Beyond shape: how you learn about objects affects how they are represented in visual cortex

Distinct but related abilities for visual and haptic object recognition

People vary in their ability to recognize objects visually. Individual differences for matching and recognizing objects visually is supported by a domain-general ability capturing common variance across different tasks (e.g., Richler et al., Psychological Review, 126, 226-251, 2019). Behavioral (e.g., Cooke et al., Neuropsychologia, 45, 484-495, 2007) and neural evidence (e.g., Amedi, Cerebral Cortex, 12, 1202-1212, 2002) suggest overlapping mechanisms in the processing of visual and haptic information in the service of object recognition, but it is unclear whether such group-average results generalize to individual differences. Psychometrically validated measures are required, which have been lacking in the haptic modality. We investigate whether object recognition ability is specific to vision or extends to haptics using psychometric measures we have developed. We use multiple visual and haptic tests with different objects and different formats to measure domain-general visual and haptic abilities and to test for relations across them. We measured object recognition abilities using two visual tests and four haptic tests (two each for two kinds of haptic exploration) in 97 participants. Partial correlation and confirmatory factor analyses converge to support the existence of a domain-general haptic object recognition ability that is moderately correlated with domain-general visual object recognition ability. Visual and haptic abilities share about 25% of their variance, supporting the existence of a multisensory domain-general ability while leaving a substantial amount of residual variance for modality-specific abilities. These results extend our understanding of the structure of object recognition abilities; while there are mechanisms that may generalize across categories, tasks, and modalities, there are still other mechanisms that are distinct between modalities.

Does food recognition depend on color?

Color is considered important in food perception, but its role in food-specific visual mechanisms is unclear. We explore this question in North American adults. We build on work revealing contributions from domain-general and domain-specific abilities in food recognition and a negative correlation between the domain-specific component and food neophobia (FN, aversion to novel food). In Study 1, participants performed two food-recognition tests, one in color and one in grayscale. Removing color reduced performance, but food recognition was predicted by domain-general and -specific abilities, and FN negatively correlated with food recognition. In Study 2, we removed color from both food tests. Food recognition was still predicted by domain-general and food-specific abilities, but with a relation between food-specific ability and FN. In Study 3, color-blind men reported lower FN than men with normal color perception. These results suggest two separate food-specific recognition mechanisms, only one of which is dependent on color.

Using representational similarity analysis to reveal category and process specificity in visual object recognition

Cross-condition comparisons on neurodevelopmental conditions are central in neurodiversity research. In the realm of visual perception, the performance of participants with different category-specific disorders such as developmental prosopagnosia (problems with faces) and dyslexia (problems with words) have contributed to understanding of perceptual processes involved in word and face recognition. Alterations in face and word recognition are present in several neurodiverse populations, and improved knowledge about their relationship may increase our understanding of this variability of impairment. The present study investigates organizing principles of visual object processing and their implications for developmental disorders of recognition. Some accounts suggest that distinct mechanisms are responsible for recognizing objects of different categories, while others propose that categories share or even compete for cortical resources. We took an individual differences approach to estimate the relationship between abilities in recognition. Neurotypical participants (N = 97 after outlier exclusion) performed a match-to-sample task with faces, houses, and pseudowords. Either individual features or feature configurations were manipulated. To estimate the separability of visual recognition mechanisms, we used representational similarity analysis (RSA) where correlational matrices for accuracy were compared to predicted data patterns. Recognition abilities separated into face recognition on one hand and house/pseudoword recognition on the other, indicating that face recognition may rely on relatively selective mechanisms in neurotypicals. We also found evidence for a general visual object recognition mechanism, while some combinations of category (faces, houses, words) and processing type (featural, configural) likely rely on additional mechanisms. Developmental conditions may therefore reflect combinations of impaired and intact aspects of specific and general visual object recognition mechanisms, where featural and configural processes for one object category separate from the featural or configural processing of another. More generally, RSA is a promising approach for advancing understanding of neurodiversity, including shared aspects and distinctions between neurodevelopmental conditions of visual recognition.

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.

Ethnicity, minority status, and inter-group bias: A systematic meta-analysis on fMRI studies

Introduction

This meta-analysis investigated (1) whether ethnic minority and majority members have a neural inter-group bias toward each other, and (2) whether various ethnic groups (i.e., White, Black, and Asian) are processed in the brain differently by the other respective ethnicities.

Methods

A systematic coordinate-based meta-analysis of functional magnetic resonance imaging (fMRI) studies was conducted using Web of Science, PubMed, and PsycINFO (altogether 50 datasets, n = 1211, 50.1% female).

Results

We found that ethnic minority members did not show any signs of neural inter-group bias (e.g., no majority-group derogation). Ethnic majority members, in turn, expressed biased responses toward minority (vs. majority) members in frontal, parietal, temporal, and occipital regions that are known to be involved in e.g., facial processing, attention, and perspective-taking. We also found differences in neural response patterns toward different ethnic groups (White, Black, and Asian); broadest biases in neural response patterns were evident toward Black individuals (in non-Black individuals). Heterogeneity was mostly minor or low.

Discussion

Overall, the findings increase understanding of neural processes involved in ethnicity perception and cognition as well as ethnic prejudices and discrimination. This meta-analysis provides explanations for previous behavioral reports on ethnic discrimination toward minority groups.

Distinct neural-behavioral correspondence within face processing and attention networks for the composite face effect

The composite face effect (CFE) is recognized as a hallmark for holistic face processing, but our knowledge remains sparse about its cognitive and neural loci. Using functional magnetic resonance imaging with independent localizer and complete composite face task, we here investigated its neural-behavioral correspondence within face processing and attention networks. Complementing classical comparisons, we adopted a dimensional reduction approach to explore the core cognitive constructs of the behavioral CFE measurement. Our univariate analyses found an alignment effect in regions associated with both the extended face processing network and attention networks. Further representational similarity analyses based on the Euclidian distances among all experimental conditions were used to identify cortical regions with reliable neural-behavioral correspondences. Multidimensional scaling and hierarchical clustering analyses for neural-behavioral correspondence data revealed two principal components underlying the behavioral CFE effect, which fit best to the neural responses in the bilateral insula and medial frontal gyrus. These findings highlight the distinct neurocognitive contributions of both face processing and attentional networks to the behavioral CFE outcome, which bridge the gaps between face recognition and attentional control models.

Face and word composite effects are similarly affected by priming of local and global processing

Holistic processing has been shown with both faces and words, but it is unclear how similar their underlying mechanisms are. In this study attention to global and local features was manipulated and the consequences for holistic word and face processing were examined. On each trial participants were presented two Navon figures and told to focus on either the global or the local level. Then they performed a composite task in which they indicated whether the target halves of two sequentially presented faces or words were the same or different, ignoring the irrelevant halves. Similar stronger global priming effects were found for faces and words, indicating that holistic processing for the two types of stimuli were susceptible to attention manipulations to similar degrees, which was confirmed with Bayesian analyses. The findings add to the investigation of the similarity and differences between holistic processing and help reveal those aspects of holistic processing that are domain general and those specific to individual categories.

From convolutional neural networks to models of higher-level cognition (and back again)

The remarkable successes of convolutional neural networks (CNNs) in modern computer vision are by now well known, and they are increasingly being explored as computational models of the human visual system. In this paper, we ask whether CNNs might also provide a basis for modeling higher-level cognition, focusing on the core phenomena of similarity and categorization. The most important advance comes from the ability of CNNs to learn high-dimensional representations of complex naturalistic images, substantially extending the scope of traditional cognitive models that were previously only evaluated with simple artificial stimuli. In all cases, the most successful combinations arise when CNN representations are used with cognitive models that have the capacity to transform them to better fit human behavior. One consequence of these insights is a toolkit for the integration of cognitively motivated constraints back into CNN training paradigms in computer vision and machine learning, and we review cases where this leads to improved performance. A second consequence is a roadmap for how CNNs and cognitive models can be more fully integrated in the future, allowing for flexible end-to-end algorithms that can learn representations from data while still retaining the structured behavior characteristic of human cognition.

Perceptual expertise with Chinese characters predicts Chinese reading performance among Hong Kong Chinese children with developmental dyslexia

This study explores the theoretical proposal that developmental dyslexia involves a failure to develop perceptual expertise with words despite adequate education. Among a group of Hong Kong Chinese children diagnosed with developmental dyslexia, we investigated the relationship between Chinese word reading and perceptual expertise with Chinese characters. In a perceptual fluency task, the time of visual exposure to Chinese characters was manipulated and limited such that the speed of discrimination of a short sequence of Chinese characters at an accuracy level of 80% was estimated. Pair-wise correlations showed that perceptual fluency for characters predicted speeded and non-speeded word reading performance. Exploratory hierarchical regressions showed that perceptual fluency for characters accounted for 5.3% and 9.6% variance in speeded and non-speeded reading respectively, in addition to age, non-verbal IQ, phonological awareness, morphological awareness, rapid automatized naming (RAN) and perceptual fluency for digits. The findings suggest that perceptual expertise with words plays an important role in Chinese reading performance in developmental dyslexia, and that perceptual training is a potential remediation direction.

Investigating holistic face processing within and outside of face-responsive brain regions

It has been shown that human faces are processed holistically (i.e. as indecomposable wholes, rather than by their component parts) and this holistic face processing is linked to brain activity in face-responsive brain regions. Although several brain regions outside of the face-responsive network are also sensitive to relational processing and perceptual grouping, whether these non-face-responsive regions contribute to holistic processing remains unclear. Here, we investigated holistic face processing in the composite face paradigm both within and outside of face-responsive brain regions. We recorded participants' brain activity using fMRI while they performed a composite face task. Behavioural results indicate that participants tend to judge the same top face halves as different when they are aligned with different bottom face halves but not when they are misaligned, demonstrating a composite face effect. Neuroimaging results revealed significant differences in responses to aligned and misaligned faces in the lateral occipital complex (LOC), and trends in the anterior part of the fusiform face area (FFA2) and transverse occipital sulcus (TOS), suggesting that these regions are sensitive to holistic versus part-based face processing. Furthermore, the retrosplenial cortex (RSC) and the parahippocampal place area (PPA) showed a pattern of neural activity consistent with a holistic representation of face identity, which also correlated with the strength of the behavioural composite face effect. These results suggest that neural activity in brain regions both within and outside of the face-responsive network contributes to the composite-face effect.

A reliable and valid tool for measuring visual recognition ability with musical notation

Recognizing musical notation is an important skill to a full participation of Western classical music, but remains a largely under-researched topic in the psychology of music. One plausible reason of such omission is that, in the past, the research field has heavily relied on self-report of music reading ability, which was subjective and highly variable. This paper presents a reliable and valid tool for objectively measuring individual abilities in visual recognition of musical notation. The visual fluency task measures how fast one can accurately recognize a sequence of musical notation at a desired accuracy level using the adaptive psychometric method QUEST. We checked the reliability of this task in over 200 participants in terms of Guttman's λ-2 and Cronbach's alpha. Also, we evaluated the construct validity of this task by considering the convergent validity of this task with multiple external real-world measures of one's musical training background, with numerous experimental measures of visual tendencies of musical notation recognition and with sight-reading performance. Overall, the visual fluency task achieved satisfactory reliability and validity for measuring abilities in recognizing musical notation. This opens the door for characterizing the cognitive mechanisms, development, and individual differences in musical notation recognition, for understanding music learning and music psychology and for understanding of visual perceptual expertise in general.

A heuristic information cluster search approach for precise functional brain mapping

Detection of the relevant brain regions for characterizing the distinction between cognitive conditions is one of the most sought after objectives in neuroimaging research. A popular approach for achieving this goal is the multivariate pattern analysis which is currently conducted through a number of approaches such as the popular searchlight procedure. This is due to several advantages such as being automatic and flexible with regards to size of the search region. However, these approaches suffer from a number of limitations which can lead to misidentification of truly informative regions which in turn results in imprecise information maps. These limitations mainly stem from several factors such as the fact that the information value of the search spheres are assigned to the voxel at the center of them (in case of searchlight), the requirement for manual tuning of parameters such as searchlight radius and shape, and high complexity and low interpretability in commonly used machine learning-based approaches. Other drawbacks include overlooking the structure and interactions within the regions, and the disadvantages of using certain regularization techniques in analysis of datasets with characteristics of common functional magnetic resonance imaging data. In this article, we propose a fully data-driven maximum relevance minimum redundancy search algorithm for detecting precise information value of the clusters within brain regions while alleviating the above-mentioned limitations. Moreover, in order to make the proposed method faster, we propose an efficient algorithmic implementation. We evaluate and compare the proposed algorithm with the searchlight procedure as well as least absolute shrinkage and selection operator regularization-based mapping approach using both real and synthetic datasets. The analysis results of the proposed approach demonstrate higher information detection precision and map specificity compared to the benchmark approaches.

Factors Determining Where Category-Selective Areas Emerge in Visual Cortex

A hallmark of functional localization in the human brain is the presence of areas in visual cortex specialized for representing particular categories such as faces and words. Why do these areas appear where they do during development? Recent findings highlight several general factors to consider when answering this question. Experience-driven category selectivity arises in regions that have: (i) pre-existing selectivity for properties of the stimulus, (ii) are appropriately placed in the computational hierarchy of the visual system, and (iii) exhibit domain-specific patterns of connectivity to nonvisual regions. In other words, cortical location of category selectivity is constrained by what category will be represented, how it will be represented, and why the representation will be used.

Visual training with musical notes changes late but not early electrophysiological responses in the visual cortex

Visual expertise with musical notation is unique. Fluent music readers show selectively higher activity to musical notes than to other visually similar patterns in both the retinotopic and higher-level visual areas and both very early (e.g., C1) and later (e.g., N170) visual event-related potential (ERP) components. This is different from domains such as face and letter perception, of which the neural expertise marker is typically found in the higher-level ventral visual areas and later (e.g., N170) ERP components. An intriguing question concerns whether the visual skills and neural selectivity observed in music-reading experts are a result of the effects of extensive visual experience with musical notation. The current study aimed to investigate the causal relationship between visual experience and its neural changes with musical notation. Novices with no formal musical training experience were trained to visually discriminate between note patterns in the laboratory for 10-26 hr such that their performance was comparable with fluent music readers. The N170 component became more selective for musical notes after training. Training was not, however, followed by changes in the earlier C1 component. The findings show that visual training is enough for causing changes in the responses of the higher-level visual areas to musical notation while the engagement of the early visual areas may involve additional nonvisual factors.

Bilateral engagement of the occipito-temporal cortex in response to dance kinematics in experts

Previous evidence has shown neuroplastic changes in brain anatomy and connectivity associated with the acquisition of professional visuomotor skills. Reduced hemispherical asymmetry was found in the sensorimotor and visual areas in expert musicians and athletes compared with non-experts. Moreover, increased expertise with faces, body, and objects resulted in an enhanced engagement of the occipito-temporal cortex (OTC) during stimulus observation. The present study aimed at investigating whether intense and extended practice with dance would result in an enhanced symmetric response of OTC at an early stage of action processing. Expert ballet dancers and non-dancer controls were presented with videos depicting ballet steps during EEG recording. The observation of the moving dancer elicited a posterior N2 component, being larger over the left hemisphere in dancers than controls. The source reconstruction (swLORETA) of the negativity showed the engagement of the bilateral inferior and middle temporal regions in experts, while right-lateralized activity was found in controls. The dancers also showed an early P2 and enhanced P300 responses, indicating faster stimulus processing and subsequent recognition. This evidence seemed to suggest expertise-related increased sensitivity of the OTC in encoding body kinematics. Thus, we speculated that long-term whole-body practice would result in enriched and refined action processing.

Cross-task perceptual learning of object recognition in simulated retinal implant perception

The perception gained by retina implants (RI) is limited, which asks for a learning regime to improve patients' visual perception. Here we simulated RI vision and investigated if object recognition in RI patients can be improved and maintained through training. Importantly, we asked if the trained object recognition can be generalized to a new task context, and to new viewpoints of the trained objects. For this purpose, we adopted two training tasks, a labelling task where participants had to choose the correct label out of other distracting labels for the presented object, and a reverse labelling task where participants had to choose the correct object out of other distracting objects to match the presented label. Our results showed that, despite of the task order, recognition performance was improved in both tasks and lasted at least for a week. The improved object recognition, however, can be transferred only from the labelling task to the reverse labelling task but not vice versa. Additionally, the trained object recognition can be transferred to new viewpoints of the trained objects only in the labelling task but not in the reverse labelling task. Training with the labelling task is therefore recommended for RI patients to achieve persistent and flexible visual perception.

High-resolution Functional Magnetic Resonance Imaging Reveals Configural Processing of Cars in Right Anterior Fusiform Face Area of Car Experts

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.

Hemispheric asymmetry in holistic processing of words

Holistic processing has been regarded as a hallmark of face perception, indicating the automatic and obligatory tendency of the visual system to process all face parts as a perceptual unit rather than in isolation. Studies involving lateralized stimulus presentation suggest that the right hemisphere dominates holistic face processing. Holistic processing can also be shown with other categories such as words and thus it is not specific to faces or face-like expertize. Here, we used divided visual field presentation to investigate the possibly different contributions of the two hemispheres for holistic word processing. Observers performed same/different judgment on the cued parts of two sequentially presented words in the complete composite paradigm. Our data indicate a right hemisphere specialization for holistic word processing. Thus, these markers of expert object recognition are domain general.

How holistic processing of faces relates to cognitive control and intelligence

The Vanderbilt Holistic Processing Test for faces (VHPT-F) is the first standard test designed to measure individual differences in holistic processing. The test measures failures of selective attention to face parts through congruency effects, an operational definition of holistic processing. However, this conception of holistic processing has been challenged by the suggestion that it may tap into the same selective attention or cognitive control mechanisms that yield congruency effects in Stroop and Flanker paradigms. Here, we report data from 130 subjects on the VHPT-F, several versions of Stroop and Flanker tasks, as well as fluid IQ. Results suggested a small degree of shared variance in Stroop and Flanker congruency effects, which did not relate to congruency effects on the VHPT-F. Variability on the VHPT-F was also not correlated with Fluid IQ. In sum, we find no evidence that holistic face processing as measured by congruency in the VHPT-F is accounted for by domain-general control mechanisms.

Domain-general and domain-specific neural changes underlying visual expertise

Visual expertise induces changes in neural processing for many different domains of expertise. However, it is unclear how expertise effects for different domains of expertise are related. In the present fMRI study, we combine large-scale univariate and multi-voxel analyses to contrast the expertise-related neural changes associated with two different domains of expertise, bird expertise (ornithology) and mineral expertise (mineralogy). Results indicated distributed expertise-related neural changes, with effects for both domains of expertise in high-level visual cortex and effects for bird expertise even extending to low-level visual regions and the frontal lobe. Importantly, a multivariate generalization analysis showed that effects in high-level visual cortex were specific to the domain of expertise. In contrast, the neural changes in the frontal lobe relating to expertise showed significant generalization, signaling the presence of domain-independent expertise effects. In conclusion, expertise is related to a combination of domain-specific and domain-general changes in neural processing.

Preserved Expert Object Recognition in a Case of Visual Hemiagnosia

We examined a stroke patient (HWS) with a unilateral lesion of the right medial ventral visual stream, involving the right fusiform and parahippocampal gyri. In a number of object recognition tests with lateralized presentations of target stimuli, HWS showed significant symptoms of hemiagnosia with contralesional recognition deficits for everyday objects. We further explored the patient's capacities of visual expertise that were acquired before the current perceptual impairment became effective. We confronted him with objects he was an expert for already before stroke onset and compared this performance with the recognition of familiar everyday objects. HWS was able to identify significantly more of the specific (“expert”) than of the everyday objects on the affected contralesional side. This observation of better expert object recognition in visual hemiagnosia allows for several interpretations. The results may be caused by enhanced information processing for expert objects in the ventral system in the affected or the intact hemisphere. Expert knowledge could trigger top–down mechanisms supporting object recognition despite of impaired basic functions of object processing. More importantly, the current work demonstrates that top–down mechanisms of visual expertise influence object recognition at an early stage, probably before visual object information propagates to modules of higher object recognition. Because HWS showed a lesion to the fusiform gyrus and spared capacities of expert object recognition, the current study emphasizes possible contributions of areas outside the ventral stream to visual expertise.

Does Extensive Training at Individuating Novel Objects in Adulthood Lead to Visual Expertise? The Role of Facelikeness

Human adults have a rich visual experience thanks to seeing human faces since birth, which may contribute to the acquisition of perceptual processes that rapidly and automatically individuate faces. According to a generic visual expertise hypothesis, extensive experience with nonface objects may similarly lead to efficient processing of objects at the individual level. However, whether extensive training in adulthood leads to visual expertise remains debated. One key issue is the extent to which the acquisition of visual expertise depends on the resemblance of objects to faces in terms of the spatial configuration of parts. We therefore trained naive human adults to individuate a large set of novel parametric multipart objects. Critically, one group of participants trained with the objects in a "facelike" stimulus orientation, whereas a second group trained with the same objects but with the objects rotated 180° in the picture plane into a "nonfacelike" orientation. We used a fast periodic visual stimulation EEG protocol to objectively quantify participants' ability to discriminate untrained exemplars before and after training. EEG responses associated with the frequency of identity change in a fast stimulation sequence, which reflects rapid and automatic perceptual processes, were observed over lateral occipital sites for both groups before training. There was a significant, albeit small, increase in these responses after training but only for the facelike group and only to facelike stimuli. Our findings indicate that perceived facelikeness plays a role in visual expertise and highlight how the adult perceptual system exploits familiar spatial configurations when learning new object categories.

The Word Composite Effect Depends on Abstract Lexical Representations But Not Surface Features Like Case and Font

Prior studies have shown that words show a composite effect: When readers perform a same-different matching task on a target-part of a word, performance is affected by the irrelevant part, whose influence is severely reduced when the two parts are misaligned. However, the locus of this word composite effect is largely unknown. To enlighten it, in two experiments, Portuguese readers performed the composite task on letter strings: in Experiment 1, in written words varying in surface features (between-participants: courier, notera, alternating-cAsE), and in Experiment 2 in pseudowords. The word composite effect, signaled by a significant interaction between alignment of the two word parts and congruence between parts was found in the three conditions of Experiment 1, being unaffected by NoVeLtY of the configuration or by handwritten form. This effect seems to have a lexical locus, given that in Experiment 2 only the main effect of congruence between parts was significant and was not modulated by alignment. Indeed, the cross-experiment analysis showed that words presented stronger congruence effects than pseudowords only in the aligned condition, because when misaligned the whole lexical item configuration was disrupted. Therefore, the word composite effect strongly depends on abstract lexical representations, as it is unaffected by surface features and is specific to lexical items.

The Limited Impact of Exposure Duration on Holistic Word Processing

The current study explored the impact of stimuli exposure duration on holistic word processing measured by the complete composite paradigm (CPc paradigm). The participants were asked to match the cued target parts of two characters which were presented for either a long (600 ms) or a short duration (170 ms). They were also tested by two popular versions of the CPc paradigm: the “early-fixed” task where the attention cue was visible from the beginning of each trial at a fixed position, and the “delayed-random” task where the cue showed up after the study character at random locations. The holistic word effect, as indexed by the alignment × congruency interaction, was identified in both tasks and was unaffected by the stimuli duration in both tasks. Meanwhile, the “delayed-random” task did not bring about larger holistic word effect than the “early-fixed” task. These results suggest the exposure duration (from around 150 to 600 ms) has a limited impact on the holistic word effect, and have methodological implications for experiment designs in this field.

Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration

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].

Spatial attention does not modulate holistic face processing, even when multiple faces are present

The perception of faces is often considered to be unique in comparison with that of other objects in the world. The fact that faces are processed not by their constituent components but by the spatial configuration between those components (holistic face processing--HFP) is often used to support this. Despite two decades of research, however, there is no consensus as to whether or not HFP is a process that is subject to attentional modulation. Here, in two experiments, we used a method to direct spatial attention not previously used in studies of HFP--an exogenous spatial cue--as it offers a robust, rapid, and involuntary method of directing attention. In one experiment we demonstrate that the degree of HFP afforded to a face is not reduced when attention is directed away from that face. In a second experiment we replicate this finding even when the face is simultaneously flanked by other faces--a condition under which a face-specific processing module would, hypothetically, be more sensitive to attentional guidance. These results add to the argument that HFP is carried out independently of attention.

Electrical stimulation over bilateral occipito-temporal regions reduces N170 in the right hemisphere and the composite face effect

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that can modulate cortical excitability. Although the clinical value of tDCS has been advocated, the potential of tDCS in cognitive rehabilitation of face processing deficits is less understood. Face processing has been associated with the occipito-temporal cortex (OT). The present study investigated whether face processing in healthy adults can be modulated by applying tDCS over the OT. Experiment 1 investigated whether tDCS can affect N170, a face-sensitive ERP component, with a face orientation judgment task. The N170 in the right hemisphere was reduced in active stimulation conditions compared with the sham stimulation condition for both upright faces and inverted faces. Experiment 2 further demonstrated that tDCS can modulate the composite face effect, a type of holistic processing that reflects the obligatory attention to all parts of a face. The composite face effect was reduced in active stimulation conditions compared with the sham stimulation condition. Additionally, the current polarity did not modulate the effect of tDCS in the two experiments. The present study demonstrates that N170 can be causally manipulated by stimulating the OT with weak currents. Furthermore, our study provides evidence that obligatory attention to all parts of a face can be affected by the commonly used tDCS parameter setting.

New insights in the limbic modulation of visual inputs: the role of the inferior longitudinal fasciculus and the Li-Am bundle

Recent anatomical and DTI data demonstrated new aspects in the subcortical occipito-temporal connections. Although a direct (inferior longitudinal fasciculus, ILF) pathway has been previously described, its fine description is still matter of debate. Moreover, a fast and direct subcortical connection between the limbic system and the occipital lobe has been previously recognized in many functional studies but it still remains poorly documented by anatomical images. We provided for the first time an extensive and detailed anatomical description of the ILF subcortical segmentation. We dissected four human hemispheres with modified Klingler's technique, from the basal to the lateral occipito-temporal surface in the two steps, tracking the ILF fibers until their cortical termination. Pictures of this direct temporo-occipital pathway are discussed in the light of recent literature regarding anatomy and functions of occipito-temporal areas. The dissection confirmed the classical originating branches of ILF and allowed a fine description of two main subcomponent of this bundle, both characterized by separate hierarchical distribution: a dorsal ILF and a ventral ILF. Moreover, a direct pathway between lingual cortex and amygdala, not previously demonstrated, is here described with anatomical images. Even if preliminary in results, this is the first fine description of ILF's subcomponents. The complex but clearly segregated organization of the fibers of this bundle (dILF and vILF) supports different level of functions mediated by visual recognition. Moreover, the newly described direct pathway from lingual to amygdala (Li-Am), seems involved in the limbic modulation of visual processing, so it may support physiological conditions the crucial role of this connection in human social cognition. In pathological conditions, on the other hand, this may be one of the hyperactivated pathways in temporo-occipital epileptic and nonepileptic syndromes.

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. The low load condition revealed several areas more active as a function of expertise, including both posterior and anterior portions of FFA bilaterally (FFA1/FFA2, respectively). Under high load, fewer areas were positively correlated with expertise and several areas were even negatively correlated, but the expertise effect in face-selective voxels in the anterior portion of FFA (FFA2) remained robust. Finally, we found that behavioral car expertise also predicted increased responses to sofa images but no behavioral advantages in sofa discrimination, suggesting that global shape similarity to a category of expertise is enough to elicit a response in FFA and other areas sensitive to experience, even when the category itself is not of special interest. The robustness of expertise effects in right FFA2 and the expertise effects driven by visual similarity both argue against attention being the sole determinant of expertise effects in extrastriate areas.

Studying real-world perceptual expertise

Significant insights into visual cognition have come from studying real-world perceptual expertise. Many have previously reviewed empirical findings and theoretical developments from this work. Here we instead provide a brief perspective on approaches, considerations, and challenges to studying real-world perceptual expertise. We discuss factors like choosing to use real-world versus artificial object domains of expertise, selecting a target domain of real-world perceptual expertise, recruiting experts, evaluating their level of expertise, and experimentally testing experts in the lab and online. Throughout our perspective, we highlight expert birding (also called birdwatching) as an example, as it has been used as a target domain for over two decades in the perceptual expertise literature.

A meta-analysis and review of holistic face processing

The concept of holistic processing is a cornerstone of face recognition research, yet central questions related to holistic processing remain unanswered, and debates have thus far failed to reach a resolution despite accumulating empirical evidence. We argue that a considerable source of confusion in this literature stems from a methodological problem. Specifically, 2 measures of holistic processing based on the composite paradigm (complete design and partial design) are used in the literature, but they often lead to qualitatively different results. First, we present a comprehensive review of the work that directly compares the 2 designs, and which clearly favors the complete design over the partial design. Second, we report a meta-analysis of holistic face processing according to both designs and use this as further evidence for one design over the other. The meta-analysis effect size of holistic processing in the complete design is nearly 3 times that of the partial design. Effect sizes were not correlated between measures, consistent with the suggestion that they do not measure the same thing. Our meta-analysis also examines the correlation between conditions in the complete design of the composite task, and suggests that in an individual differences context, little is gained by including a misaligned baseline. Finally, we offer a comprehensive review of the state of knowledge about holistic processing based on evidence gathered from the measure we favor based on the 1st sections of our review-the complete design-and outline outstanding research questions in that new context.

The perceptual effects of learning object categories that predict perceptual goals

In classic category learning studies, subjects typically learn to assign items to 1 of 2 categories, with no further distinction between how items on each side of the category boundary should be treated. In real life, however, we often learn categories that dictate further processing goals, for instance, with objects in only 1 category requiring further individuation. Using methods from category learning and perceptual expertise, we studied the perceptual consequences of experience with objects in tasks that rely on attention to different dimensions in different parts of the space. In 2 experiments, subjects first learned to categorize complex objects from a single morphspace into 2 categories based on 1 morph dimension, and then learned to perform a different task, either naming or a local feature judgment, for each of the 2 categories. A same-different discrimination test before and after each training measured sensitivity to feature dimensions of the space. After initial categorization, sensitivity increased along the category-diagnostic dimension. After task association, sensitivity increased more for the category that was named, especially along the nondiagnostic dimension. The results demonstrate that local attentional weights, associated with individual exemplars as a function of task requirements, can have lasting effects on perceptual representations.

Perceptual expertise and top-down expectation of musical notation engages the primary visual cortex

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.

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., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions.

Unsupervised learning of facial emotion decoding skills

Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practice without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear, and sadness) was shown in each clip. Although no external information about the correctness of the participant’s response or the sender’s true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple visual stimuli described in previous studies and practice effects often observed in cognitive tasks.

Beyond perceptual expertise: revisiting the neural substrates of expert object recognition

Real-world expertise provides a valuable opportunity to understand how experience shapes human behavior and neural function. In the visual domain, the study of expert object recognition, such as in car enthusiasts or bird watchers, has produced a large, growing, and often-controversial literature. Here, we synthesize this literature, focusing primarily on results from functional brain imaging, and propose an interactive framework that incorporates the impact of high-level factors, such as attention and conceptual knowledge, in supporting expertise. This framework contrasts with the perceptual view of object expertise that has concentrated largely on stimulus-driven processing in visual cortex. One prominent version of this perceptual account has almost exclusively focused on the relation of expertise to face processing and, in terms of the neural substrates, has centered on face-selective cortical regions such as the Fusiform Face Area (FFA). We discuss the limitations of this face-centric approach as well as the more general perceptual view, and highlight that expert related activity is: (i) found throughout visual cortex, not just FFA, with a strong relationship between neural response and behavioral expertise even in the earliest stages of visual processing, (ii) found outside visual cortex in areas such as parietal and prefrontal cortices, and (iii) modulated by the attentional engagement of the observer suggesting that it is neither automatic nor driven solely by stimulus properties. These findings strongly support a framework in which object expertise emerges from extensive interactions within and between the visual system and other cognitive systems, resulting in widespread, distributed patterns of expertise-related activity across the entire cortex.

The neural correlates of reading fluency deficits in children

Multiple studies have shown that individuals with a reading disability (RD) demonstrate deficits in posterior left-hemispheric brain regions during reading-related tasks. These studies mainly focused on reading sub-skills, and it remains debated whether such dysfunction is apparent during more ecologically valid reading skills, such as reading fluency. In this fMRI study, reading fluency was systematically varied to characterize neural correlates of reading fluency in 30 children with (RD) and without (typical developing children, TYP) a RD. Sentences were presented at constrained, comfortable, and accelerated speeds, which were determined based on individual reading speed. Behaviorally, RD children displayed decreased performance in several reading-related tasks. Using fMRI, we demonstrated that both TYP and RD children display increased activation in several components of the reading network during fluent reading. When required to read at an accelerated speed, RD children exhibited less activation in the fusiform gyrus (FG) compared with the TYP children. A region of interest analysis substantiated differences in the FG and demonstrated a relationship to behavioral reading performance. These results suggest that the FG plays a key role in fluent reading and that it can be modulated by speed. These results and their implications for remediation strategies should be considered in educational practice.

Visual category learning

Visual categories group together different objects as the same kinds of thing. We review a selection of research on how visual categories are learned. We begin with a guide to visual category learning experiments, describing a space of common manipulations of objects, categories, and methods used in the category learning literature. We open with a guide to these details in part because throughout our review we highlight how methodological details can sometimes loom large in theoretical discussions of visual category learning, how variations in methodological details can significantly affect our understanding of visual category learning, and how manipulations of methodological details can affect how visual categories are learned. We review a number of core theories of visual category learning, specifically those theories instantiated as computational models, highlighting just some of the experimental results that help distinguish between competing models. We examine behavioral and neural evidence for single versus multiple representational systems for visual category learning. We briefly discuss how visual category learning influences visual perception, describing empirical and brain imaging results that show how learning to categorize objects can influence how those objects are represented and perceived. We close with work that can potentially impact translation, describing recent experiments that explicitly manipulate key methodological details of category learning procedures with the goal of optimizing visual category learning. WIREs Cogn Sci 2014, 5:75-94. doi: 10.1002/wcs.1268 CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Comparing visual representations across human fMRI and computational vision

Feedforward visual object perception recruits a cortical network that is assumed to be hierarchical, progressing from basic visual features to complete object representations. However, the nature of the intermediate features related to this transformation remains poorly understood. Here, we explore how well different computer vision recognition models account for neural object encoding across the human cortical visual pathway as measured using fMRI. These neural data, collected during the viewing of 60 images of real-world objects, were analyzed with a searchlight procedure as in Kriegeskorte, Goebel, and Bandettini (2006): Within each searchlight sphere, the obtained patterns of neural activity for all 60 objects were compared to model responses for each computer recognition algorithm using representational dissimilarity analysis (Kriegeskorte et al., 2008). Although each of the computer vision methods significantly accounted for some of the neural data, among the different models, the scale invariant feature transform (Lowe, 2004), encoding local visual properties gathered from "interest points," was best able to accurately and consistently account for stimulus representations within the ventral pathway. More generally, when present, significance was observed in regions of the ventral-temporal cortex associated with intermediate-level object perception. Differences in model effectiveness and the neural location of significant matches may be attributable to the fact that each model implements a different featural basis for representing objects (e.g., more holistic or more parts-based). Overall, we conclude that well-known computer vision recognition systems may serve as viable proxies for theories of intermediate visual object representation.

Toward a unified model of face and object recognition in the human visual system

Our understanding of the mechanisms and neural substrates underlying visual recognition has made considerable progress over the past 30 years. During this period, accumulating evidence has led many scientists to conclude that objects and faces are recognised in fundamentally distinct ways, and in fundamentally distinct cortical areas. In the psychological literature, in particular, this dissociation has led to a palpable disconnect between theories of how we process and represent the two classes of object. This paper follows a trend in part of the recognition literature to try to reconcile what we know about these two forms of recognition by considering the effects of learning. Taking a widely accepted, self-organizing model of object recognition, this paper explains how such a system is affected by repeated exposure to specific stimulus classes. In so doing, it explains how many aspects of recognition generally regarded as unusual to faces (holistic processing, configural processing, sensitivity to inversion, the other-race effect, the prototype effect, etc.) are emergent properties of category-specific learning within such a system. Overall, the paper describes how a single model of recognition learning can and does produce the seemingly very different types of representation associated with faces and objects.

When Intuition Fails to Align with Data: A Reply to

Holistic processing, a hallmark of face perception, is often measured in the so-called composite paradigm, in which participants are asked to match part of a stimulus while ignoring another part. In prior work, we recommended against the use of one version of the composite task we call the partial design, on the basis of confounds with response biases. Rossion wrote a lengthy piece that reviews the work that he has published using this design, raising a large number of criticisms, both about an alternative measure of holistic processing that we have used and advocated (which we call the complete design) and about our work in general. In this reply, we have limited our discussion to those issues that would be relevant to a researcher looking to decide which version of this composite paradigm to use, as we doubt a comprehensive reply would be of significant interest outside a very small circle.

Meanings, mechanisms, and measures of holistic processing

Few concepts are more central to the study of face recognition than holistic processing. Progress toward understanding holistic processing is challenging because the term “holistic” has many meanings, with different researchers addressing different mechanisms and favoring different measures. While in principle the use of different measures should provide converging evidence for a common theoretical construct, convergence has been slow to emerge. We explore why this is the case. One challenge is that “holistic processing” is often used to describe both a theoretical construct and a measured effect, which may not have a one-to-one mapping. Progress requires more than greater precision in terminology regarding different measures of holistic processing or different hypothesized mechanisms of holistic processing. Researchers also need to be explicit about what meaning of holistic processing they are investigating so that it is clear whether different researchers are describing the same phenomenon or not. Face recognition differs from object recognition, and not all meanings of holistic processing are equally suited to help us understand that important difference.

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. (2006) Nat Neurosci 9:1177-1185] and neurophysiology in face patches in the monkey brain [Tsao DY, et al. (2006) Science 311:670-674] reveal no reliable selectivity for objects. It is thus possible that FFA responses to objects with SR-fMRI are a result of spatial blurring of responses from nonface-selective areas, potentially driven by attention to objects of expertise. Using HR-fMRI in two experiments, we provide evidence of reliable responses to cars in the FFA that correlate with behavioral car expertise. Effects of expertise in the FFA for nonface objects cannot be attributed to spatial blurring beyond the scale at which modular claims have been made, and within the lateral fusiform gyrus, they are restricted to a small area (200 mm(2) on the right and 50 mm(2) on the left) centered on the peak of face selectivity. Experience with a category may be sufficient to explain the spatially clustered face selectivity observed in this region.

Invariant object recognition based on extended fragments

Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called "digital embryos." Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI) of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination), and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition.