented objects, objects usually seen in one orientation when it is inverted. When presenting both inverted mono-oriented objects (such as planes, cars and houses) and faces to adult participants, participants had more difficulty remembering inverted faces compared to inverted objects. These findings led the author to suggest that faces are special and processed differently compare to objects.
One explanation of the inversion effect that has been proposed is the configural information hypothesis (see next section for details). This hypothesis states that we process a face holistically (as a whole) using configural information while objects are processed featurally (in parts). When a face is inverted it disrupts configural processing, forcing the face to be processed featurally like other objects. This in turn causes a slower reaction time and less accuracy when viewing an inverted face.
Configural vs Featural Processing
Studies have suggested that unlike other objects, faces are a special category of stimuli with the unique position of face features (eyes, nose, mouth, etc) that are homogenous and have to be discriminated based on relational information such as distance between eyes or eyes and nose or nose and lips (Leder & Bruce, 2000). Configural processing, a term used to describe the ability to process this relational information, is hypothesized by researchers to happen as a result of experiences (Diamond and Carey, 1986; Gauthier and Tarr, 1997, Maurer, LeGrand & Mondloch, 2002). Mondloch, LeGrand & Maurer (2002) noted that expertise in face processing takes many years to develop and we do not just distinguish a face based on the shape of the features, a process known as featural processing, but also the relations among these features (configural processing). As humans have years of experience perceiving upright faces, face processing is disrupted when we view an inverted face. The inversion effect states that faces are identified and distinguish more accurately and faster when presented in an upright orientation compare to an upside-down orientation (Yin, 1969). Configural information required to recognise a face becomes disrupted when a face is inverted, resulting in the use of a less accurate featural processing strategy (Diamond and Carey, 1986). As features of a face are often represented in memory in an upright orientation, an inverted face must be uprighted mentally before it can be identified. This becomes more difficult when complex information such as relations between features and contours are an important distinguishing feature in faces as well. Hence, researchers have typically used the failure to recognise an inverted face as an indirect measure of configural processing. The face inversion effect has been demonstrated in adults using a variety of face stimuli such as schematic faces (Yin, 1969), famous faces (Yarney, 1971) and photographs of real faces (Carey and Diamond, 1977) using different types of testing paradigms (Yin, 1969; Valentine and Bruce, 1986; Freire et al., 2000).
In a series of experiments, Carey and colleagues (Carey & Diamond, 1977, 1994; Diamond & Carey, 1977; Carey, Diamond & Woods, 1980) proposed the encoding switch hypothesis that children encode faces using distinctive features such as eyes and nose (featural processing) while adults use configural processing (encode spatial relationship information between face features) when recognising a face. However, as children’s exposure to faces increases, their processing strategy is said to switch from featural to configural processing when recognising an individual. It is with this shift of processing strategy that their levels of face recognition performance improve. Carey and Diamond proposed this happens in older children at about 10 years of age. This assertion was initially based on evidence that young children’s recognition of faces is less affected by the inversion effect than adults. Support for this was shown in their study (Carey and Diamond, 1977) where the inversion effect disrupts 10 year–olds’ performance in faces more than houses but not for 6-and 8-year-old children in the study. Based on the assumption that inversion impairs configural processing, it was concluded that adult-like configural processing is only fully developed at around 10-years of age. However, some subsequent studies with infants and children have challenged this account (Brace et al., 2001; Want et al., 2003, Cohen & Cashon, 2001; Turati, Sangrigoli, Ruel & de Schonen, 2004).
Several preferences have also been found to be disrupted when the face stimuli are inverted in children younger than 10-years old. For example, Slater et al. (2000) found that newborn’s preference for attractive faces was eliminated when the face was presented inverted. Similarly, Quinn et al. (2002) found that 3-month-old infants’ preference for female faces was abolished when these faces were displayed in an inverted orientation. Findings from these two studies seem to suggest that configural processing may be already present in very young infants.
The inversion effect has also been found in infants as young as 4 months of age (Turati et al., 2004). Four months old infants were found to be able to recognise an upright face and an inverted face when the same face was used in familiarisation and test. However, when a face is learned at different poses, recognition of the inverted face is lost. In 2001, Cohen and Cashon demonstrated evidence that configurational processing is already present in 7-month-old infants when viewing an upright face and that featural processing is used in an inverted face. Cohen and Cashon (2001) habituated thirty-two 7-month-old infants to two female faces and then tested them on a familiar face, a switched face consisting of a combination of internal and external features from the two habituated female faces and a novel face. It was hypothesised that if infants only process independent features of a face during recognition, the switch face would be view as a familiar face since the features of the switch face have been seen during habituation by the infant. However, if infants use configural processing (i.e. process relational information among features), the switch face should look novel to the infant. A group of infants was shown upright faces and a second group of infants was shown the inverted faces. Results showed that infants looked longer at the switch face in the upright face condition indicating that infants are processing some level of configurational information when viewing upright face. On the contrary, in the inverted face condition, infants fail to look longer at the switch face indicating that perhaps a featural processing strategy was used when viewing an inverted face. Infants in this study were already demonstrating adult-like patterns of response at 7 months of age and were already sensitive to configural face information. Further evidence for configural processing in infants was found in Zauner and Schwarzer (2003) study, using schematical drawn face stimuli. In this study, 6-and 8-month-old infants were found to process relational information whereas a featural approach was found in 4 months old infants. Using the switch face approach, Schwarzer et al. (2007) found that there is a shift of featural to configural face processing in infants 4 to 10-months of age. In this study, the eyes and mouth of the habituated faces were switched to produce the switch faces. Results showed that 10-month-old infants processed eyes and mouth configurally, while 4-month-old infants processed eyes and mouth featurally. The 6-month-old infants processed the mouth holistically but the eyes featurally indicating a transitional stage of processing.
Results from the above studies indicate mixed results, implying that while configural processing is observed in infants around 6-to 7-month-olds, it is not adult-like in its pattern. Younger infants appear to use the featural approach when certain stimuli are employed (Zauner & Schwarner, 2003).
An alternative account to the featural-configural processing hypothesis is the view that both featural and configural information are processed simultaneously and equally important when processing a face. The term holistic processing has been used by researchers to describe the claim that the face is perceived as a whole and not based on separate features. The holistic processing view is based on the Gestalt principle and was first introduced by Francis Galton (Galton, 1883). The face holistic processing has been evidenced using two experimental paradigms: 1) The composite face paradigm (Young, Hellaway, & Hay, 1987) and 2) the whole-part paradigm (Tanaka & Farah, 1993).
In the composite face paradigm, a composite face stimulus is created by combining the top half of a face with the bottom half of another face. The composite face results in a novel face that neither resembles the original faces used. In this paradigm, participants learned a series of faces and are presented with the new composite faces either in aligned or misaligned positions (see figure 3). Participants are asked to judge if the top half of the face has been seen during the learning trials (familiar) or unfamiliar. Participants often have more difficulty recognising the top half of the face when it is aligned over the misaligned face, indicating that in the aligned condition, the faces are processed holistically and viewed as a new face. In the misaligned condition, the accuracy of recall is better as the two halves are processed independently.
Figure 3. Examples of Aligned and Misaligned composite faces; the top half is the same in both pictures. Reproduced from de Heering et al. (2007).
In the whole-part face paradigm, participants learned a series of faces and memory for one feature of the learned face (e.g., eyes, nose or mouth) is then tested in isolated part condition or embedded in a whole face condition. Participants were found to have better recognition performance when the feature is presented in the whole face condition over the isolation condition (Tanaka & Farah, 1993). This is then taken as evidenced that holistic processing is in place when viewing a face as memory for a feature is better identified when it is presented in a whole face context as memory of a feature is remembered in a whole face representation rather than in isolation.
Figure 4: Example of composite face images for isolated parts and whole-part test used in Tanaka et al. (1998).
The holistic face processing using either composite face and whole-part face paradigm have been seen in adults and children (Michel, Caldara & Rossion, 2006; Michel, Rossion, Chung, Caldara, 2006; Farah, Wilson, Drain & Tanaka, 1998, de Heering, Houthuys, and Rossion, 2007; Pellicano & Rhodes, 2003). Using the part-whole face paradigm, Farah and colleagues (Farah et al., 1998; Tanaka & Farah, 1993) demonstrate that adults were better at identifying a single facial feature presented in a whole face than when it is presented separately. When this was tested with scrambled or inverted faces and houses, this advantage disappeared. Similarly, Tanaka et al. (1998) found that children age 6 –to 10 years old were more accurate in recognizing facial features when presented in a whole face context than in isolation (see figure 4). This advantage again diminishes when the faces were inverted, supporting that holistic processing is essential in an upright face. Pellicano and Rhodes (2003) and de Heering et al. (2007) using the face composite paradigm later found evidence for holistic processing in children as young as 4 years of age. However, when children aged 2- 5-year-olds were asked to categorize faces, they used a single facial feature strategy instead of categorizing the faces holistically (Schwarzer,2002). In Schwarzer, 2002 study they found that a shift in holistic categorizing is only present between 6 to 10 years of age. Hence Schwarzer concluded that the ability to process face holistically, specifically recognising changes in a face, emerges early in childhood, the usage of holistic information in categorization of faces develops later in childhood.
Holistic processing has also been investigated in infants. Turati et al. (2010), using the composite face paradigm, tested newborns, 3-month-olds and adults using an eye-tracker and found the presence of holistic processing in infants as young as 3 months of age. Nakabayashi and Liu (2014) proposed that while holistic information has been observed to be present in infants, children and adults, it is the holistic interference effect that accounts for the difference between children’s and adults’ recognition performance. Specifically, they suggest that featural processing rather than holistic processing takes longer to develop. The interference effect can be observed in the whole-part paradigm when participants have difficulty with recognising a specific face part when this learned part is presented in a whole face context at the test. Nabayashi and Liu (2013) subsequently showed that 6-year-old children have more difficulty ignoring irrelevant information in a whole face during part recognition (interference effect) as compare to 9-10-year-olds or adults (see Nakabayashi and Liu; 2014 for review of the interference effect).
When we view a face, we process different information about the face such as the race of the person, age, gender, etc. This information can be classified into different facial categories such as age, gender, race and species. Forming categories or concepts is important for organising information in our memories and helps direct our responses to novel objects. In the 1970s, researchers accepted that categories are identifiable by extracting similar attributes within a category (attribute correlations) (Mervis & Rosch, 1981; Cohen & Younger, 1983).
Species. Since infants have been shown to be able to distinguish face and non-face stimuli, researchers were also interested in understanding whether infants are able to distinguish different species base on facial information/ perceptual cues. Quinn and Eimas (1996) found infants 3-months of age were able to categorise cat and dog faces based on internal facial features and external contours of the head (Quinn and Eimas, 1996). Similarly, Spencer et al. (1997) demonstrated that 4-month-olds infants were able to categorize cats and dogs based on information from the head and face region of the stimuli presented. Results from eye-tracking studies by Quinn et al., (2009) further suggest that the use of head information to categorise cats and dogs indicate a pre-existing bias of attending to face information during categorisation. Experience with pets has also been found to influence older infants’ categorization of animals such as cats and dogs (Kovack-Lesh et al., 2008).
Figure 5. Examples of an infant monkey and a caregiver with (A) and without (B) a facemask.
Reproduced from Sugita (2008).
Heron-Delaney, Wirth & Pascalis (2011) showed that infants as young as 3.5months had a preference for human representation over non-human species (i.e., gorilla or monkey) when the head and or body information were presented, indicating an early own species preference early in life. This early preference to own species is learned through experience. Sugita (2008) demonstrated in a study with rhesus infant monkeys that were reared with no exposure to any faces demonstrated an equal preference for monkey and human faces (see figure 5). Once the monkeys were exposed to either monkey faces or human faces, these monkeys discriminated against the exposed species face selectively indicating the influence of experience on species face preference and discrimination.
In summary, the ability to categorise species appears to be developed early in life and the ability to recognise own species is learned.
Race. Faces have different facial physiognomy and skin tone is evident from different races (e.g., Caucasian faces have lighter skin tones, higher and narrow noses, higher cheekbones; African faces have darker skin tones, wider noses). Infants’ ability to categorize based on race has been demonstrated in infants 9 months old (Anzures et al., 2010). Infants were familiarized with different faces from the same race group and then tested with female faces of another ethnic group (see Figure 6). 9-months-old infants successfully differentiate between both race categories and looked longer at the novel race face. Caucasian 6-months-old in this study was only able to show discrimination of different race categories after familiarisation with Asian faces but not Caucasian faces, indicating that the ability to categorise other-race faces is still developing at 6-months of age. Infant’s spontaneous preference for own-race faces (Bar-Haim et al., 2006; Kelly et al., 2005) may have also influenced the 6-month’s old infant’s racial categorisation performance. Infants have been found to prefer looking at own-race faces compared to other-race faces (Kelly et al., 2005). Infants’ preference for looking at one’s own race may have then hindered looking time at novel other-race faces after being familiarised with own-race faces.
Are infants able to form distinct different categories for other-race faces or do they group them as belonging to one other race category? In 2016, Quinn and colleagues investigated this issue on how infants categorise different classes of other-race faces by familiarizing 6- and 9-months old Caucasian infants with African or Asian other-race faces. They then tested whether infants had longer looking time at a novel African versus a novel Asian face. 6-month-olds infant demonstrated novel category preferences for other-race faces (e.g infants familiarised with African faces, would look longer at the novel Asian face at test trials). The findings suggest that 6-month-old infants distinctly categorised different classes of other-race faces. However, by 9-months-old, within the same study, older infants were unable to display a novel category preference. Further investigation revealed that 9 months old infants had developed a broad categorisation of other-race faces inclusive of both African and Asian faces in this study. The authors suggest that perceptual narrowing of different other race categorization takes place between 6 to 9-months of age; from being able to form distinct other race categorisation at 6-months-old to having a broad representation of other race categories at 9-months-old.
Table of contents :
Why face recognition?
Chapter 1: The development of face processing.
1.1 Face Preference
1.2 Face recognition
1.2.1 Mother face preference.
1.2.2. Attractive face preference.
1.2.3. Recognition of unfamiliar face.
1.3 Understanding what disrupts face processing
1.4 Face-Inversion effect
1.5 Configural vs Featural Processing
1.6 Holistic Processing
1.7 Facial categories
Chapter 2: The other-race effect (ORE)
2.1 Behavioural Testing paradigm used in investigating the Other Race Effect
2.2 Development of the ORE
2.2.1 Infant studies.
2.2.2 Children studies.
2.2.3 Adult studies.
2.3 Theoretical Framework
2.3.1 Perceptual Learning Models
2.3.2 Social Cognitive Models
2.3.3 Categorization-Individual Model
2.4 Plasticity of the ORE effect
Chapter 3: Introduction to the Other Race Categorisation Advantage (ORA)
3.1.1 Multidimensional Space Hypothesis
3.1.2 Contact Hypothesis
3.1.3 Feature Selection Hypothesis
3.2 Evidences of the presence of ORA
Chapter 4: Thesis Aims
Chapter 5: Experiment 1: Development of the other-race effect in Malaysian-Chinese infants
5.3.1 Habituation trials.
5.3.2 Test trials.
5.3.3 The other-race effect.
5.3.4 Social and caregiving environment
5.3.5 Social and caregiving environment and the other-race effect
Chapter 6: Experiment 2 & 3: The other-race effect in Malaysian adults and children in a multiracial context.
6.2 Experiment 2
6.3 Experiment 3
6.3.1 Experiment 3a
6.3.2 Experiment 3b
6.3.3 Experiment 3c
6.3.4 General discussion for Experiment 3a, 3b & 3c
Chapter 7: Experiment 4: The Other-Categorisation Advantage in Malaysian children and adults a multiracial context.
7.1.1 The other-race effect (own-race recognition advantage)
7.1.2 The other-race categorization advantage
7.1.3 Theoretical accounts.
7.1.4 The current study
7.2.2 Stimuli and materials
7.3.2 Response Time
Chapter 8: Experiment 5: The role of experience in kinship detection
8.1.1 Kinship Recognition
8.1.2 Inheritance understanding
8.2 Present study
8.2.1 Pilot study method
8.3.1. Main Study Method
Chapter 9: General Discussion and Conclusion
9.1 How does differential experience in a multiracial environment affect facial recognition (ORE) in infants, children and adults?
9.2 How does differential experience in a multiracial environment affects face categorization (ORA) in children and adults?
9.3 How does differential experience from a multiracial environment affects pre-schoolers ability to detect kinship relations?
Would an individual who have more experience with mixed race kinship be able to have an earlier understanding of biological inheritance?