Vaidehi Natu

The neural processing of familiar and unfamiliar faces: A review and synopsis

Familiar faces are represented with rich visual, semantic, and emotional codes that support nearly effortless perception and recognition of these faces. Unfamiliar faces pose a greater challenge to human perception and memory systems. The established behavioural disparities for familiar and unfamiliar faces undoubtedly stem from differences in the quality and nature of their underlying neural representations. In this review, our goal is to characterize what is known about the neural pathways that respond to familiar and unfamiliar faces using data from functional neuroimaging studies. We divide our presentation by type of familiarity (famous, personal, and visual familiarity) to consider the distinct neural underpinnings of each. We conclude with a description of a recent model of person information proposed by Gobbini and Haxby (2007) and a list of open questions and promising directions for future research.

Dissociable neural patterns of facial identity across changes in viewpoint

We examined the neural response patterns for facial identity independent of viewpoint and for viewpoint independent of identity. Neural activation patterns for identity and viewpoint were collected in an fMRI experiment. Faces appeared in identity-constant blocks, with variable viewpoint, and in viewpoint-constant blocks, with variable identity. Pattern-based classifiers were used to discriminate neural response patterns for all possible pairs of identities and viewpoints. To increase the likelihood of detecting distinct neural activation patterns for identity, we tested maximally dissimilar “face”–“antiface” pairs and normal face pairs. Neural response patterns for four of six identity pairs, including the “face”–“antiface” pairs, were discriminated at levels above chance. A behavioral experiment showed accord between perceptual and neural discrimination, indicating that the classifier tapped a high-level visual identity code. Neural activity patterns across a broad span of ventral temporal (VT) cortex, including fusiform gyrus and lateral occipital areas (LOC), were required for identity discrimination. For viewpoint, five of six viewpoint pairs were discriminated neurally. Viewpoint discrimination was most accurate with a broad span of VT cortex, but the neural and perceptual discrimination patterns differed. Less accurate discrimination of viewpoint, more consistent with human perception, was found in right posterior superior temporal sulcus, suggesting redundant viewpoint codes optimized for different functions. This study provides the first evidence that it is possible to dissociate neural activation patterns for identity and viewpoint independently.

Unaware Person Recognition From the Body When Face Identification Fails

How does one recognize a person when face identification fails? Here, we show that people rely on the body but are unaware of doing so. State-of-the-art face-recognition algorithms were used to select images of people with almost no useful identity information in the face. Recognition of the face alone in these cases was near chance level, but recognition of the person was accurate. Accuracy in identifying the person without the face was identical to that in identifying the whole person. Paradoxically, people reported relying heavily on facial features over noninternal face and body features in making their identity decisions. Eye movements indicated otherwise, with gaze duration and fixations shifting adaptively toward the body and away from the face when the body was a better indicator of identity than the face. This shift occurred with no cost to accuracy or response time. Human identity processing may be partially inaccessible to conscious awareness.

Microstructural proliferation in human cortex is coupled with the development of face processing

Brain structure and function mature together Our ability to recognize faces improves from infancy to adulthood. This improvement depends on specific face-selective regions in the visual system. Gomez et al. tested face memory and place recognition in children and adults while scanning relevant brain regions. Anatomical changes co-occurred with functional changes in the brain. Some regions in the high-level visual cortex showed profound developmental maturation, whereas others were stable. Thus, improvements in face recognition involve an interplay between structural and functional changes in the brain. Science, this issue p. 68 Developmental improvements in face recognition occur together with tissue proliferation in face-selective brain regions. How does cortical tissue change as brain function and behavior improve from childhood to adulthood? By combining quantitative and functional magnetic resonance imaging in children and adults, we find differential development of high-level visual areas that are involved in face and place recognition. Development of face-selective regions, but not place-selective regions, is dominated by microstructural proliferation. This tissue development is correlated with specific increases in functional selectivity to faces, as well as improvements in face recognition, and ultimately leads to differentiated tissue properties between face- and place-selective regions in adulthood, which we validate with postmortem cytoarchitectonic measurements. These data suggest a new model by which emergent brain function and behavior result from cortical tissue proliferation rather than from pruning exclusively.

Computational perspectives on the other-race effect

Psychological studies have long shown that human memory is superior for faces of our own-race than for faces of other-races. In this paper, we review computational studies of own- versus other-race face processing. Computational models examine the visual challenges of representing the uniqueness of individual faces that vary both within and across demographic categories. These models isolate the visual components of the other-race effect and provide an objective control for socioaffective responses to other-race faces. This control allows researchers to compare and test the role of experience/contact in the other-race effect, using various operational definitions of this theoretical construct. The models show that to produce an other-race effect computationally, biased experience or learning must intervene during the process of feature selection. This implicates the critical importance of “developmental” learning in the other-race effect.

The Effect of Image Quality and Forensic Expertise in Facial Image Comparisons

Images of perpetrators in surveillance video footage are often used as evidence in court. In this study, identification accuracy was compared for forensic experts and untrained persons in facial image comparisons as well as the impact of image quality. Participants viewed thirty image pairs and were asked to rate the level of support garnered from their observations for concluding whether or not the two images showed the same person. Forensic experts reached their conclusions with significantly fewer errors than did untrained participants. They were also better than novices at determining when two high‐quality images depicted the same person. Notably, lower image quality led to more careful conclusions by experts, but not for untrained participants. In summary, the untrained participants had more false negatives and false positives than experts, which in the latter case could lead to a higher risk of an innocent person being convicted for an untrained witness.

The neural representation of faces and bodies in motion and at rest.

The neural organization of person processing relies on brain regions functionally selective for faces or bodies, with a subset of these regions preferring moving stimuli. Although the response properties of the individual areas are well established, less is known about the neural response to a whole person in a natural environment. Targeting an area of cortex that spans multiple functionally-selective face and body regions, we examined the relationship among neural activity patterns elicited in response to faces, bodies, and people in static and moving displays. When both stimuli were static or moving, pattern classification analyses indicated highly discriminable responses to faces, bodies, and whole people. Neural discrimination transferred in both directions between representations created from moving or static stimuli. It transferred also to stimuli experienced across static and dynamic presentations (one static and the other dynamic). In both transfer cases, however, discrimination accuracy decreased relative to the case where the representations were both created and tested with static or moving forms. Next, we examined the relative contribution of activity pattern and response magnitude to discrimination by comparing classifiers that operated with magnitude-normalized scans with classifiers that retained pattern and magnitude information. When both stimuli were moving or static, response magnitude contributed to classification, but the spatially distributed activity pattern accounted for most of the discrimination. Across static and moving presentations, activity pattern accounted completely for the discriminability of neural responses to faces, bodies, and people, with no contribution from response magnitude. Combined, the results indicate redundant and flexible access to person-based shape codes from moving and static presentations. The transfer of shape information across presentation types that preferentially access dorsal and ventral visual processing streams indicates that a common shape code may ground functional divisions in the processing of face and body information.

Defining the most probable location of the parahippocampal place area using cortex-based alignment and cross-validation.

ABSTRACT The parahippocampal place area (PPA) is a widely studied high‐level visual region in the human brain involved in place and scene processing. The goal of the present study was to identify the most probable location of place‐selective voxels in medial ventral temporal cortex. To achieve this goal, we first used cortex‐based alignment (CBA) to create a probabilistic place‐selective region of interest (ROI) from one group of 12 participants. We then tested how well this ROI could predict place selectivity in each hemisphere within a new group of 12 participants. Our results reveal that a probabilistic ROI (pROI) generated from one group of 12 participants accurately predicts the location and functional selectivity in individual brains from a new group of 12 participants, despite between subject variability in the exact location of place‐selective voxels relative to the folding of parahippocampal cortex. Additionally, the prediction accuracy of our pROI is significantly higher than that achieved by volume‐based Talairach alignment. Comparing the location of the pROI of the PPA relative to published data from over 500 participants, including data from the Human Connectome Project, shows a striking convergence of the predicted location of the PPA and the cortical location of voxels exhibiting the highest place selectivity across studies using various methods and stimuli. Specifically, the most predictive anatomical location of voxels exhibiting the highest place selectivity in medial ventral temporal cortex is the junction of the collateral and anterior lingual sulci. Methodologically, we make this pROI freely available (vpnl.stanford.edu/PlaceSelectivity), which provides a means to accurately identify a functional region from anatomical MRI data when fMRI data are not available (for example, in patient populations). Theoretically, we consider different anatomical and functional factors that may contribute to the consistent anatomical location of place selectivity relative to the folding of high‐level visual cortex. HIGHLIGHTSA probabilistic place ROI was created from cortex‐based alignment in 24 participantsCross‐validation shows that this ROI predicts place selectivity in new participantsThis ROI predicts voxels with peak place selectivity in >500 participantsThe collateral/lingual sulcal junction is most predictive of place selectivityWe share this predictive ROI with the field (vpnl.stanford.edu/PlaceSelectivity)

Neural perspectives on the other-race effect

Psychological studies have long shown that human memory is superior for faces of our own-race than for faces of other-races. In this paper, we review neural studies of own- versus other-race face processing. These studies divide naturally into those focused on socioaffective aspects of the other-race effect and those directed at high-level visual processing differences. The socioaffective studies consider how subconscious bias and emotional responses affect brain areas such as the amygdala, anterior cingulate cortex, and parahippocampal gyrus. The visual studies focus on face-selective areas in the ventral stream, such as the fusiform face area (FFA). In both cases, factors such as experience, familiarity, social/emotional responses, cultural learning, and bias modulate the patterns of neural activity elicited in response to own- and other-race faces.

On object selectivity and the anatomy of the human fusiform gyrus

&NA; pFs is a functionally‐defined region in the human brain that is involved in recognizing objects. A recent trend refers to pFs as the posterior fusiform sulcus, which is a neuroanatomical structure that does not exist. Here, we correct this mistake. To achieve this goal, we first recount the original definitions of pFs and then review the identification of sulci within and surrounding the fusiform gyrus (FG) including the mid‐fusiform sulcus (MFS), which is a tertiary sulcus within the FG. We highlight that tertiary sulci, such as the MFS, are often absent from brain atlases, which complicates the accurate localization of functional regions, as well as the understanding of structural‐functional relationships in ventral temporal cortex (VTC). When considering the location of object‐selective pFs from previously published data relative to the sulci surrounding the FG, as well as the MFS, we illustrate that (1) pFs spans several macroanatomical structures, which is consistent with the original definitions of pFs (Grill‐Spector et al., 1999, 2000), and (2) the topological relationship between pFs and MFS has both stable and variable features. To prevent future confusion regarding the anatomical location of functional regions within VTC, as well as to complement tools that automatically identify sulci surrounding the FG, we provide a method to automatically identify the MFS in individual brains using FreeSurfer. Finally, we highlight the benefits of using cortical surface reconstructions in large datasets to identify and quantify tertiary sulci compared to classic dissection methods because the latter often fail to differentiate tertiary sulci from shallow surface indentations produced by veins and arteries. Altogether, we propose that the inclusion of definitions and labels for tertiary sulci in neuroanatomical atlases and neuroimaging software packages will enhance understanding of functional‐structural relationships throughout the human brain.