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.

Deep whole brain segmentation of 7T structural MRI.

7T magnetic resonance imaging (MRI) has the potential to drive our understanding of human brain function through new contrast and enhanced resolution. Whole brain segmentation is a key neuroimaging technique that allows for region-by-region analysis of the brain. Segmentation is also an important preliminary step that provides spatial and volumetric information for running other neuroimaging pipelines.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Item response theory analyses of the Cambridge Face Memory Test (CFMT).

We evaluated the psychometric properties of the Cambridge Face Memory Test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bifactor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and 3 specific factors clustered by targets of CFMT.

Robust expertise effects in right FFA.

The fusiform face area (FFA) is one of several areas in occipito-temporal cortex whose activity is correlated with perceptual expertise for objects. Here, we investigate the robustness of expertise effects in FFA and other areas to a strong task manipulation that increases both perceptual and attentional demands. With high-resolution fMRI at 7T, we measured responses to images of cars, faces and a category globally visually similar to cars (sofas) in 26 subjects who varied in expertise with cars, in (a) a low load 1-back task with a single object category and (b) a high load task in which objects from two categories were rapidly alternated and attention was required to both categories.

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.

Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition.

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g.

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.

High-resolution imaging of expertise reveals reliable object selectivity in the fusiform face area related to perceptual performance.

The fusiform face area (FFA) is a region of human cortex that responds selectively to faces, but whether it supports a more general function relevant for perceptual expertise is debated. Although both faces and objects of expertise engage many brain areas, the FFA remains the focus of the strongest modular claims and the clearest predictions about expertise. Functional MRI studies at standard-resolution (SR-fMRI) have found responses in the FFA for nonface objects of expertise, but high-resolution fMRI (HR-fMRI) in the FFA [Grill-Spector K, et al.

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.

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.

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.

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.

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.

Perceptual expertise with objects predicts another hallmark of face perception.

There is no shortage of evidence to suggest that faces constitute a special category in human perception. Surprisingly little consensus exists, however, regarding the interpretation of these results. The question persists: what makes faces special? We address this issue via one hallmark of face perception-its striking sensitivity to low-level image format-and present evidence in favor of an expertise account of the specialization of face perception.