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 object expertise correlates with neural selectivity in the fusiform face area (FFA). Although behavioral studies suggest that visual expertise is associated with increased use of holistic and configural information, little is known about the nature of the supporting neural representations. Using high-resolution 7-T functional magnetic resonance imaging, we recorded the multivoxel activation patterns elicited by whole cars, configurally disrupted cars, and car parts in individuals with a wide range of car expertise. A probabilistic support vector machine classifier was trained to differentiate activation patterns elicited by whole car images from activation patterns elicited by misconfigured car images. The classifier was then used to classify new combined activation patterns that were created by averaging activation patterns elicited by individually presented top and bottom car parts. In line with the idea that the configuration of parts is critical to expert visual perception, car expertise was negatively associated with the probability of a combined activation pattern being classified as a whole car in the right anterior FFA, a region critical to vision for categories of expertise. Thus, just as found for faces in normal observers, the neural representation of cars in right anterior FFA is more holistic for car experts than car novices, consistent with common mechanisms of neural selectivity for faces and other objects of expertise in this area.

Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v , that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing [“The Model”, TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception . Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a “spreading transform” for faces (separating them in representational space) that generalizes to objects that must be individuated. Interestingly, when the task of the network is basic level categorization, no increase in the correlation between domains is observed. Hence, our model predicts that it is the type of experience that matters and that the source of the correlation is in the fusiform face area, rather than in cortical areas that subserve basic level categorization. This result is consistent with our previous modeling elucidating why the FFA is recruited for novel domains of expertise [Tong, M. H., Joyce, C. A., & Cottrell, G. W. Why is the fusiform face area recruited for novel categories of expertise? A neurocomputational investigation. Brain Research, 1202, 14–24, 2008].

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.

Most theories of visual processing propose that object recognition is achieved in higher visual cortex. However, we show that category selectivity for musical notation can be observed in the first ERP component called the C1 (measured 40–60 msec after stimulus onset) with music-reading expertise. Moreover, the C1 note selectivity was observed only when the stimulus category was blocked but not when the stimulus category was randomized. Under blocking, the C1 activity for notes predicted individual music-reading ability, and behavioral judgments of musical stimuli reflected music-reading skill. Our results challenge current theories of object recognition, indicating that the primary visual cortex can be selective for musical notation within the initial feedforward sweep of activity with perceptual expertise and with a testing context that is consistent with the expertise training, such as blocking the stimulus category for music reading.

Prior neuroimaging work on visual perceptual expertise has focused on changes in the visual system, ignoring possible effects of acquiring expert visual skills in nonvisual areas. We investigated expertise for reading musical notation, a skill likely to be associated with multimodal abilities. We compared brain activity in music-reading experts and novices during perception of musical notation, Roman letters, and mathematical symbols and found selectivity for musical notation for experts in a widespread multimodal network of areas. The activity in several of these areas was correlated with a behavioral measure of perceptual fluency with musical notation, suggesting that activity in nonvisual areas can predict individual differences in visual expertise. The visual selectivity for musical notation is distinct from that for faces, single Roman letters, and letter strings. Implications of the current findings to the study of visual perceptual expertise, music reading, and musical expertise are discussed.

We document a seemingly unique case of severe prosopagnosia, L. R., who suffered damage to his anterior and inferior right temporal lobe as a result of a motor vehicle accident. We systematically investigated each of three factors associated with expert face recognition: fine-level discrimination, holistic processing, and configural processing (Experiments 1-3). Surprisingly, L. R. shows preservation of all three of these processes; that is, his performance in these experiments is comparable to that of normal controls. However, L. R. is only able to apply these processes over a limited spatial extent to the fine-level detail within faces. Thus, when the location of a given change is unpredictable (Experiment 3), L. R. exhibits normal detection of features and spatial configurations only for the lower half of each face. Similarly, when required to divide his attention over multiple face features, L. R. is able to determine the identity of only a single feature (Experiment 4). We discuss these results in the context of forming a better understanding of prosopagnosia and the mechanisms used in face recognition and visual expertise. We conclude that these mechanisms are not “all-or-none”, but rather can be impaired incrementally, such that they may remain functional over a restricted spatial area. This conclusion is consistent with previous research suggesting that perceptual expertise is acquired in a spatially incremental manner [Gauthier, I., & Tarr, M. J. Unraveling mechanisms for expert object recognition: Bridging brain activity and behavior. Journal of Experimental Psychology: Human Perception & Performance , 28, 431-446, 2002].

Agnosia, the impairment in object and face recognition despite intact vision and intelligence, is one of the most intriguing and debilitating neuropsychological deficits. The goal of this study was to determine whether S.M., an individual with longstanding visual agnosia and concomitant prosopagnosia, can be retrained to perform visual object recognition and, if so, what neural substrates mediate this reacquisition. Additionally, of interest is the extent to which training on one type of visual stimulus generalizes to other visual stimuli, as this informs our understanding of the organization of ventral visual cortex. Greebles were chosen as the stimuli for retraining given that, in neurologically normal individuals, these stimuli can engage the fusiform face area. Posttraining, S.M. showed significant improvement in recognizing Greebles, although he did not attain normal levels of performance. He was also able to recognize untrained Greebles and showed improvement in recognizing common objects. Surprisingly, his performance on face recognition, albeit poor initially, was even more impaired following training. A comparison of preand postintervention functional neuroimaging data mirrored the behavioral findings: Face-selective voxels in the fusiform gyrus prior to training were no longer so and were, in fact, more Greeble-selective. The findings indicate potential for experience-dependent dynamic reorganization in agnosia with the possibility that residual neural tissue, with limited capacity, will compete for representations.

According to modular models of cortical organization, many areas of the extrastriate cortex are dedicated to object categories. These models often assume an early processing stage for the detection of category membership. Can functional imaging isolate areas responsible for detection of members of a category, such as faces or letters? We consider whether responses in three different areas (two selective for faces and one selective for letters) support category detection. Activity in these areas habituates to the repeated presentation of one exemplar more than to the presentation of different exemplars of the same category, but only for the category for which the area is selective. Thus, these areas appear to play computational roles more complex than detection, processing stimuli at the individual level. Drawing from prior work, we suggest that face-selective areas may be involved in the perception of faces at the individual level, whereas letter-selective regions may be tuning themselves to font information in order to recognize letters more efficiently.

We argue that the current literature on prosopagnosia fails to demonstrate unequivocal evidence for a disproportionate impairment for faces as compared to nonface objects. Two prosopagnosic subjects were tested for the discrimination of objects from several categories (face as well as nonface) at different levels of categorization (basic, subordinate, and exemplar levels). Several dependent measures were obtained including accuracy, signal detection measures, and response times. The results from Experiments 1 to 4 demonstrate that, in simultaneous-matching tasks, response times may reveal impairments with nonface objects in subjects whose error rates only indicate a face deficit. The results from Experiments 5 and 6 show that, given limited stimulus presentation times for face and nonface objects, the same subjects may demonstrate a deªcit for both stimulus categories in sensitivity. In Experiments 7, 8 and 9, a match-to-sample task that places greater demands on memory led to comparable recognition sensitivity with both face and nonface objects. Regardless of object category, the prosopagnosic subjects were more affected by manipulations of the level of categorization than normal controls. This result raises questions regarding neuropsychological evidence for the modularity of face recognition, as well as its theoretical and methodological foundations.