No evidence for an other-race effect in dominance and trustworthy judgements from faces.

A variety of evidence shows that social categorization of people based on their race can lead to stereotypical judgements and prejudicial behaviour. Here, we explore the extent to which trait judgements of faces are influenced by race. To address this issue, we measured the reliability of first impressions for own-race and other-race faces in Asian and White participants. Participants viewed pairs of faces and were asked to indicate which of the two faces was more dominant or which of the two faces was more trustworthy. We measured the consistency (or reliability) of these judgements across participants for own-race and other-races faces. We found that judgements of dominance or trustworthiness showed similar levels of reliability for own-race and other-race faces. Moreover, an item analysis showed that the judgements on individual trials were very similar across participants from different races. Next, participants made overall ratings of dominance and trustworthiness from own-race and other-race faces. Again, we found that there was no evidence for an ORE. Together, these results provide a new approach to measuring trait judgements of faces and show that in these conditions there is no ORE for the perception of dominance and trustworthiness.

The importance of conceptual knowledge when becoming familiar with faces during naturalistic viewing.

Although the ability to recognise familiar faces is a critical part of everyday life, the process by which a face becomes familiar in the real world is not fully understood. Previous research has focussed on the importance of perceptual experience. However, in natural viewing, perceptual experience with faces is accompanied by increased knowledge about the person and the context in which they are encountered. Although conceptual information is known to be crucial for the formation of new episodic memories, it requires a period of consolidation. It is unclear, however, whether a similar process occurs when we learn new faces. Using a natural viewing paradigm, we investigated how the context in which events are presented influences our understanding of those events and whether, after a period of consolidation, this has a subsequent effect on face recognition. The context was manipulated by presenting events in 1) the original sequence, or 2) a scrambled sequence. Although this manipulation was predicted to have a significant effect on conceptual understanding of events, it had no effect on overall visual experience with the faces. Our prediction was that this contextual manipulation would affect face recognition after the information has been consolidated into memory. We found that understanding of the narrative was greater for participants who viewed the movie in the original sequence compared to those that viewed the movie in a scrambled order. To determine if the context in which the movie was viewed had an effect on face recognition, we compared recognition in the original and scrambled condition. We found an overall effect of conceptual knowledge on face recognition. That is, participants who viewed the original sequence had higher face recognition compared to participants who viewed the scrambled sequence. However, our planned comparisons did not reveal a greater effect of conceptual knowledge on face recognition after consolidation. In an exploratory analysis, we found that overlap in conceptual knowledge between participants was significantly correlated with the overlap in face recognition. We also found that this relationship was greater after a period of consolidation. Together, these findings provide new insights into the role of non-visual, conceptual knowledge for face recognition during natural viewing.

Mapping the functional and structural connectivity of the scene network.

The recognition and perception of places has been linked to a network of scene-selective regions in the human brain. While previous studies have focussed on functional connectivity between scene-selective regions themselves, less is known about their connectivity with other cortical and subcortical regions in the brain. Here, we determine the functional and structural connectivity profile of the scene network. We used fMRI to examine functional connectivity between scene regions and across the whole brain during rest and movie-watching. Connectivity within the scene network revealed a bias between posterior and anterior scene regions implicated in perceptual and mnemonic aspects of scene perception respectively. Differences between posterior and anterior scene regions were also evident in the connectivity with cortical and subcortical regions across the brain. For example, the Occipital Place Area (OPA) and posterior Parahippocampal Place Area (PPA) showed greater connectivity with visual and dorsal attention networks, while anterior PPA and Retrosplenial Complex showed preferential connectivity with default mode and frontoparietal control networks and the hippocampus. We further measured the structural connectivity of the scene network using diffusion tractography. This indicated both similarities and differences with the functional connectivity, highlighting biases between posterior and anterior regions, but also between ventral and dorsal scene regions. Finally, we quantified the structural connectivity between the scene network and major white matter tracts throughout the brain. These findings provide a map of the functional and structural connectivity of scene-selective regions to each other and the rest of the brain.

Distinct patterns of neural response to faces from different races in humans and deep networks.

Social categories such as the race or ethnicity of an individual are typically conveyed by the visual appearance of the face. The aim of this study was to explore how these differences in facial appearance are represented in human and artificial neural networks. First, we compared the similarity of faces from different races using a neural network trained to discriminate identity. We found that the differences between races were most evident in the fully connected layers of the network. Although these layers were also able to predict behavioural judgements of face identity from human participants, performance was biased toward White faces. Next, we measured the neural response in face-selective regions of the human brain to faces from different races in Asian and White participants. We found distinct patterns of response to faces from different races in face-selective regions. We also found that the spatial pattern of response was more consistent across participants for own-race compared to other-race faces. Together, these findings show that faces from different races elicit different patterns of response in human and artificial neural networks. These differences may underlie the ability to make categorical judgements and explain the behavioural advantage for the recognition of own-race faces.

A narrow band of image dimensions is critical for face recognition.

A key challenge in human and computer face recognition is to differentiate information that is diagnostic for identity from other sources of image variation. Here, we used a combined computational and behavioural approach to reveal critical image dimensions for face recognition. Behavioural data were collected using a sorting and matching task with unfamiliar faces and a recognition task with familiar faces. Principal components analysis was used to reveal the dimensions across which the shape and texture of faces in these tasks varied. We then asked which image dimensions were able to predict behavioural performance across these tasks. We found that the ability to predict behavioural responses in the unfamiliar face tasks increased when the early PCA dimensions (i.e. those accounting for most variance) of shape and texture were removed from the analysis. Image similarity also predicted the output of a computer model of face recognition, but again only when the early image dimensions were removed from the analysis. Finally, we found that recognition of familiar faces increased when the early image dimensions were removed, decreased when intermediate dimensions were removed, but then returned to baseline recognition when only later dimensions were removed. Together, these findings suggest that early image dimensions reflect ambient changes, such as changes in viewpoint or lighting, that do not contribute to face recognition. However, there is a narrow band of image dimensions for shape and texture that are critical for the recognition of identity in humans and computer models of face recognition.

Connectopic mapping techniques do not reflect functional gradients in the brain.

Functional gradients, in which response properties change gradually across a brain region, have been proposed as a key organising principle of the brain. Recent studies using both resting-state and natural viewing paradigms have indicated that these gradients may be reconstructed from functional connectivity patterns via "connectopic mapping" analyses. However, local connectivity patterns may be confounded by spatial autocorrelations artificially introduced during data analysis, for instance by spatial smoothing or interpolation between coordinate spaces. Here, we investigate whether such confounds can produce illusory connectopic gradients. We generated datasets comprising random white noise in subjects' functional volume spaces, then optionally applied spatial smoothing and/or interpolated the data to a different volume or surface space. Both smoothing and interpolation induced spatial autocorrelations sufficient for connectopic mapping to produce both volume- and surface-based local gradients in numerous brain regions. Furthermore, these gradients appeared highly similar to those obtained from real natural viewing data, although gradients generated from real and random data were statistically different in certain scenarios. We also reconstructed global gradients across the whole-brain - while these appeared less susceptible to artificial spatial autocorrelations, the ability to reproduce previously reported gradients was closely linked to specific features of the analysis pipeline. These results indicate that previously reported gradients identified by connectopic mapping techniques may be confounded by artificial spatial autocorrelations introduced during the analysis, and in some cases may reproduce poorly across different analysis pipelines. These findings imply that connectopic gradients need to be interpreted with caution.

Recognition of animal faces is impaired in developmental prosopagnosia.

An on-going debate in psychology and neuroscience concerns the way faces and objects are represented. Domain-specific theories suggest that faces are processed via a specialised mechanism, separate from objects. Developmental prosopagnosia (DP) is a neurodevelopmental disorder in which there is a deficit in the ability to recognize conspecific (human) faces. It is unclear, however, whether prosopagnosia also affects recognition of heterospecific (animal) faces. To address this question, we compared recognition performance with human and animal faces in neurotypical controls and participants with DP. We found that DPs showed deficits in the recognition of both human and animal faces compared to neurotypical controls. In contrast to, we found no group-level deficit in the recognition of animate or inanimate non-face objects in DPs. Using an individual-level approach, we demonstrate that in 60% of cases in which face recognition is impaired, there is a concurrent deficit with animal faces. Together, these results show that DPs have a general deficit in the recognition of faces that encompass a range of configural and morphological structures.

An evaluation of how connectopic mapping reveals visual field maps in V1.

Functional gradients, in which response properties change gradually across the cortical surface, have been proposed as a key organising principle of the brain. However, the presence of these gradients remains undetermined in many brain regions. Resting-state neuroimaging studies have suggested these gradients can be reconstructed from patterns of functional connectivity. Here we investigate the accuracy of these reconstructions and establish whether it is connectivity or the functional properties within a region that determine these "connectopic maps". Different manifold learning techniques were used to recover visual field maps while participants were at rest or engaged in natural viewing. We benchmarked these reconstructions against maps measured by traditional visual field mapping. We report an initial exploratory experiment of a publicly available naturalistic imaging dataset, followed by a preregistered replication using larger resting-state and naturalistic imaging datasets from the Human Connectome Project. Connectopic mapping accurately predicted visual field maps in primary visual cortex, with better predictions for eccentricity than polar angle maps. Non-linear manifold learning methods outperformed simpler linear embeddings. We also found more accurate predictions during natural viewing compared to resting-state. Varying the source of the connectivity estimates had minimal impact on the connectopic maps, suggesting the key factor is the functional topography within a brain region. The application of these standardised methods for connectopic mapping will allow the discovery of functional gradients across the brain. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 19 April 2022. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.19771717 .

Covariation in the recognition of own-race and other-race faces argues against the role of group bias in the other race effect.

A dominant theory of the other race effect (ORE) is that group-bias causes us to process own-race and other-race faces using different cognitive processes. To test this theory, we measured individual differences across two face recognition tasks. Our predictions were that the magnitude and pattern of performance on own-race faces would not predict performance on other-race faces and that participants would take more time with own-race faces. In a face matching task, we found that participants were more accurate with own-race faces compared to other-race faces. However, performance on own-race faces was highly correlated with performance on other-race faces. In a face sorting task, participants made fewer piles and fewer errors (i.e. higher accuracy) with own-race faces compared to other-race faces. However, we again found that performance on own-race faces was highly correlated with performance on other-race faces. The covariation in performance between own-race and other-race faces suggests that they engage similar perceptual processes. Finally, we found that participants did not spend more time on tasks involving own-race faces suggesting that different levels of motivation do not explain the ORE. Together, these findings argue against the idea that group bias leads to different perceptual processing of own-race and other-race faces.

The emergence of view-symmetric neural responses to familiar and unfamiliar faces.

Successful recognition of familiar faces is thought to depend on the ability to integrate view-dependent representations of a face into a view-invariant representation. It has been proposed that a key intermediate step in achieving view invariance is the representation of symmetrical views. However, key unresolved questions remain, such as whether these representations are specific for naturally occurring changes in viewpoint and whether view-symmetric representations exist for familiar faces. To address these issues, we compared behavioural and neural responses to natural (canonical) and unnatural (noncanonical) rotations of the face. Similarity judgements revealed that symmetrical viewpoints were perceived to be more similar than non-symmetrical viewpoints for both canonical and non-canonical rotations. Next, we measured patterns of neural response from early to higher level regions of visual cortex. Early visual areas showed a view-dependent representation for natural or canonical rotations of the face, such that the similarity between patterns of response were related to the difference in rotation. View symmetric patterns of neural response to canonically rotated faces emerged in higher visual areas, particularly in face-selective regions. The emergence of a view-symmetric representation from a view-dependent representation for canonical rotations of the face was also evident for familiar faces, suggesting that view-symmetry is an important intermediate step in generating view-invariant representations. Finally, we measured neural responses to unnatural or non-canonical rotations of the face. View-symmetric patterns of response were also found in face-selective regions. However, in contrast to natural or canonical rotations of the face, these view-symmetric responses did not arise from an initial view-dependent representation in early visual areas. This suggests differences in the way that view-symmetrical representations emerge with canonical or non-canonical rotations. The similarity in the neural response to canonical views of familiar and unfamiliar faces in the core face network suggests that the neural correlates of familiarity emerge at later stages of processing.

The representation of shape and texture in category-selective regions of ventral-temporal cortex.

Neuroimaging studies using univariate and multivariate approaches have shown that the fusiform face area (FFA) and parahippocampal place area (PPA) respond selectively to images of faces and places. The aim of this study was to determine the extent to which this selectivity to faces or places is based on the shape or texture properties of the images. Faces and houses were filtered to manipulate their texture properties, while preserving the shape properties (spatial envelope) of the images. In Experiment 1, multivariate pattern analysis (MVPA) showed that patterns of fMRI response to faces and houses in FFA and PPA were predicted by the shape properties, but not by the texture properties of the image. In Experiment 2, a univariate analysis (fMR-adaptation) showed that responses in the FFA and PPA were sensitive to changes in both the shape and texture properties of the image. These findings can be explained by the spatial scale of the representation of images in the FFA and PPA. At a coarser scale (revealed by MVPA), the neural selectivity to faces and houses is sensitive to variation in the shape properties of the image. However, at a finer scale (revealed by fMR-adaptation), the neural selectivity is sensitive to the texture properties of the image. By combining these neuroimaging paradigms, our results provide insights into the spatial scale of the neural representation of faces and places in the ventral-temporal cortex.

Recognition of pareidolic objects in developmental prosopagnosic and neurotypical individuals.

Developmental prosopagnosia (DP) is a neurodevelopmental disorder associated with difficulties in the perception and recognition of faces. However, the extent to which DP affects non-face object is an ongoing debate. In this study, we asked whether pareidolic objects (which give rise to the perception of a face) are also affected in DP. First, we compared performance in DPs (n = 30) and controls (n = 27) on a recognition task with faces, pareidolic objects and non-pareidolic objects (bottles). The pareidolic objects had either similar or dissimilar image statistics to faces. Consistent with our understanding of DP, we found that the pattern of recognition across items between DPs and controls was lowest for faces. Interestingly, there was also a low correlation between DPs and controls for pareidolic-similar objects that was similar to faces. In contrast, there were higher correlations between DPs and controls for pareidolic-dissimilar objects and bottles, which were both significantly different to faces. These findings suggest that the deficit in DP involves processing image properties that are common to faces. Next, using an individual differences approach across a large group of neurotypical adults (n = 94), we found that face recognition covaried with the recognition of pareidolic-similar objects, but not with pareidolic-dissimilar objects or non-pareidolic objects. Together, these findings support the idea that a representation based on image properties plays an important role in the perception and recognition of objects and faces and that the deficit in the perception of some object categories in DP could be explained by their similarity to the image properties found in faces.

The roles of shape and texture in the recognition of familiar faces.

The surface texture of the face is proposed to be the dominant cue in face recognition. In this study, we investigated the role of shape information in face recognition. We compared the roles of shape and surface texture in the recognition of face identity using familiar and unfamiliar hybrid faces in which the average shape from one facial identity was combined with the average texture of a different identity. In the first experiment (n = 53), participants had to match the name of a familiar person to one of eight hybrid face images. In texture trials, all images had the correct shape, but only one image had the correct texture. In shape trials, all images had the correct texture, but only one image had the correct shape. Importantly, neither task could be performed by perceptual matching. Although performance was lower for the shape trials (81%) compared to texture trials (99%), both were significantly above chance (12.5%). In the second experiment (n = 110), participants had to name hybrid faces. There were two potentially correct answers for each face image: one based on the texture and one based on the shape. Participants reported the correct name based on the texture on 61% of trials and the correct name based on the shape on 12% of trials. In the third experiment (n = 19), fMR-adaptation was used to measure the neural sensitivity to changes in the shape or texture. The core face-selective regions showed a similar sensitivity to shape and texture. These findings confirm that texture is the dominant cue for face recognition, but also show that shape plays an important role in the recognition and neural response to familiar faces.

Power contours: Optimising sample size and precision in experimental psychology and human neuroscience.

When designing experimental studies with human participants, experimenters must decide how many trials each participant will complete, as well as how many participants to test. Most discussion of statistical power (the ability of a study design to detect an effect) has focused on sample size, and assumed sufficient trials. Here we explore the influence of both factors on statistical power, represented as a 2-dimensional plot on which iso-power contours can be visualized. We demonstrate the conditions under which the number of trials is particularly important, that is, when the within-participant variance is large relative to the between-participants variance. We then derive power contour plots using existing data sets for 8 experimental paradigms and methodologies (including reaction times, sensory thresholds, fMRI, MEG, and EEG), and provide example code to calculate estimates of the within- and between-participants variance for each method. In all cases, the within-participant variance was larger than the between-participants variance, meaning that the number of trials has a meaningful influence on statistical power in commonly used paradigms. An online tool is provided (https://shiny.york.ac.uk/powercontours/) for generating power contours, from which the optimal combination of trials and participants can be calculated when designing future studies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A data-driven approach to stimulus selection reveals an image-based representation of objects in high-level visual areas.

The ventral visual pathway is directly involved in the perception and recognition of objects. However, the extent to which the neural representation of objects in this region reflects low-level or high-level properties remains unresolved. A problem in resolving this issue is that only a small proportion of the objects experienced during natural viewing can be shown during a typical experiment. This can lead to an uneven sampling of objects that biases our understanding of how they are represented. To address this issue, we developed a data-driven approach to stimulus selection that involved describing a large number objects in terms of their image properties. In the first experiment, clusters of objects were evenly selected from this multi-dimensional image space. Although the clusters did not have any consistent semantic features, each elicited a distinct pattern of neural response. In the second experiment, we asked whether high-level, category-selective patterns of response could be elicited by objects from other categories, but with similar image properties. Object clusters were selected based on the similarity of their image properties to objects from five different categories (bottle, chair, face, house, and shoe). The pattern of response to each metameric object cluster was similar to the pattern elicited by objects from the corresponding category. For example, the pattern for bottles was similar to the pattern for objects with similar image properties to bottles. In both experiments, the patterns of response were consistent across participants providing evidence for common organising principles. This study provides a more ecological approach to understanding the perceptual representations of objects and reveals the importance of image properties.

Symmetrical Viewpoint Representations in Face-Selective Regions Convey an Advantage in the Perception and Recognition of Faces.

Learning new identities is crucial for effective social interaction. A critical aspect of this process is the integration of different images from the same face into a view-invariant representation that can be used for recognition. The representation of symmetrical viewpoints has been proposed to be a key computational step in achieving view-invariance. The aim of this study was to determine whether the representation of symmetrical viewpoints in face-selective regions is directly linked to the perception and recognition of face identity. In Experiment 1, we measured fMRI responses while male and female human participants viewed images of real faces from different viewpoints (-90, -45, 0, 45, and 90° from full-face view). Within the face regions, patterns of neural response to symmetrical views (-45 and 45° or -90 and 90°) were more similar than responses to nonsymmetrical views in the fusiform face area and superior temporal sulcus, but not in the occipital face area. In Experiment 2, participants made perceptual similarity judgements to pairs of face images. Images with symmetrical viewpoints were reported as being more similar than nonsymmetric views. In Experiment 3, we asked whether symmetrical views also convey an advantage when learning new faces. We found that recognition was best when participants were tested with novel face images that were symmetrical to the learning viewpoint. Critically, the pattern of perceptual similarity and recognition across different viewpoints predicted the pattern of neural response in face-selective regions. Together, our results provide support for the functional value of symmetry as an intermediate step in generating view-invariant representations.SIGNIFICANCE STATEMENT The recognition of identity from faces is crucial for successful social interactions. A critical step in this process is the integration of different views into a unified, view-invariant representation. The representation of symmetrical views (e.g., left profile and right profile) has been proposed as an important intermediate step in computing view-invariant representations. We found view symmetric representations were specific to some face-selective regions, but not others. We also show that these neural representations influence the perception of faces. Symmetric views were perceived to be more similar and were recognized more accurately than nonsymmetric views. Moreover, the perception and recognition of faces at different viewpoints predicted patterns of response in those face regions with view symmetric representations.

Neural Correlates of Group Bias During Natural Viewing.

Individuals from different social groups interpret the world in different ways. This study explores the neural basis of these group differences using a paradigm that simulates natural viewing conditions. Our aim was to determine if group differences could be found in sensory regions involved in the perception of the world or were evident in higher-level regions that are important for the interpretation of sensory information. We measured brain responses from 2 groups of football supporters, while they watched a video of matches between their teams. The time-course of response was then compared between individuals supporting the same (within-group) or the different (between-group) team. We found high intersubject correlations in low-level and high-level regions of the visual brain. However, these regions of the brain did not show any group differences. Regions that showed higher correlations for individuals from the same group were found in a network of frontal and subcortical brain regions. The interplay between these regions suggests a range of cognitive processes from motor control to social cognition and reward are important in the establishment of social groups. These results suggest that group differences are primarily reflected in regions involved in the evaluation and interpretation of the sensory input.

Reduced connectivity between mentalizing and mirror systems in autism spectrum condition.

The mentalizing system and mirror system are thought to play important roles in inferring the internal mental states of others - a process known as mentalizing. Autism spectrum condition (ASC) is associated with difficulties in mentalizing. The aim of this study was to determine whether the behavioural difficulties in mentalizing associated with ASC can be explained by changes in functional connectivity between the mentalizing and mirror system. We recruited 40 adult participants (20 with ASC and 20 typically-developing). Brain activity was monitored using functional magnetic resonance imaging while participants watched videos in which actors performed hand actions. The videos were shown in separate mentalizing and non-mentalizing blocks. During mentalizing blocks, participants were asked to indicate whether hand actions were clumsy or spiteful (i.e. to judge the intent of the action). During non-mentalizing blocks, participants indicated whether the actions were successful or unsuccessful (i.e. to judge the outcome of the action). Higher activity during the mentalizing blocks compared to non-mentalizing blocks was found in regions associated with the mentalizing system: the dorsal medial prefrontal cortex (dmPFC) and the temporo-parietal junction (TPJ), as well as in regions typically associated with the mirror system: the inferior frontal gyrus (IFG) and the inferior parietal lobe (IPL). Next, functional connectivity between regions was evaluated as a function of task. During mentalizing blocks, there was increased functional connectivity between the dmPFC and the mirror system in typically developing participants. In contrast, there was no increase in functional connectivity between these regions in ASC participants. Connectivity between the dmPFC and IFG was negatively correlated with autistic traits. The reduced connectivity in ASC participants was consistent with behavioural performance on the mentalizing task, which was also negatively correlated with the level of autistic traits. Together, these data emphasise the importance of functional connectivity between the mentalizing and mirror systems when inferring social intentions and show that reduced connectivity between these systems may explain some of the behavioural difficulties experienced by adults with ASC.

Selectivity for mid-level properties of faces and places in the fusiform face area and parahippocampal place area.

Regions in the ventral visual pathway, such as the fusiform face area (FFA) and parahippocampal place area (PPA) are selective for images from specific object categories. Yet images from different object categories differ in their image properties. To investigate how these image properties are represented in the FFA and PPA, we compared neural responses to locally-SCRAMBLED images (in which mid-level, spatial properties are preserved) and globally-SCRAMBLED images (in which mid-level, spatial properties are not preserved). There was a greater response in the FFA and PPA to images from the preferred CATEGORY relative to their non-preferred category for the scrambled conditions. However, there was a greater selectivity for locally-scrambled compared to globally-scrambled images. Next, we compared the magnitude of fMR-adaptation to intact and scrambled images. fMR-adaptation was evident to locally-scrambled images from the preferred category. However, there was no adaptation to globally-scrambled images from the preferred category. These results show that the selectivity to faces and places in the FFA and PPA is dependent on mid-level properties of the image that are preserved by local-scrambling.

Patterns of neural response in face regions are predicted by low-level image properties.

Models of face processing suggest that the neural response in different face regions is selective for higher-level attributes of the face, such as identity and expression. However, it remains unclear to what extent the response in these regions can also be explained by more basic organizing principles. Here, we used functional magnetic resonance imaging multivariate pattern analysis (fMRI-MVPA) to ask whether spatial patterns of response in the core face regions (occipital face area - OFA, fusiform face area - FFA, superior temporal sulcus - STS) can be predicted across different participants by lower level properties of the stimulus. First, we compared the neural response to face identity and viewpoint, by showing images of different identities from different viewpoints. The patterns of neural response in the core face regions were predicted by the viewpoint, but not the identity of the face. Next, we compared the neural response to viewpoint and expression, by showing images with different expressions from different viewpoints. Again, viewpoint, but not expression, predicted patterns of response in face regions. Finally, we show that the effect of viewpoint in both experiments could be explained by changes in low-level image properties. Our results suggest that a key determinant of the neural representation in these core face regions involves lower-level image properties rather than an explicit representation of higher-level attributes in the face. The advantage of a relatively image-based representation is that it can be used flexibly in the perception of faces.