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Many brain imaging studies have looked at the cortical responses to object categories and faces. A popular way to manipulate face stimuli is by using a "face space," a high dimensional representation of individual face images, with the average face located at the origin. However, how the brain responds to faces that deviate substantially from average has not been much explored. Increasing the distance from the average (leading to increased caricaturing) could increase neural responses in face-selective regions, an idea supported by results from non-human primates. Here, we used a face space based on principal component analysis (PCA) to generate faces ranging from average to heavily caricatured. Using functional magnetic resonance imaging (fMRI), we first independently defined face-, object- and scene-selective areas with a localiser scan and then measured responses to parametrically caricatured faces. We also included conditions in which the images of faces were inverted. Interestingly in the right fusiform face area (FFA), we found that the patterns of fMRI response were more consistent as caricaturing increased. However, we found no consistent effect of either caricature level or facial inversion on the average fMRI response in the FFA or face-selective regions more broadly. In contrast, object-selective regions showed an increase in both the consistency of response pattern and the average fMRI response with increasing caricature level. This shows that caricatured faces recruit processing from regions typically defined as object-selective, possibly through enhancing low-level properties that are characteristic of objects. [ABSTRACT FROM AUTHOR]

Many brain imaging studies have looked at the cortical responses to object categories and faces. A popular way to manipulate face stimuli is by using a “face space,” a high dimensional representation of individual face images, with the average face located at the origin. However, how the brain responds to faces that deviate substantially from average has not been much explored. Increasing the distance from the average (leading to increased caricaturing) could increase neural responses in face-selective regions, an idea supported by results from non-human primates. Here, we used a face space based on principal component analysis (PCA) to generate faces ranging from average to heavily caricatured. Using functional magnetic resonance imaging (fMRI), we first independently defined face-, object- and scene-selective areas with a localiser scan and then measured responses to parametrically caricatured faces. We also included conditions in which the images of faces were inverted. Interestingly in the right fusiform face area (FFA), we found that the patterns of fMRI response were more consistent as caricaturing increased. However, we found no consistent effect of either caricature level or facial inversion on the average fMRI response in the FFA or face-selective regions more broadly. In contrast, object-selective regions showed an increase in both the consistency of response pattern and the average fMRI response with increasing caricature level. This shows that caricatured faces recruit processing from regions typically defined as object-selective, possibly through enhancing low-level properties that are characteristic of objects.

The relevance of the research is conditioned by the demand in operational method of experimental estimation of the stress-state of a coal seam ahead of the working, which is defined by key outburst danger factors: ground pressure, gas pressure and coal strength. The main aim is to substantiate the method of estimating the stress state of a coal seam selvage in the form of ratio of current and critical values of outburst danger indicator applying simultaneously performed spectral-acoustic method and instrumental method of outburst danger current (operational) prediction. Objects: underground mine coal seams prone to dynamic phenomena. Methods: the analysis of instrumental and geophysical methods of a face space stress state control; the estimation of a stress state based on geo-mechanics of solid bodies; instrumental method of outburst danger control – on the initial speed of gas emission and cutting fines output under interval drilling of boreholes; geometric acoustics; geophysical method of outburst danger control based on spectral analysis of the drilling rig working element noise; estimation of a stress state of a coal seam selvage on the result of simultaneous control fulfilled by instrumental and geophysical methods. Results. The paper introduces the characteristics of instrumental and geophysical methods of the ground pressure control and a stress state of underground working face space, in general. It is shown that for estimating the outburst danger degree neither ground pressure value nor gas pressure value bear any importance but the ratio of current and critical values of a stress state and it is, approximately, defined by three key factors: overlaying rock pressure, in-situ gas pressure and by the strength of the most broken coal layer. The technology of defining the stress state of a coal seam, which includes interval drilling of a borehole into the wall of the working into a certain depth with the interval length of 1 meter and measuring outburst danger indicator at each interval by instrumental and geophysical methods, is substantiated. Based on the measuring results one can determine the ratio of medium values of current and critical stresses at the distance between the miller of the drillrod at the end of the current drilling of a control borehole and a geophone, installed into the wall of the working.

Although faces "in the wild" constantly undergo complicated movements, humans adeptly perceive facial identity and expression. Previous studies, focusing mainly on identity, used photographic caricature to show that distinctive form increases perceived dissimilarity. We tested whether distinctive facial movements showed similar effects, and we focussed on both perception of expression and identity. We caricatured the movements of an animated computer head, using physical motion metrics extracted from videos. We verified that these "ground truth" metrics showed the expected effects: Caricature increased physical dissimilarity between faces differing in expression and those differing in identity. Like the ground truth dissimilarity, participants' dissimilarity perception was increased by caricature when faces differed in expression. We found these perceived dissimilarities to reflect the "representational geometry" of the ground truth. However, neither of these findings held for faces differing in identity. These findings replicated across two paradigms: pairwise ratings and multiarrangement. In a final study, motion caricature did not improve recognition memory for identity, whether manipulated at study or test. We report several forms of converging evidence for spatiotemporal caricature effects on dissimilarity perception of different expressions. However, more work needs to be done to discover what identity-specific movements can enhance face identification. [ABSTRACT FROM AUTHOR]

Face recognition is a computationally challenging classification task. Deep convolutional neural networks (DCNNs) are brain‐inspired algorithms that have recently reached human‐level performance in face and object recognition. However, it is not clear to what extent DCNNs generate a human‐like representation of face identity. We have recently revealed a subset of facial features that are used by humans for face recognition. This enables us now to ask whether DCNNs rely on the same facial information and whether this human‐like representation depends on a system that is optimized for face identification. In the current study, we examined the representation of DCNNs of faces that differ in features that are critical or non‐critical for human face recognition. Our findings show that DCNNs optimized for face identification are tuned to the same facial features used by humans for face recognition. Sensitivity to these features was highly correlated with performance of the DCNN on a benchmark face recognition task. Moreover, sensitivity to these features and a view‐invariant face representation emerged at higher layers of a DCNN optimized for face recognition but not for object recognition. This finding parallels the division to a face and an object system in high‐level visual cortex. Taken together, these findings validate human perceptual models of face recognition, enable us to use DCNNs to test predictions about human face and object recognition as well as contribute to the interpretability of DCNNs. [ABSTRACT FROM AUTHOR]

During the recognition of faces, the incoming perceptual information is matched against mental representations of familiar faces stored in memory. Face space models describe an abstract concept of face representations and their mental organization, in which facial representations are located on various characteristic dimensions, depending on their specific facial characteristics. However, these models are defined just as incompletely as the general understanding of face recognition. We took two phenomena from face processing to better understand face recognition, and so the nature of face space: face adaptation and face priming. The face literature has mainly focused on face adaptation, largely neglecting face priming when trying to integrate outcomes regarding face recognition into the face space framework. Consequently, the present paper aims to review both phenomena and their contributions to face recognition, representation, and face space.

Recent research has demonstrated that neural and behavioral data acquired in response to viewing face images can be used to reconstruct the images themselves. However, the theoretical implications, promises, and challenges of this direction of research remain unclear. We evaluate the potential of this research for elucidating the visual representations underlying face recognition. Specifically, we outline complementary and converging accounts of the visual content, the representational structure, and the neural dynamics of face processing. We illustrate how this research addresses fundamental questions in the study of normal and impaired face recognition, and how image reconstruction provides a powerful framework for uncovering face representations, for unifying multiple types of empirical data, and for facilitating both theoretical and methodological progress. The visual content of human face representations can be derived through image reconstruction at an unprecedented level of detail. The neural underpinnings of psychological face representations can be elucidated via image reconstruction from behavioral and multiple types of neural data. Facial image reconstruction capitalizes on the structure of face space and also serves to validate its representational properties. The recovery of face representations from both perception and memory can help to clarify the relationship between these two components of cognition. Image reconstruction can pinpoint the loss of information and/or misrepresentations in face perception across a broad population, including individuals with deficits in face processing. [ABSTRACT FROM AUTHOR]

During the recognition of faces, the incoming perceptual information is matched against mental representations of familiar faces stored in memory. Face space models describe an abstract concept of face representations and their mental organization, in which facial representations are located on various characteristic dimensions, depending on their specific facial characteristics. However, these models are defined just as incompletely as the general understanding of face recognition. We took two phenomena from face processing to better understand face recognition, and so the nature of face space: face adaptation and face priming. The face literature has mainly focused on face adaptation, largely neglecting face priming when trying to integrate outcomes regarding face recognition into the face space framework. Consequently, the present paper aims to review both phenomena and their contributions to face recognition, representation, and face space. [ABSTRACT FROM AUTHOR]

This research examined how 5-, B-, and 11-month-olds with female primary caregivers mentally represented faces using a familiarization procedure similar to real-world experience in which infants have greater exposure to female faces aged 21-39 years than other face types. We predicted infants would form weighted representations of faces (i.e., representations weighted toward the most frequently seen faces) and would more easily form weighted representations of female than male faces given their predominant experience with women (Experiments 1 and 2). We also tested adults using this familiarization procedure (Experiment 3) and predicted they would form averaged representations of faces based on data showing that preferences for averageness (the mathematical central tendency of a population) get stronger with development. Data from the three studies supported these hypotheses. Differences in how infants and adults mentally represent faces might be developmentally advantageous and such representations provide a mechanism to help explain the differential expertise in infants' and adults' face processing abilities. [ABSTRACT FROM AUTHOR]

In the present research, we took advantage of geometric morphometrics to propose a data-driven method for estimating the individual degree of facial typicality/distinctiveness for cross-cultural (and other cross-group) comparisons. Looking like a stranger in one’s home culture may be somewhat stressful. The same facial appearance, however, might become advantageous within an outgroup population. To address this fit between facial appearance and cultural setting, we propose a simple measure of distinctiveness/typicality based on position of an individual along the axis connecting the facial averages of two populations under comparison. The more distant a face is from its ingroup population mean toward the outgroup mean the more distinct it is (vis-à-vis the ingroup) and the more it resembles the outgroup standards. We compared this new measure with an alternative measure based on distance from outgroup mean. The new measure showed stronger association with rated facial distinctiveness than distance from outgroup mean. Subsequently, we manipulated facial stimuli to reflect different levels of ingroup-outgroup distinctiveness and tested them in one of the target cultures. Perceivers were able to successfully distinguish outgroup from ingroup faces in a two-alternative forced-choice task. There was also some evidence that this task was harder when the two faces were closer along the axis connecting the facial averages from the two cultures. Future directions and potential applications of our proposed approach are discussed.

In the present research, we took advantage of geometric morphometrics to propose a data-driven method for estimating the individual degree of facial typicality/distinctiveness for cross-cultural (and other cross-group) comparisons. Looking like a stranger in one's home culture may be somewhat stressful. The same facial appearance, however, might become advantageous within an outgroup population. To address this fit between facial appearance and cultural setting, we propose a simple measure of distinctiveness/typicality based on position of an individual along the axis connecting the facial averages of two populations under comparison. The more distant a face is from its ingroup population mean toward the outgroup mean the more distinct it is (vis-à-vis the ingroup) and the more it resembles the outgroup standards. We compared this new measure with an alternative measure based on distance from outgroup mean. The new measure showed stronger association with rated facial distinctiveness than distance from outgroup mean. Subsequently, we manipulated facial stimuli to reflect different levels of ingroup-outgroup distinctiveness and tested them in one of the target cultures. Perceivers were able to successfully distinguish outgroup from ingroup faces in a two-alternative forced-choice task. There was also some evidence that this task was harder when the two faces were closer along the axis connecting the facial averages from the two cultures. Future directions and potential applications of our proposed approach are discussed. [ABSTRACT FROM AUTHOR]

Highlights • First report of ERPs to faces and anti-faces of familiar and unfamiliar persons. • P200 decreases with distance-to-norm irrespective of face familiarity. • N250 and late negativity are much larger to familiar faces than their anti-faces. • Unfamiliar faces and their anti-faces show similar N250 and late negativity. • Face-sensitive ERPs dissociate different aspects of representational face space. Abstract The norm-based face space model (nMDFS) predicts that perceived typicality decreases with distance to the norm. Accordingly, an original face and its corresponding anti-face (deviating in exactly opposite direction from the norm) should inherit equivalent levels of typicality. Similarly, varying distance-to-norm (DTN, in absolute values) should have equivalent effects on typicality for both unfamiliar faces and their anti-faces. Here we reasoned that familiar faces would not follow this rule, due to the special nature of their mental representations. We investigated event-related brain potentials (ERPs) to familiar and unfamiliar faces and their anti-faces with different DTN (±0.33, ±0.66, and ±0.99). Across DTN, rated typicality was highest for original familiar faces, whereas all other face stimuli exhibited the expected gradual decrease of typicality with increasing DTN. ERPs showed pronounced DTN effects in the occipitotemporal P200 (190–260 ms), with progressively smaller amplitudes for faces with higher DTN, for all face types. By contrast, prominent effects of familiarity were found for the subsequent N250 (260–400 ms) and a late occipitotemporal negativity (LN, 400–800 ms). A large increase of occipitotemporal negativity was observed for original familiar faces versus their non-recognizable anti-faces. Analogous effects were small or absent for unfamiliar faces versus their anti-faces. These results confirm the N250 and LN as correlates of the processing of the identity of known faces, and show for the first time that the face-sensitive P200 is primarily modulated by DTN of a face in nMDFS. [ABSTRACT FROM AUTHOR]

Face recognition is a computationally challenging task that humans perform effortlessly. Nonetheless, this remarkable ability is better for familiar faces than unfamiliar faces. To account for humans' superior ability to recognize familiar faces, current theories suggest that different features are used for the representation of familiar and unfamiliar faces. In the current study, we applied a reverse engineering approach to reveal which facial features are critical for familiar face recognition. In contrast to current views, we discovered that the same subset of features that are used for matching unfamiliar faces, are also used for matching as well as recognition of familiar faces. We further show that these features are also used by a deep neural network face recognition algorithm. We therefore propose a new framework that assumes similar perceptual representation for all faces and integrates cognition and perception to account for humans' superior recognition of familiar faces. [ABSTRACT FROM AUTHOR]

This study considers the conception that drawing or copying a face that is vertically inverted will improve the accuracy of the drawing by preventing holistic interference. We used a novel parameterized face space both for generating face stimuli and for measuring the physical accuracy of drawings. One group of participants (theartists) were asked to draw 16 parameterized faces (eight upright and eight inverted). We computed two physical measures of accuracy by comparing the face-space representation of each drawing to the original face. A second and third group of participants (theraters) compared the similarity between each original face and each pair of drawings of that face (one upright and one inverted per artist). For the second group, all faces were presented upright; for the third group, all faces were presented inverted. Our results showed that upright drawings were more accurate than inverted drawings, both in terms of the physical face-space measure and in terms of the perceptual judgments for both orientations. Our data suggest that holistic processing may aid rather than hinder face drawing accuracy. [ABSTRACT FROM AUTHOR]