Challenges in replication: Does amygdala gray matter volume relate to social network size?

In this work, we tried to replicate and extend prior research on the relationship between social network size and the volume of the amygdala. We focused on the earliest evidence for this relationship (Bickart et al., Nature Neuroscience 14(2), 163-164, 2011) and another methodologically unique study that often is cited as a replication (Kanai et al., Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012). Despite their tight link in the literature, we argue that Kanai et al. (Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012) is not a replication of Bickart et al. Nature Neuroscience 14(2), 163-164 (2011), because it uses different morphometric measurements. We collected data from 128 participants on a 7-Tesla MRI and examined variations in gray matter volume (GMV) in the amygdala and its nuclei. We found inconclusive support for a correlation between measures of real-world social network and amygdala GMV, with small effect sizes and only anecdotal evidence for a positive relationship. We found support for the absence of a correlation between measures of online social network and amygdala GMV. We discuss different challenges faced in replication attempts for small effects, as initially reported in these two studies, and suggest that the results would be most helpful in the context of estimation and future meta-analytical efforts. Our findings underscore the value of a narrow approach in replication of brain-behavior relationships, one that is focused enough to investigate the specifics of what is measured. This approach can provide a complementary perspective to the more popular "thematic" alternative, in which conclusions are often broader but where conclusions may become disconnected from the evidence.

The neural correlates of domain-general visual ability.

People vary in their general ability to compare, identify, and remember objects. Research using latent variable modeling identifies a domain-general visual recognition ability (called o) that reflects correlations among different visual tasks and categories. We measure associations between a psychometrically-sensitive measure of o and a neurometrically-sensitive measure of visual sensitivity to shape. We report evidence for distributed neural correlates of o using functional and anatomical regions-of-interest (ROIs) as well as whole brain analyses. Neural selectivity to shape is associated with o in several regions of the ventral pathway, as well as additional foci in parietal and premotor cortex. Multivariate analyses suggest the distributed effects in ventral cortex reflect a common mechanism. The network of brain areas where neural selectivity predicts o is similar to that evoked by the most informative features for object recognition in prior work, showing convergence of 2 different approaches on identifying areas that support the best object recognition performance. Because o predicts performance across many visual tasks for both novel and familiar objects, we propose that o could predict the magnitude of neural changes in task-relevant areas following experience with specific task and object category.

Thickness of Deep Layers in the Fusiform Face Area Predicts Face Recognition.

People with superior face recognition have relatively thin cortex in face-selective brain areas, whereas those with superior vehicle recognition have relatively thick cortex in the same areas. We suggest that these opposite correlations reflect distinct mechanisms influencing cortical thickness (CT) as abilities are acquired at different points in development. We explore a new prediction regarding the specificity of these effects through the depth of the cortex: that face recognition selectively and negatively correlates with thickness of the deepest laminar subdivision in face-selective areas. With ultrahigh resolution MRI at 7T, we estimated the thickness of three laminar subdivisions, which we term "MR layers," in the right fusiform face area (FFA) in 14 adult male humans. Face recognition was negatively associated with the thickness of deep MR layers, whereas vehicle recognition was positively related to the thickness of all layers. Regression model comparisons provided overwhelming support for a model specifying that the magnitude of the association between face recognition and CT differs across MR layers (deep vs. superficial/middle) whereas the magnitude of the association between vehicle recognition and CT is invariant across layers. The total CT of right FFA accounted for 69% of the variance in face recognition, and thickness of the deep layer alone accounted for 84% of this variance. Our findings demonstrate the functional validity of MR laminar estimates in FFA. Studying the structural basis of individual differences for multiple abilities in the same cortical area can reveal effects of distinct mechanisms that are not apparent when studying average variation or development.

Visual imagery of faces and cars in face-selective visual areas.

Neuroimaging provides a unique tool to investigate otherwise difficult-to-access mental processes like visual imagery. Prior studies support the idea that visual imagery is a top-down reinstatement of visual perception, and it is likely that this extends to object processing. Here we use functional MRI and multi-voxel pattern analysis to ask if mental imagery of cars engages the fusiform face area, similar to what is found during perception. We test only individuals who we assumed could imagine individual car models based on their above-average perceptual abilities with cars. Our results provide evidence that cars are represented differently from common objects in face-selective visual areas, at least in those with above-average car recognition ability. Moreover, pattern classifiers trained on data acquired during imagery can decode the neural response pattern acquired during perception, suggesting that the tested object categories are represented similarly during perception and visual imagery. The results suggest that, even at high-levels of visual processing, visual imagery mirrors perception to some extent, and that face-selective areas may in part support non-face object imagery.

The Role of Experience in the Face-Selective Response in Right FFA.

The expertise hypothesis suggests the fusiform face area (FFA) is more responsive to faces than to other categories because of experience individuating faces. Accordingly, individual differences in FFA's selectivity for faces should relate to differences in behavioral face-recognition ability. However, previous studies have not demonstrated this, while the comparable association is often observed with nonface objects. We created a training paradigm with conditions sufficient to observe the same effect with faces. First, we selected subjects with a wide range of behavioral face-recognition abilities, then we manipulated experience with an artificial race of faces based on subjects' pretraining ability, maximizing variability in face individuation. Neural selectivity was measured for Caucasian faces and artificial-race faces relative to control objects. Selecting subjects for greater variability in face-recognition ability revealed an association between behavior and FFA selectivity for Caucasian faces, with an effect exclusive to the middle right FFA (FFA2). Manipulating experience with artificial-race faces led to stronger brain-behavior correlation for artificial-race faces, also in right FFA2. Group analyses showed an overlap of these effects for Caucasian and artificial-race faces in right FFA2. The right FFA2 appears particularly sensitive to experience with faces just as it is for nonface objects.

Domain-specific reports of visual imagery vividness are not related to perceptual expertise.

Just as people vary in their perceptual expertise with a given domain, they also vary in their abilities to imagine objects. Visual imagery and perception share common mechanisms. However, it is unclear whether domain-specific expertise is relevant to visual imagery. Although the vividness of visual imagery is typically measured as a domain-general construct, a component of this vividness may be domain-specific. For example, individuals who have gained perceptual expertise with a specific domain might experience clearer mental images within this domain. Here we investigated whether perceptual expertise for cars relates to visual imagery vividness in the same domain, by assessing the correlations between a widely used domain-general measure of visual imagery vividness (the Vividness of Visual Imagery Questionnaire; Marks in British Journal of Psychology, 64, 17-24, 1973), a new measure of visual imagery vividness specific to cars, and behavioral tests of car expertise. We found that domain-specific imagery relates most strongly to general imagery vividness and less strongly to self-reported expertise, while it does not relate to perceptual or semantic expertise.

A functional neuroimaging study of fusiform response to restricted interests in children and adolescents with autism spectrum disorder.

BACKGROUND: While autism spectrum disorder (ASD) is characterized by both social communication deficits and restricted and repetitive patterns of behavior and interest, literature examining possible neural bases of the latter class of symptoms is limited. The fusiform face area (FFA) is a region in the ventral temporal cortex that not only shows preferential responsiveness to faces but also responds to non-face objects of visual expertise. Because restricted interests in ASD are accompanied by high levels of visual expertise, the objective of this study was to determine the extent to which this region responds to images related to restricted interests in individuals with ASD, compared to individuals without ASD who have a strong hobby or interest. METHODS: Children and adolescents with and without ASD with hobbies or interests that consumed a pre-determined minimum amount of time were identified, and the intensity, frequency, and degree of interference of these interests were quantified. Each participant underwent functional magnetic resonance imaging (fMRI) while viewing images related to their personal restricted interests (in the ASD group) or strong interest or hobby (in the comparison group). A generalized linear model was used to compare the intensity and spatial extent of fusiform gyrus response between groups, controlling for the appearance of faces in the stimuli. RESULTS: Images related to interests and expertise elicited response in FFA in both ASD and typically developing individuals, but this response was more robust in ASD. CONCLUSIONS: These findings add neurobiological support to behavioral observations that restricted interests are associated with enhanced visual expertise in ASD, above and beyond what would be expected for simply a strong interest. Further, the results suggest that brain regions associated with social functioning may not be inherently less responsive in ASD, but rather may be recruited by different environmental stimuli. This study contributes to our understanding of the neural basis of restricted interests in ASD and may provide clues toward developing novel interventions.

Cortical Thickness in Fusiform Face Area Predicts Face and Object Recognition Performance.

The fusiform face area (FFA) is defined by its selectivity for faces. Several studies have shown that the response of FFA to nonface objects can predict behavioral performance for these objects. However, one possible account is that experts pay more attention to objects in their domain of expertise, driving signals up. Here, we show an effect of expertise with nonface objects in FFA that cannot be explained by differential attention to objects of expertise. We explore the relationship between cortical thickness of FFA and face and object recognition using the Cambridge Face Memory Test and Vanderbilt Expertise Test, respectively. We measured cortical thickness in functionally defined regions in a group of men who evidenced functional expertise effects for cars in FFA. Performance with faces and objects together accounted for approximately 40% of the variance in cortical thickness of several FFA patches. Whereas participants with a thicker FFA cortex performed better with vehicles, those with a thinner FFA cortex performed better with faces and living objects. The results point to a domain-general role of FFA in object perception and reveal an interesting double dissociation that does not contrast faces and objects but rather living and nonliving objects.

The reliability of individual differences in face-selective responses in the fusiform gyrus and their relation to face recognition ability.

Face recognition ability varies widely in the normal population and there is increasing interest in linking individual differences in perception to their neural correlates. Such brain-behavior correlations require that both the behavioral measures and the selective BOLD responses be reliable. The reliability of the location of the fusiform face area (FFA) has been demonstrated in several studies. Here, we address reliability of a different kind: reliability of the magnitude of responses to faces within this localized region. We calculated split-half reliability of face-selective responses within functionally defined posterior and anterior face-selective patches in the fusiform gyrus (FFA1/FFA2). We used data from two published studies that included both a functional localizer for face-selective regions and independent data suitable for quantifying face-selectivity. We found highly reliable face selectivity in both hemispheres that was highest in the centermost voxel(s) compared to larger regions of interest. Differences in face-selectivity between the two face patches within one hemisphere and across hemispheres were also reliable. Our results reveal considerable reliability of face-selective signals in and across FFA in adults. Given the good reliability of behavioral measures of face recognition, prior failures to find a relationship between the mean response to faces in FFA and behavioral face recognition in normal adult subjects are unlikely to be due to limitations of the measurements.

Measuring nonvisual knowledge about object categories: The Semantic Vanderbilt Expertise Test.

How much do people differ in their abilities to recognize objects, and what is the source of these differences? To address the first question, psychologists have created visual learning tests including the Cambridge Face Memory Test (Duchaine & Nakayama, 2006) and the Vanderbilt Expertise Test (VET; McGugin et al., 2012). The second question requires consideration of the influences of both innate potential and experience, but experience is difficult to measure. One solution is to measure the products of experience beyond perceptual knowledge-specifically, nonvisual semantic knowledge. For instance, the relation between semantic and perceptual knowledge can help clarify the nature of object recognition deficits in brain-damaged patients (Barton, Hanif, & Ashraf, Brain, 132, 3456-3466, 2009). We present a reliable measure of nonperceptual knowledge in a format applicable across categories. The Semantic Vanderbilt Expertise Test (SVET) measures knowledge of relevant category-specific nomenclature. We present SVETs for eight categories: cars, planes, Transformers, dinosaurs, shoes, birds, leaves, and mushrooms. The SVET demonstrated good reliability and domain-specific validity. We found partial support for the idea that the only source of domain-specific shared variance between the VET and SVET is experience with a category. We also demonstrated the utility of the SVET-Bird in experts. The SVET can facilitate the study of individual differences in visual recognition.

Differential item functioning analysis of the Vanderbilt Expertise Test for cars.

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge.

Experience moderates overlap between object and face recognition, suggesting a common ability.

Some research finds that face recognition is largely independent from the recognition of other objects; a specialized and innate ability to recognize faces could therefore have little or nothing to do with our ability to recognize objects. We propose a new framework in which recognition performance for any category is the product of domain-general ability and category-specific experience. In Experiment 1, we show that the overlap between face and object recognition depends on experience with objects. In 256 subjects we measured face recognition, object recognition for eight categories, and self-reported experience with these categories. Experience predicted neither face recognition nor object recognition but moderated their relationship: Face recognition performance is increasingly similar to object recognition performance with increasing object experience. If a subject has a lot of experience with objects and is found to perform poorly, they also prove to have a low ability with faces. In a follow-up survey, we explored the dimensions of experience with objects that may have contributed to self-reported experience in Experiment 1. Different dimensions of experience appear to be more salient for different categories, with general self-reports of expertise reflecting judgments of verbal knowledge about a category more than judgments of visual performance. The complexity of experience and current limitations in its measurement support the importance of aggregating across multiple categories. Our findings imply that both face and object recognition are supported by a common, domain-general ability expressed through experience with a category and best measured when accounting for experience.

Heterogeneity of FFA responses or multiplexing?

Recent work using cluster analysis of brain activity during movies revealed distinct clusters that respond to faces and different non-face categories in the fusiform face area (FFA). Because of the limited heterogeneity observed, these results could mean that the FFA contains one population of cells capable of representing multiple categories.

The Vanderbilt Expertise Test reveals domain-general and domain-specific sex effects in object recognition.

Individual differences in face recognition are often contrasted with differences in object recognition using a single object category. Likewise, individual differences in perceptual expertise for a given object domain have typically been measured relative to only a single category baseline. In Experiment 1, we present a new test of object recognition, the Vanderbilt Expertise Test (VET), which is comparable in methods to the Cambridge Face Memory Task (CFMT) but uses eight different object categories. Principal component analysis reveals that the underlying structure of the VET can be largely explained by two independent factors, which demonstrate good reliability and capture interesting sex differences inherent in the VET structure. In Experiment 2, we show how the VET can be used to separate domain-specific from domain-general contributions to a standard measure of perceptual expertise. While domain-specific contributions are found for car matching for both men and women and for plane matching in men, women in this sample appear to use more domain-general strategies to match planes. In Experiment 3, we use the VET to demonstrate that holistic processing of faces predicts face recognition independently of general object recognition ability, which has a sex-specific contribution to face recognition. Overall, the results suggest that the VET is a reliable and valid measure of object recognition abilities and can measure both domain-general skills and domain-specific expertise, which were both found to depend on the sex of observers.

Race-specific perceptual discrimination improvement following short individuation training with faces.

This study explores the effect of individuation training on the acquisition of race-specific expertise. First, we investigated whether practice individuating other-race faces yields improvement in perceptual discrimination for novel faces of that race. Second, we asked whether there was similar improvement for novel faces of a different race for which participants received equal practice, but in an orthogonal task that did not require individuation. Caucasian participants were trained to individuate faces of one race (African American or Hispanic) and to make difficult eye-luminance judgments on faces of the other race. By equating these tasks we are able to rule out raw experience, visual attention, or performance/success-induced positivity as the critical factors that produce race-specific improvements. These results indicate that individuation practice is one mechanism through which cognitive, perceptual, and/or social processes promote growth of the own-race face recognition advantage.

Interference in character processing reflects common perceptual expertise across writing systems.

Perceptual expertise, even within the visual domain, can take many forms, depending on the goals of the practiced task and the visual information available to support performance. Given the same goals, expertise for different categories can recruit common perceptual resources, which could lead to interference during concurrent processing. We measured whether irrelevant characters of one writing system produce interference during visual search for characters of another writing system, as a function of expertise. Chinese-English bilinguals and English readers searched for target Roman letters among other distractors in a rapid serial visual presentation (RSVP) sequence. Chinese character distractors interfered with Roman letter search more than pseudoletter distractors, only for bilingual readers, suggesting a common perceptual bottleneck for Roman and Chinese processing in experts with both domains. We ruled out an explanation at the level of phonetic codes, by showing that concurrent verbal rehearsal has no effect on the magnitude of such interference. These findings converge with results showing competition between faces and cars in car experts to suggest that different domains of expertise that overlap in their cortical representations also possess a common perceptual bottleneck.

Irrelevant objects of expertise compete with faces during visual search.

Prior work suggests that nonface objects of expertise can interfere with the perception of faces when the two categories are alternately presented, suggesting competition for shared perceptual resources. Here, we ask whether task-irrelevant distractors from a category of expertise compete when faces are presented in a standard visual search task. Participants searched for a target (face or sofa) in an array containing both relevant and irrelevant distractors. The number of distractors from the target category (face or sofa) remained constant, whereas the number of distractors from the irrelevant category (cars) varied. Search slopes, calculated as a function of the number of irrelevant cars, were correlated with car expertise. The effect was not due to car distractors grabbing attention, because they did not compete with sofa targets. Objects of expertise interfere with face perception even when they are task irrelevant, visually distinct, and separated in space from faces.

Expertise increases the functional overlap between face and object perception.

Recent studies indicate that expertise with objects can interfere with face processing. Although competition occurs between faces and objects of expertise, it remains unclear whether this reflects an expertise-specific bottleneck or the fact that objects of expertise grab attention and thereby consume more central resources. We investigated the perceptual costs of expertise by measuring visual thresholds for identifying targets embedded within RSVP sequences presented at varying temporal rates. Car experts and novices searched for face targets among face and car distractors, or watch targets among watch and car distractors. Remarkably, car experts were slower than novices at identifying faces among task-irrelevant cars, yet faster than novices at identifying watches among cars. This suggests that car expertise leads to greater functional overlap between cars and faces while reducing the functional overlap between cars and objects, a result incompatible with the notion of an encapsulated module for exclusive processing of faces.