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Many of the objects we encounter in our everyday environments would be hard to recognize without any expectations about these objects. For example, a distant silhouette may be perceived as a car because we expect objects of that size, positioned on a road, to be cars. Reflecting the influence of such expectations on visual processing, neuroimaging studies have shown that when objects are poorly visible, expectations derived from scene context facilitate the representations of these objects in visual cortex from around 300 ms after scene onset. The current magnetoencephalography (MEG) study tested whether this facilitation occurs independently of attention and task relevance. Participants viewed degraded objects alone or within scene context while they either attended the scenes (attended condition) or the fixation cross (unattended condition), also temporally directing attention away from the scenes. Results showed that at 300 ms after stimulus onset, multivariate classifiers trained to distinguish clearly visible animate vs inanimate objects generalized to distinguish degraded objects in scenes better than degraded objects alone, despite the added clutter of the scene background. Attention also modulated object representations at this latency, with better category decoding in the attended than the unattended condition. The modulatory effects of context and attention were independent of each other. Finally, data from the current study and a previous study were combined (N = 51) to provide a more detailed temporal characterization of contextual facilitation. These results extend previous work by showing that facilitatory scene-object interactions are independent of the specific task performed on the visual input., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

As our viewpoint changes, the whole scene around us rotates coherently. This allows us to predict how one part of a scene (e.g., an object) will change by observing other parts (e.g., the scene background). While human object perception is known to be strongly context-dependent, previous research has largely focused on how scene context can disambiguate fixed object properties, such as identity (e.g., a car is easier to recognize on a road than on a beach). It remains an open question whether object representations are updated dynamically based on the surrounding scene context, for example across changes in viewpoint. Here, we tested whether human observers dynamically and automatically predict the appearance of objects based on the orientation of the background scene. In three behavioral experiments (N = 152), we temporarily occluded objects within scenes that rotated. Upon the objects' reappearance, participants had to perform a perceptual discrimination task, which did not require taking the scene rotation into account. Performance on this orthogonal task strongly depended on whether objects reappeared rotated coherently with the surrounding scene or not. This effect persisted even when a majority of trials violated this real-world contingency between scene and object, showcasing the automaticity of these scene-based predictions. These findings indicate that contextual information plays an important role in predicting object transformations in structured real-world environments., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Visual search is supported by an internal representation of the target, the attentional template. However, which features are diagnostic of target presence critically depends on the distractors. Accordingly, previous research showed that consistent distractor context shapes the attentional template for simple targets, with the template emphasizing diagnostic dimensions (e.g., color or orientation) in blocks of trials. Here, we investigated how distractor expectations bias attentional templates for complex shapes, and tested whether such biases reflect intertrial priming or can be instantiated flexibly. Participants searched for novel shapes (cued by name) in two probabilistic distractor contexts: Either the target's orientation or rectilinearity was unique (80% validity). Across four experiments, performance was better when the distractor context was expected, indicating that target features in the expected diagnostic dimension were emphasized. Attentional templates were biased by distractor expectations when distractor context was blocked, also for participants reporting no awareness of the manipulation. Interestingly, attentional templates were also biased when distractor context was cued on a trial-by-trial basis, but only when the two contexts were consistently presented at distinct spatial locations. These results show that attentional templates can flexibly and adaptively incorporate expectations about target-distractor relations when looking for the same object in different contexts. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The human brain is capable of using statistical regularities to predict future inputs. In the real world, such inputs typically comprise a collection of objects (e.g. a forest constitutes numerous trees). The present study aimed to investigate whether perceptual anticipation relies on lower-level or higher-level information. Specifically, we examined whether the human brain anticipates each object in a scene individually or anticipates the scene as a whole. To explore this issue, we first trained participants to associate co-occurring objects within fixed spatial arrangements. Meanwhile, participants implicitly learned temporal regularities between these displays. We then tested how spatial and temporal violations of the structure modulated behavior and neural activity in the visual system using fMRI. We found that participants only showed a behavioral advantage of temporal regularities when the displays conformed to their previously learned spatial structure, demonstrating that humans form configuration-specific temporal expectations instead of predicting individual objects. Similarly, we found suppression of neural responses for temporally expected compared with temporally unexpected objects in lateral occipital cortex only when the objects were embedded within expected configurations. Overall, our findings indicate that humans form expectations about object configurations, demonstrating the prioritization of higher-level over lower-level information in temporal expectation., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under these conditions when objects are seen within their typical scene context. What are the neural mechanisms of context-based object recognition? According to parallel processing accounts, context-based object recognition is supported by the parallel processing of object and scene information in separate pathways. Output of these pathways is then combined in downstream regions, leading to contextual benefits in object recognition. Alternatively, according to feedback accounts, context-based object recognition is supported by (direct or indirect) feedback from scene-selective to object-selective regions. Here, in three pre-registered transcranial magnetic stimulation (TMS) experiments, we tested a key prediction of the feedback hypothesis: that scene-selective cortex causally and selectively supports context-based object recognition before object-selective cortex does. Early visual cortex (EVC), object-selective lateral occipital cortex (LOC), and scene-selective occipital place area (OPA) were stimulated at three time points relative to stimulus onset while participants categorized degraded objects in scenes and intact objects in isolation, in different trials. Results confirmed our predictions: relative to isolated object recognition, context-based object recognition was selectively and causally supported by OPA at 160-200 ms after onset, followed by LOC at 260-300 ms after onset. These results indicate that context-based expectations facilitate object recognition by disambiguating object representations in the visual cortex., Competing Interests: MW No competing interests declared, MP Reviewing editor, eLife, (© 2021, Wischnewski and Peelen.)

Sounds (e.g., barking) help us to visually identify objects (e.g., a dog) that are distant or ambiguous. While neuroimaging studies have revealed neuroanatomical sites of audiovisual interactions, little is known about the time course by which sounds facilitate visual object processing. Here we used magnetoencephalography to reveal the time course of the facilitatory influence of natural sounds (e.g., barking) on visual object processing and compared this to the facilitatory influence of spoken words (e.g., "dog"). Participants viewed images of blurred objects preceded by a task-irrelevant natural sound, a spoken word, or uninformative noise. A classifier was trained to discriminate multivariate sensor patterns evoked by animate and inanimate intact objects with no sounds, presented in a separate experiment, and tested on sensor patterns evoked by the blurred objects in the 3 auditory conditions. Results revealed that both sounds and words, relative to uninformative noise, significantly facilitated visual object category decoding between 300-500 ms after visual onset. We found no evidence for earlier facilitation by sounds than by words. These findings provide evidence for a semantic route of facilitation by both natural sounds and spoken words, whereby the auditory input first activates semantic object representations, which then modulate the visual processing of objects., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In daily life, attention is often directed to high-level object attributes, such as when we look out for cars before crossing a road. Previous work used MEG decoding to investigate the influence of such category-based attention on the time course of object category representations. Attended object categories were more strongly represented than unattended categories from 180 msec after scene onset. In the present study, we used a similar approach to determine when attention is spatially focused on the target. Participants completed two tasks. In the first, they detected cars and people at varying locations in photographs of real-world scenes. In the second, they detected a cross that appeared at salient locations in an array of lines. Multivariate classifiers were trained on data of the artificial salience experiment and tested on data of the naturalistic visual search experiment. Results showed that the location of both target and distracter objects could be accurately decoded shortly after scene onset (50 msec). However, the emergence of spatial attentional selection - reflected in better decoding of target location than distracter location - emerged only later in time (240 msec). Target presence itself (irrespective of location and category) could be decoded from 180 msec after stimulus onset. Combined with earlier work, these results suggest that naturalistic category search operates through an initial spatially-global modulation of category processing that then guides attention to the location of the target., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

When searching for relevant objects in our environment (say, an apple), we create a memory template (a red sphere), which causes our visual system to favor template-matching visual input (applelike objects) at the expense of template-mismatching visual input (e.g., leaves). Although this principle seems straightforward in a lab setting, it poses a problem in naturalistic viewing: Two objects that have the same size on the retina will differ in real-world size if one is nearby and the other is far away. Using the Ponzo illusion to manipulate perceived size while keeping retinal size constant, we demonstrated across 71 participants that visual objects attract attention when their perceived size matches a memory template, compared with mismatching objects that have the same size on the retina. This shows that memory templates affect visual selection after object representations are modulated by scene context, thus providing a working mechanism for template-based search in naturalistic vision.

The principles underlying the animacy organization of the ventral temporal cortex (VTC) remain hotly debated, with recent evidence pointing to an animacy continuum rather than a dichotomy. What drives this continuum? According to the visual categorization hypothesis, the continuum reflects the degree to which animals contain animal-diagnostic features. By contrast, the agency hypothesis posits that the continuum reflects the degree to which animals are perceived as (social) agents. Here, we tested both hypotheses with a stimulus set in which visual categorizability and agency were dissociated based on representations in convolutional neural networks and behavioral experiments. Using fMRI, we found that visual categorizability and agency explained independent components of the animacy continuum in VTC. Modeled together, they fully explained the animacy continuum. Finally, clusters explained by visual categorizability were localized posterior to clusters explained by agency. These results show that multiple organizing principles, including agency, underlie the animacy continuum in VTC., Competing Interests: ST, DP, MP No competing interests declared, (© 2019, Thorat et al.)

Human high-level visual cortex shows a distinction between animate and inanimate objects, as revealed by fMRI. Recent studies have shown that object animacy can similarly be decoded from MEG sensor patterns. Which object properties drive this decoding? Here, we disentangled the influence of perceptual and categorical object properties by presenting perceptually matched objects (e.g., snake and rope) that were nonetheless easily recognizable as being animate or inanimate. In a series of behavioral experiments, three aspects of perceptual dissimilarity of these objects were quantified: overall dissimilarity, outline dissimilarity, and texture dissimilarity. Neural dissimilarity of MEG sensor patterns was modeled using regression analysis, in which perceptual dissimilarity (from the behavioral experiments) and categorical dissimilarity served as predictors of neural dissimilarity. We found that perceptual dissimilarity was strongly reflected in MEG sensor patterns from 80 ms after stimulus onset, with separable contributions of outline and texture dissimilarity. Surprisingly, when controlling for perceptual dissimilarity, MEG patterns did not carry information about object category (animate vs inanimate) at any time point. Nearly identical results were found in a second MEG experiment that required basic-level object recognition. This is in contrast to results observed in fMRI using the same stimuli, task, and analysis approach: fMRI voxel patterns in object-selective cortex showed a highly reliable categorical distinction even when controlling for perceptual dissimilarity. These results suggest that MEG sensor patterns do not capture object animacy independently of perceptual differences between animate and inanimate objects., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Scene context is known to facilitate object recognition in both machines and humans, suggesting that the underlying representations may be similar. Alternatively, they may be qualitatively different since the training experience of machines and humans are strikingly different. Machines are typically trained on images containing objects and their context, whereas humans frequently experience scenes without objects (such as highways without cars). If these context representations are indeed different, machine vision algorithms will be improved on augmenting them with human context representations, provided these expectations can be measured and are systematic. Here, we developed a paradigm to measure human contextual expectations. We asked human subjects to indicate the scale, location and likelihood at which cars or people might occur in scenes without these objects. This yielded highly systematic expectations that we could then accurately predict using scene features. This allowed us to predict human expectations on novel scenes without requiring explicit measurements. Next we augmented decisions made by deep neural networks with these predicted human expectations and obtained substantial gains in accuracy for detecting cars and people (1-3%) as well as on detecting associated objects (3-20%). In contrast, augmenting deep network decisions with other conventional computer vision features yielded far smaller gains. Taken together, our results show that augmenting deep neural networks with human-derived contextual expectations improves their performance, suggesting that contextual representations are qualitatively different in humans and deep neural networks.

Understanding other people's actions and mental states includes the interpretation of body postures and movements. In particular, hand postures are an important channel to signal both action and communicative intentions. Recognizing hand postures is computationally challenging because hand postures often differ only in the subtle configuration of relative finger positions and because visual characteristics of hand postures change across viewpoints. To allow for accurate interpretation, the brain needs to represent hand postures in a view-invariant but posture-specific manner. Here we test for such representations in hand-, body-, and object-selective regions of the lateral occipitotemporal cortex (LOTC). We used multivariate pattern analysis of fMRI data to test for view-specific and view-invariant representations of individual hand postures, separately for two domains: action-related postures (e.g., a precision grasp) and communicative postures (e.g., thumbs up). Results showed that hand-selective LOTC, but not nearby body- and object-selective LOTC, represented hand postures in a view-invariant manner, with relatively similar activity patterns to the same hand posture seen from different viewpoints. View invariance was equally strong for action and communicative postures. By contrast, object-selective cortex represented hand postures in a view-specific manner. These results indicate a role for hand-selective LOTC in solving the view-invariance problem for individual hand postures. View-invariant representations of hand postures in this region may then be accessed and further interpreted by multiple downstream systems to inform high-level judgments related to action understanding, emotion recognition, and non-verbal communication., (Copyright © 2018. Published by Elsevier Inc.)

To optimize processing, the human visual system utilizes regularities present in naturalistic visual input. One of these regularities is the relative position of objects in a scene (e.g., a sofa in front of a television), with behavioral research showing that regularly positioned objects are easier to perceive and to remember. Here we use fMRI to test how positional regularities are encoded in the visual system. Participants viewed pairs of objects that formed minimalistic two-object scenes (e.g., a "living room" consisting of a sofa and television) presented in their regularly experienced spatial arrangement or in an irregular arrangement (with interchanged positions). Additionally, single objects were presented centrally and in isolation. Multi-voxel activity patterns evoked by the object pairs were modeled as the average of the response patterns evoked by the two single objects forming the pair. In two experiments, this approximation in object-selective cortex was significantly less accurate for the regularly than the irregularly positioned pairs, indicating integration of individual object representations. More detailed analysis revealed a transition from independent to integrative coding along the posterior-anterior axis of the visual cortex, with the independent component (but not the integrative component) being almost perfectly predicted by object selectivity across the visual hierarchy. These results reveal a transitional stage between individual object and multi-object coding in visual cortex, providing a possible neural correlate of efficient processing of regularly positioned objects in natural scenes., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Humans excel at finding objects in complex natural scenes, but the features that guide this behaviour have proved elusive. We used computational modeling to measure the contributions of target, nontarget, and coarse scene features towards object detection in humans. In separate experiments, participants detected cars or people in a large set of natural scenes. For each scene, we extracted target-associated features, annotated the presence of nontarget objects (e.g., parking meter, traffic light), and extracted coarse scene structure from the blurred image. These scene-specific values were then used to model human reaction times for each novel scene. As expected, target features were the strongest predictor of detection times in both tasks. Interestingly, target detection time was additionally facilitated by coarse scene features but not by nontarget objects. In contrast, nontarget objects predicted target-absent responses in both person and car tasks, with contributions from target features in the person task. In most cases, features that speeded up detection tended to slow down rejection. Taken together, these findings demonstrate that humans show systematic variations in object detection that can be understood using computational modeling.

Scenes strongly facilitate object recognition, such as when we make out the shape of a distant boat on the water. Yet, although known to interact in perception, neuroimaging research has primarily provided evidence for separate scene- and object-selective cortical pathways. This raises the question of how these pathways interact to support context-based perception. Here we used a novel approach in human fMRI and MEG studies to reveal supra-additive scene-object interactions. Participants (men and women) viewed degraded objects that were hard to recognize when presented in isolation but easy to recognize within their original scene context, in which no other associated objects were present. fMRI decoding showed that the multivariate representation of the objects' category (animate/inanimate) in object-selective cortex was strongly enhanced by the presence of scene context, even though the scenes alone did not evoke category-selective response patterns. This effect in object-selective cortex was correlated with concurrent activity in scene-selective regions. MEG decoding results revealed that scene-based facilitation of object processing peaked at 320 ms after stimulus onset, 100 ms later than peak decoding of intact objects. Together, results suggest that expectations derived from scene information, processed in scene-selective cortex, feed back to shape object representations in visual cortex. These findings characterize, in space and time, functional interactions between scene- and object-processing pathways. SIGNIFICANCE STATEMENT Although scenes and objects are known to contextually interact in visual perception, the study of high-level vision has mostly focused on the dissociation between their selective neural pathways. The current findings are the first to reveal direct facilitation of object recognition and neural representation by scene background, even in the absence of contextually associated objects. Using a multivariate approach to both fMRI and MEG, we characterize the functional neuroanatomy and neural dynamics of such scene-based object facilitation. Finally, the correlation of this effect with scene-selective activity suggests that, although functionally distinct, scene and object processing pathways do interact at a perceptual level to fill in for insufficient visual detail., (Copyright © 2017 the authors 0270-6474/17/377700-11$15.00/0.)

Theories of reinforcement learning and approach behavior suggest that reward can increase the perceptual salience of environmental stimuli, ensuring that potential predictors of outcome are noticed in the future. However, outcome commonly follows visual processing of the environment, occurring even when potential reward cues have long disappeared. How can reward feedback retroactively cause now-absent stimuli to become attention-drawing in the future? One possibility is that reward and attention interact to prime lingering visual representations of attended stimuli that sustain through the interval separating stimulus and outcome. Here, we test this idea using multivariate pattern analysis of fMRI data collected from male and female humans. While in the scanner, participants searched for examples of target categories in briefly presented pictures of cityscapes and landscapes. Correct task performance was followed by reward feedback that could randomly have either high or low magnitude. Analysis showed that high-magnitude reward feedback boosted the lingering representation of target categories while reducing the representation of nontarget categories. The magnitude of this effect in each participant predicted the behavioral impact of reward on search performance in subsequent trials. Other analyses show that sensitivity to reward-as expressed in a personality questionnaire and in reactivity to reward feedback in the dopaminergic midbrain-predicted reward-elicited variance in lingering target and nontarget representations. Credit for rewarding outcome thus appears to be assigned to the target representation, causing the visual system to become sensitized for similar objects in the future. SIGNIFICANCE STATEMENT How do reward-predictive visual stimuli become salient and attention-drawing? In the real world, reward cues precede outcome and reward is commonly received long after potential predictors have disappeared. How can the representation of environmental stimuli be affected by outcome that occurs later in time? Here, we show that reward acts on lingering representations of environmental stimuli that sustain through the interval between stimulus and outcome. Using naturalistic scene stimuli and multivariate pattern analysis of fMRI data, we show that reward boosts the representation of attended objects and reduces the representation of unattended objects. This interaction of attention and reward processing acts to prime vision for stimuli that may serve to predict outcome., (Copyright © 2017 the authors 0270-6474/17/377297-08$15.00/0.)

Top-down attention is the mechanism that allows us to selectively process goal-relevant aspects of a scene while ignoring irrelevant aspects. A large body of research has characterized the effects of attention on neural activity evoked by a visual stimulus. However, attention also includes a preparatory phase before stimulus onset in which the attended dimension is internally represented. Here, we review neurophysiological, functional magnetic resonance imaging, magnetoencephalography, electroencephalography, and transcranial magnetic stimulation (TMS) studies investigating the neural basis of preparatory attention, both when attention is directed to a location in space and when it is directed to nonspatial stimulus attributes (content-based attention) ranging from low-level features to object categories. Results show that both spatial and content-based attention lead to increased baseline activity in neural populations that selectively code for the attended attribute. TMS studies provide evidence that this preparatory activity is causally related to subsequent attentional selection and behavioral performance. Attention thus acts by preactivating selective neurons in the visual cortex before stimulus onset. This appears to be a general mechanism that can operate on multiple levels of representation. We discuss the functional relevance of this mechanism, its limitations, and its relation to working memory, imagery, and expectation. We conclude by outlining open questions and future directions., (© 2017 New York Academy of Sciences.)

Humans are remarkably efficient in detecting highly familiar object categories in natural scenes, with evidence suggesting that such object detection can be performed in the (near) absence of attention. Here we systematically explored the influences of both spatial attention and category-based attention on the accuracy of object detection in natural scenes. Manipulating both types of attention additionally allowed for addressing how these factors interact: whether the requirement for spatial attention depends on the extent to which observers are prepared to detect a specific object category-that is, on category-based attention. The results showed that the detection of targets from one category (animals or vehicles) was better than the detection of targets from two categories (animals and vehicles), demonstrating the beneficial effect of category-based attention. This effect did not depend on the semantic congruency of the target object and the background scene, indicating that observers attended to visual features diagnostic of the foreground target objects from the cued category. Importantly, in three experiments the detection of objects in scenes presented in the periphery was significantly impaired when observers simultaneously performed an attentionally demanding task at fixation, showing that spatial attention affects natural scene perception. In all experiments, the effects of category-based attention and spatial attention on object detection performance were additive rather than interactive. Finally, neither spatial nor category-based attention influenced metacognitive ability for object detection performance. These findings demonstrate that efficient object detection in natural scenes is independently facilitated by spatial and category-based attention.

Famous places and famous people are different from their common counterparts in that we have unique knowledge about individual items, including specific knowledge about their visual appearance and other sensory properties. Previous studies have shown that the processing of unique entities selectively activates a network of brain regions that includes the bilateral anterior temporal lobes (ATL), posterior cingulate cortex and adjacent medial precuneus (PCC/medPrec), medial prefrontal cortex (medPFC), and temporal-parietal junction (TPJ). The degree to which these regions represent visual properties associated with famous people/places is unknown. Here we compared fMRI responses in congenitally and sighted individuals to test whether visual experience contributes to the development of unique-entity responses in these regions. Names of unique entities (famous places, famous people) and generic items (daily scenes such as "bridge", face parts) were presented aurally to 13 congenitally blind and 16 sighted participants. Sighted participants additionally viewed corresponding photographs. We found that bilateral PCC/medPrec, medPFC, left TPJ, left ATL and right superior frontal gyrus were more strongly activated by pictures of unique entities compared to generic items. Importantly, all regions showed similar selectivity for unique entities in both groups when only names were presented. Furthermore, resting-state functional connectivity analysis revealed that these regions were tightly interconnected in both groups. Together, these results provide evidence for a visually-independent brain network underlying unique entity processing., (Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Access to visual awareness for human faces is strongly influenced by spatial orientation: Under continuous flash suppression (CFS), upright faces break into awareness more quickly than inverted faces. This effect of inversion for faces is larger than for a wide range of other animate and inanimate objects. Here we asked whether this apparently specific sensitivity to upright faces reflects face-specific detection mechanisms or whether it reflects perceptual expertise more generally. We tested car experts who varied in their degree of car and face expertise and measured the time upright and inverted faces, cars, and chairs needed to overcome CFS and break into awareness. Results showed that greater car expertise was correlated with larger car inversion effects under CFS. A similar relation between better discrimination performance and larger CFS inversion effects was found for faces. CFS inversion effects are thus modulated by perceptual expertise for both faces and cars. These results demonstrate that inversion effects in conscious access are not unique to faces but similarly exist for other objects of expertise. More generally, we interpret these findings as suggesting that access to awareness and exemplar-level discrimination rely on partially shared perceptual mechanisms. (PsycINFO Database Record, ((c) 2016 APA, all rights reserved).)

Objects belonging to different categories evoke reliably different fMRI activity patterns in human occipitotemporal cortex, with the most prominent distinction being that between animate and inanimate objects. An unresolved question is whether these categorical distinctions reflect category-associated visual properties of objects or whether they genuinely reflect object category. Here, we addressed this question by measuring fMRI responses to animate and inanimate objects that were closely matched for shape and low-level visual features. Univariate contrasts revealed animate- and inanimate-preferring regions in ventral and lateral temporal cortex even for individually matched object pairs (e.g., snake-rope). Using representational similarity analysis, we mapped out brain regions in which the pairwise dissimilarity of multivoxel activity patterns (neural dissimilarity) was predicted by the objects' pairwise visual dissimilarity and/or their categorical dissimilarity. Visual dissimilarity was measured as the time it took participants to find a unique target among identical distractors in three visual search experiments, where we separately quantified overall dissimilarity, outline dissimilarity, and texture dissimilarity. All three visual dissimilarity structures predicted neural dissimilarity in regions of visual cortex. Interestingly, these analyses revealed several clusters in which categorical dissimilarity predicted neural dissimilarity after regressing out visual dissimilarity. Together, these results suggest that the animate-inanimate organization of human visual cortex is not fully explained by differences in the characteristic shape or texture properties of animals and inanimate objects. Instead, representations of visual object properties and object category may coexist in more anterior parts of the visual system.

Neuroimaging research has identified category-specific neural response patterns to a limited set of object categories. For example, faces, bodies, and scenes evoke activity patterns in visual cortex that are uniquely traceable in space and time. It is currently debated whether these apparently categorical responses truly reflect selectivity for categories or instead reflect selectivity for category-associated shape properties. In the present study, we used a cross-classification approach on functional MRI (fMRI) and magnetoencephalographic (MEG) data to reveal both category-independent shape responses and shape-independent category responses. Participants viewed human body parts (hands and torsos) and pieces of clothing that were closely shape-matched to the body parts (gloves and shirts). Category-independent shape responses were revealed by training multivariate classifiers on discriminating shape within one category (e.g., hands versus torsos) and testing these classifiers on discriminating shape within the other category (e.g., gloves versus shirts). This analysis revealed significant decoding in large clusters in visual cortex (fMRI) starting from 90 ms after stimulus onset (MEG). Shape-independent category responses were revealed by training classifiers on discriminating object category (bodies and clothes) within one shape (e.g., hands versus gloves) and testing these classifiers on discriminating category within the other shape (e.g., torsos versus shirts). This analysis revealed significant decoding in bilateral occipitotemporal cortex (fMRI) and from 130 to 200 ms after stimulus onset (MEG). Together, these findings provide evidence for concurrent shape and category selectivity in high-level visual cortex, including category-level responses that are not fully explicable by two-dimensional shape properties., (Copyright © 2016 the American Physiological Society.)

Perception of others' bodies provides information that is useful for a number of important social-cognitive processes. Evidence from neuroimaging methods has identified focal cortical regions that are highly selective for perceiving bodies and body parts, including the extrastriate body area (EBA) and fusiform body area (FBA). Our understanding of the functional properties of these regions, and their causal contributions to behavior, has benefitted from the study of neuropsychological patients and particularly from investigations using transcranial magnetic stimulation (TMS). We review this evidence, focusing on TMS studies that are revealing of how (and when) activity in EBA contributes to detecting people in natural scenes; to resolving their body shape, movements, actions, individual parts, and identities; and to guiding goal-directed behavior. These findings are considered in reference to a framework for body perception in which the patterns of neural activity in EBA and FBA jointly serve to make explicit the elements of the visual scene that correspond to the body and its parts. These representations are modulated by other sources of information such as prior knowledge, and are shared with wider brain networks involved in many aspects of social cognition., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The detectability of an object in our visual environment is primarily determined by the object's low-level visual salience, resulting from the physical characteristics of the object and its surroundings. In the present study we demonstrate that object detectability is additionally influenced by internally generated expectations about object properties, and that these influences are mediated by changes in perceptual sensitivity. Using continuous flash suppression (CFS) to render objects invisible, we found that providing valid information about the category membership of the object (e.g., "car") before stimulus presentation facilitated awareness of the object, as shown by improved localization performance relative to a noninformative baseline condition and to a condition with invalid prior information. Experiments 2 and 3 showed that the effect of expectation on detection generalized to binocular viewing conditions, with valid category cues facilitating the localization and detection of briefly presented objects. Experiment 4 extended these results to simple stimuli (oriented Gabor patches), for which valid orientation information improved localization performance. Finally, in Experiment 5 we found that the effect of expectation on detection and localization performance partly reflects increased perceptual sensitivity, as evidenced by decreased contrast detection thresholds for validly cued stimuli relative to noncued and invalidly cued stimuli. Together, these findings demonstrate that prior information about specific object properties dynamically enhances the effective signal of visual input matching the expected content, thereby biasing object detection in favor of expected objects., ((c) 2015 APA, all rights reserved).)

Theories of visual selective attention propose that top-down preparatory attention signals mediate the selection of task-relevant information in cluttered scenes. Neuroimaging and electrophysiology studies have provided correlative evidence for this hypothesis, finding increased activity in target-selective neural populations in visual cortex in the period between a search cue and target onset. In this study, we used online TMS to test whether preparatory neural activity in visual cortex is causally involved in naturalistic object detection. In two experiments, participants detected the presence of object categories (cars, people) in a diverse set of photographs of real-world scenes. TMS was applied over a region in posterior temporal cortex identified by fMRI as carrying category-specific preparatory activity patterns. Results showed that TMS applied over posterior temporal cortex before scene onset (-200 and -100 msec) impaired the detection of object categories in subsequently presented scenes, relative to vertex and early visual cortex stimulation. This effect was specific to category level detection and was related to the type of attentional template participants adopted, with the strongest effects observed in participants adopting category level templates. These results provide evidence for a causal role of preparatory attention in mediating the detection of objects in cluttered daily-life environments.

Regions in human lateral and ventral occipitotemporal cortices (OTC) respond selectively to pictures of the human body and its parts. What are the organizational principles underlying body part responses in these regions? Here we used representational similarity analysis (RSA) of fMRI data to test multiple possible organizational principles: shape similarity, physical proximity, cortical homunculus proximity, and semantic similarity. Participants viewed pictures of whole persons, chairs, and eight body parts (hands, arms, legs, feet, chests, waists, upper faces, and lower faces). The similarity of multivoxel activity patterns for all body part pairs was established in whole person-selective OTC regions. The resulting neural similarity matrices were then compared with similarity matrices capturing the hypothesized organizational principles. Results showed that the semantic similarity model best captured the neural similarity of body parts in lateral and ventral OTC, which followed an organization in three clusters: (1) body parts used as action effectors (hands, feet, arms, and legs), (2) noneffector body parts (chests and waists), and (3) face parts (upper and lower faces). Whole-brain RSA revealed, in addition to OTC, regions in parietal and frontal cortex in which neural similarity was related to semantic similarity. In contrast, neural similarity in occipital cortex was best predicted by shape similarity models. We suggest that the semantic organization of body parts in high-level visual cortex relates to the different functions associated with the three body part clusters, reflecting the unique processing and connectivity demands associated with the different types of information (e.g., action, social) different body parts (e.g., limbs, faces) convey. Significance statement: While the organization of body part representations in motor and somatosensory cortices has been well characterized, the principles underlying body part representations in visual cortex have not yet been explored. In the present fMRI study we used multivoxel pattern analysis and representational similarity analysis to characterize the organization of body maps in human occipitotemporal cortex (OTC). Results indicate that visual and shape dimensions do not fully account for the organization of body part representations in OTC. Instead, the representational structure of body maps in OTC appears strongly related to functional-semantic properties of body parts. We suggest that this organization reflects the unique processing and connectivity demands associated with the different types of information different body parts convey., (Copyright © 2015 the authors 0270-6474/15/3512977-09$15.00/0.)

Theories of visual search postulate that the selection of targets amongst distractors involves matching visual input to a top-down attentional template. Previous work has provided evidence that feature-based attentional templates affect visual processing globally across the visual field. In the present study, we asked whether more naturalistic, category-level attentional templates also modulate visual processing in a spatially global and obligatory way. Subjects were cued to detect people or cars in a diverse set of photographs of real-world scenes. On a subset of trials, silhouettes of people and cars appeared in search-irrelevant locations that subjects were instructed to ignore, and subjects were required to respond to the location of a subsequent dot probe. In three experiments, results showed a consistency effect on dot-probe trials: dot probes were detected faster when they appeared in the location of the cued category compared with the non-cued category, indicating attentional capture by template-matching stimuli. Experiments 1 and 2 showed that this capture was involuntary: consistency effects persisted under conditions in which attending to silhouettes of the cued category was detrimental to performance. Experiment 3 tested whether these effects could be attributed to non-attentional effects related to the processing of the category cues. Results showed a consistency effect when subjects searched for category exemplars but not when they searched for objects semantically related to the cued category. Together, these results indicate that attentional templates for familiar object categories affect visual processing across the visual field, leading to involuntary attentional capture by template-matching stimuli.

Reward is thought to motivate animal-approach behavior in part by automatically facilitating the perceptual processing of reward-associated visual stimuli. Studies have demonstrated this effect for low-level visual features such as color and orientation. However, outside of the laboratory, it is rare that low-level features uniquely characterize objects relevant for behavior. Here, we test whether reward can prime representations at the level of object category. Participants detected category exemplars (cars, trees, people) in briefly presented photographs of real-world scenes. On a subset of trials, successful target detection was rewarded and the effect of this reward was measured on the subsequent trial. Results show that rewarded selection of a category exemplar caused other members of this category to become visually salient, disrupting search when subsequently presented as distractors. It is important to note that this occurred even when there was little opportunity for the repetition of visual features between examples, with the rewarded selection of a human body increasing the salience of a subsequently presented face. Thus, selection of a category example appears to activate representations of prototypical category characteristics even when these are not present in the stimulus. In this way, reward can guide attention to categories of stimuli even when individual examples share no visual characteristics., ((c) 2015 APA, all rights reserved).)

In virtually every real-life situation humans are confronted with complex and cluttered visual environments that contain a multitude of objects. Because of the limited capacity of the visual system, objects compete for neural representation and cognitive processing resources. Previous work has shown that such attentional competition is partly object based, such that competition among elements is reduced when these elements perceptually group into an object based on low-level cues. Here, using functional MRI (fMRI) and behavioral measures, we show that the attentional benefit of grouping extends to higher-level grouping based on the relative position of objects as experienced in the real world. An fMRI study designed to measure competitive interactions among objects in human visual cortex revealed reduced neural competition between objects when these were presented in commonly experienced configurations, such as a lamp above a table, relative to the same objects presented in other configurations. In behavioral visual search studies, we then related this reduced neural competition to improved target detection when distracter objects were shown in regular configurations. Control studies showed that low-level grouping could not account for these results. We interpret these findings as reflecting the grouping of objects based on higher-level spatial-relational knowledge acquired through a lifetime of seeing objects in specific configurations. This interobject grouping effectively reduces the number of objects that compete for representation and thereby contributes to the efficiency of real-world perception.

Visual cues from the face and the body provide information about another's identity, emotional state, and intentions. Previous neuroimaging studies that investigated neural responses to (bodiless) faces and (headless) bodies have reported overlapping face- and body-selective brain regions in right fusiform gyrus (FG). In daily life, however, faces and bodies are typically perceived together and are effortlessly integrated into the percept of a whole person, raising the possibility that neural responses to whole persons are qualitatively different than responses to isolated faces and bodies. The present study used fMRI to examine how FG activity in response to a whole person relates to activity in response to the same face and body but presented in isolation. Using multivoxel pattern analysis, we modeled person-evoked response patterns in right FG through a linear combination of face- and body-evoked response patterns. We found that these synthetic patterns were able to accurately approximate the response patterns to whole persons, with face and body patterns each adding unique information to the response patterns evoked by whole person stimuli. These results suggest that whole person responses in FG primarily arise from the coactivation of independent face- and body-selective neural populations.

Knowledge of object shape is primarily acquired through the visual modality but can also be acquired through other sensory modalities. In the present study, we investigated the representation of object shape in humans without visual experience. Congenitally blind and sighted participants rated the shape similarity of pairs of 33 familiar objects, referred to by their names. The resulting shape similarity matrices were highly similar for the two groups, indicating that knowledge of the objects' shapes was largely independent of visual experience. Using fMRI, we tested for brain regions that represented object shape knowledge in blind and sighted participants. Multivoxel activity patterns were established for each of the 33 aurally presented object names. Sighted participants additionally viewed pictures of these objects. Using representational similarity analysis, neural similarity matrices were related to the behavioral shape similarity matrices. Results showed that activity patterns in occipitotemporal cortex (OTC) regions, including inferior temporal (IT) cortex and functionally defined object-selective cortex (OSC), reflected the behavioral shape similarity ratings in both blind and sighted groups, also when controlling for the objects' tactile and semantic similarity. Furthermore, neural similarity matrices of IT and OSC showed similarities across blind and sighted groups (within the auditory modality) and across modality (within the sighted group), but not across both modality and group (blind auditory-sighted visual). Together, these findings provide evidence that OTC not only represents objects visually (requiring visual experience) but also represents objects nonvisually, reflecting knowledge of object shape independently of the modality through which this knowledge was acquired.

The principles driving the functional organization of object representations in high-level visual cortex are not yet fully understood. In four human fMRI experiments, we provide evidence that the organization of high-level visual cortex partly reflects the degree to which objects are typically controlled by the body to interact with the world, thereby extending the body's boundaries. Univariate whole-brain analysis showed an overlap between responses to body effectors (e.g., hands, feet, and limbs) and object effectors (e.g., hammers, combs, and tennis rackets) in lateral occipitotemporal cortex (LOTC) and parietal cortex. Region of interest analyses showed that a hand-selective region in left LOTC responded selectively to object effectors relative to a range of noneffector object control conditions (e.g., graspable objects, "act-on" objects, musical instruments). Object ratings showed that the strong response to object effectors in hand-selective LOTC was not due to general action-related object properties shared with these control conditions, such as hand priming, hand grasping, and hand-action centrality. Finally, whole-brain representational similarity analysis revealed that the similarity of multivoxel object response patterns in left lateral occipitotemporal cortex selectively predicted the degree to which objects were rated as being controlled by and extending the body. Together, these results reveal a clustering of body and object effector representations, indicating that the organization of object representations in high-level visual cortex partly reflects how objects relate to the body.

The principles that determine the organization of object representations in ventral temporal cortex (VTC) remain elusive. Here, we focus on the parahippocampal place area (PPA), a region in medial VTC that has been shown to respond selectively to pictures of scenes. Recent studies further observed that this region also shows a preference for large nonmanipulable objects relative to other objects, which might reflect the suitability of large objects for navigation. The mechanisms underlying this selectivity remain poorly understood. We examined the extent to which PPA selectivity requires visual experience. Fourteen congenitally blind and matched sighted participants were tested on an auditory size judgment experiment involving large nonmanipulable objects, small objects (tools), and animals. Sighted participants additionally participated in a picture-viewing experiment. Replicating previous work, we found that the PPA responded selectively to large nonmanipulable objects, relative to tools and animals, in the sighted group viewing pictures. Importantly, this selectivity was also observed in the auditory experiment in both sighted and congenitally blind groups. In both groups, selectivity for large nonmanipulable objects was additionally observed in the retrosplenial complex (RSC) and the transverse occipital sulcus (TOS), regions previously implicated in scene perception and navigation. Finally, in both groups the PPA showed resting-state functional connectivity with TOS and RSC. These results provide new evidence that large object selectivity in PPA, and the intrinsic connectivity between PPA and other navigation-relevant regions, do not require visual experience. More generally, they show that the organization of object representations in VTC can develop, at least partly, without visual experience., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Visual search involves the matching of visual input to a "search template," an internal representation of task-relevant information. The present study investigated the contents of the search template during visual search for object categories in natural scenes, for which low-level features do not reliably distinguish targets from nontargets. Subjects were cued to detect people or cars in diverse photographs of real-world scenes. On a subset of trials, the cue was followed by task-irrelevant stimuli instead of scenes, directly followed by a dot that subjects were instructed to detect. We hypothesized that stimuli that matched the active search template would capture attention, resulting in faster detection of the dot when presented at the location of a template-matching stimulus. Results revealed that silhouettes of cars and people captured attention irrespective of their orientation (0°, 90°, or 180°). Interestingly, strong capture was observed for silhouettes of category-diagnostic object parts, such as the wheel of a car. Finally, attentional capture was also observed for silhouettes presented at locations that were irrelevant to the search task. Together, these results indicate that search for familiar object categories in real-world scenes is mediated by spatially global search templates that consist of view-invariant shape representations of category-diagnostic object parts.

Interaction with everyday objects requires the representation of conceptual object properties, such as where and how an object is used. What are the neural mechanisms that support this knowledge? While research on semantic dementia has provided evidence for a critical role of the anterior temporal lobes (ATLs) in object knowledge, fMRI studies using univariate analysis have primarily implicated regions outside the ATL. In the present human fMRI study we used multivoxel pattern analysis to test whether activity patterns in ATLs carry information about conceptual object properties. Participants viewed objects that differed on two dimensions: where the object is typically found (in the kitchen or the garage) and how the object is commonly used (with a rotate or a squeeze movement). Anatomical region-of-interest analyses covering the ventral visual stream revealed that information about the location and action dimensions increased from posterior to anterior ventral temporal cortex, peaking in the temporal pole. Whole-brain multivoxel searchlight analysis confirmed these results, revealing highly significant and regionally specific information about the location and action dimensions in the anterior temporal lobes bilaterally. In contrast to conceptual object properties, perceptual and low-level visual properties of the objects were reflected in activity patterns in posterior lateral occipitotemporal cortex and occipital cortex, respectively. These results provide fMRI evidence that object representations in the anterior temporal lobes are abstracted away from perceptual properties, categorizing objects in semantically meaningful groups to support conceptual object knowledge.

The rapid visual detection of other people in our environment is an important first step in social cognition. Here we provide evidence for selective sensitivity of the human visual system to upright depictions of conspecifics. In a series of seven experiments, we assessed the impact of stimulus inversion on the detection of person silhouettes, headless bodies, faces and other objects from a wide range of animate and inanimate control categories. We used continuous flash suppression (CFS), a variant of binocular rivalry, to render stimuli invisible at the beginning of each trial and measured the time upright and inverted stimuli needed to overcome such interocular suppression. Inversion strongly interfered with access to awareness for human faces, headless human bodies, person silhouettes, and even highly variable body postures, while suppression durations for control objects were not (inanimate objects) or only mildly (animal faces and bodies) affected by inversion. Furthermore, inversion effects were eliminated when the normal body configuration was distorted. The absence of strong inversion effects in a binocular control condition not involving interocular suppression suggests that non-conscious mechanisms mediated the effect of inversion on body and face detection during CFS. These results indicate that perceptual mechanisms that govern access to visual awareness are highly sensitive to the presence of conspecifics., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The left-hemisphere dominance for language is a core example of the functional specialization of the cerebral hemispheres. The degree of left-hemisphere dominance for language depends on hand preference: Whereas the majority of right-handers show left-hemispheric language lateralization, this number is reduced in left-handers. Here, we assessed whether handedness analogously has an influence upon lateralization in the visual system. Using functional magnetic resonance imaging, we localized 4 more or less specialized extrastriate areas in left- and right-handers, namely fusiform face area (FFA), extrastriate body area (EBA), fusiform body area (FBA), and human motion area (human middle temporal [hMT]). We found that lateralization of FFA and EBA depends on handedness: These areas were right lateralized in right-handers but not in left-handers. A similar tendency was observed in FBA but not in hMT. We conclude that the relationship between handedness and hemispheric lateralization extends to functionally lateralized parts of visual cortex, indicating a general coupling between cerebral lateralization and handedness. Our findings indicate that hemispheric specialization is not fixed but can vary considerably across individuals even in areas engaged relatively early in the visual system.

Accumulating evidence points to a map of visual regions encoding specific categories of objects. For example, a region in the human extrastriate visual cortex, the extrastriate body area (EBA), has been implicated in the visual processing of bodies and body parts. Although in the monkey, neurons selective for hands have been reported, in humans it is unclear whether areas selective for individual body parts such as the hand exist. Here, we conducted two functional MRI experiments to test for hand-preferring responses in the human extrastriate visual cortex. We found evidence for a hand-preferring region in left lateral occipitotemporal cortex in all 14 participants. This region, located in the lateral occipital sulcus, partially overlapped with left EBA, but could be functionally and anatomically dissociated from it. In experiment 2, we further investigated the functional profile of hand- and body-preferring regions by measuring responses to hands, fingers, feet, assorted body parts (arms, legs, torsos), and non-biological handlike stimuli such as robotic hands. The hand-preferring region responded most strongly to hands, followed by robotic hands, fingers, and feet, whereas its response to assorted body parts did not significantly differ from baseline. By contrast, EBA responded most strongly to body parts, followed by hands and feet, and did not significantly respond to robotic hands or fingers. Together, these results provide evidence for a representation of the hand in extrastriate visual cortex that is distinct from the representation of other body parts.

Viewing faces or bodies activates category-selective areas of visual cortex, including the fusiform face area (FFA), fusiform body area (FBA), and extrastriate body area (EBA). Here, using fMRI, we investigate the development of these areas, focusing on the right FFA and FBA. Despite the overlap of functionally defined FFA and FBA (54%-75% overlap), we found that these regions developed along different trajectories. With age (7-32 years old), the FFA gradually increased in size and selectivity, and was significantly larger and more face-selective in adults than children. By contrast, the size and selectivity of the FBA did not correlate with age, and were equivalent in children and adults. Whereas in adults the FFA and FBA were comparable in size, in children the FBA was on average 70% larger than the FFA. These findings suggest that, in children, the fusiform gyrus is predominantly selective for bodies, with commensurate face-selective responses apparent later in development. Moreover, differences in the development of the FFA and FBA indicate that overlapping functional brain areas, supported by the same anatomical structure, can develop along different trajectories.

The human body, like the human face, is a rich source of socially relevant information about other individuals. Evidence from studies of both humans and non-human primates points to focal regions of the higher-level visual cortex that are specialized for the visual perception of the body. These body-selective regions, which can be dissociated from regions involved in face perception, have been implicated in the perception of the self and the 'body schema', the perception of others' emotions and the understanding of actions.

We used functional magnetic resonance imaging (fMRI) to investigate within-subject reproducibility of activation in higher level, category-specific visual areas to validate the functional localization approach widely used for these areas. The brain areas investigated included the extrastriate body area (EBA), which responds selectively to human bodies, the fusiform face area (FFA) and the occipital face area (OFA), which respond selectively to faces, and the parahippocampal place area (PPA), which responds selectively to places and scenes. All six subjects showed significant bilateral activation in the four areas. Reproducibility was very high for all areas, both within a scanning session and between scanning sessions separated by 3 weeks. Within sessions, the mean distance between peak voxels of the same area localized by using different functional runs was 1.5 mm. The mean distance between peak voxels of areas localized in different sessions was 2.9 mm. Functional reproducibility, as expressed by the stability of T-values across sessions, was high for both within-session and between-session comparisons. We conclude that within subjects, high-level category-specific visual areas can be localized robustly across scanning sessions.

Functional neuroimaging studies have revealed human brain regions, notably in the fusiform gyrus, that respond selectively to images of faces as opposed to other kinds of objects. Here we use fMRI to show that the mid-fusiform gyrus responds with nearly the same level of selectivity to images of human bodies without faces, relative to tools and scenes. In a group-average analysis (n = 22), the fusiform activations identified by contrasting faces versus tools and bodies versus tools are very similar. Analyses of within-subjects regions of interest, however, show that the peaks of the two activations occupy close but distinct locations. In a second experiment, we find that the body-selective fusiform region, but not the face-selective region, responds more to stick figure depictions of bodies than to scrambled controls. This result further distinguishes the two foci and confirms that the body-selective response generalizes to abstract image formats. These results challenge accounts of the mid-fusiform gyrus that focus solely on faces and suggest that this region contains multiple distinct category-selective neural representations.