An Information-Driven 2-Pathway Characterization of Occipitotemporal and Posterior Parietal Visual Object Representations

Attention modulates human visual responses to objects by tuning sharpening

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars, and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias toward the target is not fixed but decreases with increasing target-distractor similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for the behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

Two "What" Networks in the Human Brain

Ungerleider and Mishkin, in their influential work that relied on detailed anatomical and ablation studies, suggested that visual information is processed along two distinct pathways: the dorsal "where" pathway, primarily responsible for spatial vision, and the ventral "what" pathway, dedicated to object vision. This strict division of labor has faced challenges in light of compelling evidence revealing robust shape and object selectivity within the putative "where" pathway. This article reviews evidence that supports the presence of shape selectivity in the dorsal pathway. A comparative examination of dorsal and ventral object representations in terms of invariance, task dependency, and representational content reveals similarities and differences between the two pathways. Both exhibit some level of tolerance to image transformations and are influenced by tasks, but responses in the dorsal pathway show weaker tolerance and stronger task modulations than those in the ventral pathway. Furthermore, an examination of their representational content highlights a divergence between the responses in the two pathways, suggesting that they are sensitive to distinct features of objects. Collectively, these findings suggest that two networks exist in the human brain for processing object shapes, one in the dorsal and another in the ventral visual cortex. These studies lay the foundation for future research aimed at revealing the precise roles the two "what" networks play in our ability to understand and interact with objects.

Insights from the Evolving Model of Two Cortical Visual Pathways

The two cortical visual pathways framework has had a profound influence on theories and empirical studies of the visual system for over 40 years. By grounding physiological responses and behavior in neuroanatomy, the framework provided a critical guide for understanding vision. Although the framework has evolved over time, as our understanding of the physiology and neuroanatomy expanded, cortical visual processing is still often conceptualized as two separate pathways emerging from the primary visual cortex that support distinct behaviors ("what" vs. "where/how"). Here, we take a historical perspective and review the continuing evolution of the framework, discussing key and often overlooked insights. Rather than a functional and neuroanatomical bifurcation into two independent serial, hierarchical pathways, the current evidence points to two highly recurrent heterarchies with heterogeneous connections to cortical regions and subcortical structures that flexibly support a wide variety of behaviors. Although many of the simplifying assumptions of the framework are belied by the evidence gathered since its initial proposal, the core insight of grounding function and behavior in neuroanatomy remains fundamental. Given this perspective, we highlight critical open questions and the need for a better understanding of neuroanatomy, particularly in the human.

The human posterior parietal cortices orthogonalize the representation of different streams of information concurrently coded in visual working memory

The key to adaptive visual processing lies in the ability to maintain goal-directed visual representation in the face of distraction. In visual working memory (VWM), distraction may come from the coding of distractors or other concurrently retained targets. This fMRI study reveals a common representational geometry that our brain uses to combat both types of distractions in VWM. Specifically, using fMRI pattern decoding, the human posterior parietal cortex is shown to orthogonalize the representations of different streams of information concurrently coded in VWM, whether they are targets and distractors, or different targets concurrently held in VWM. The latter is also seen in the human occipitotemporal cortex. Such a representational geometry provides an elegant and simple solution to enable independent information readout, effectively combating distraction from the different streams of information, while accommodating their concurrent representations. This representational scheme differs from mechanisms that actively suppress or block the encoding of distractors to reduce interference. It is likely a general neural representational principle that supports our ability to represent information beyond VWM in other situations where multiple streams of visual information are tracked and processed simultaneously.

Attention Modulates Human Visual Responses to Objects by Tuning Sharpening

Visual stimuli compete with each other for cortical processing and attention biases this competition in favor of the attended stimulus. How does the relationship between the stimuli affect the strength of this attentional bias? Here, we used functional MRI to explore the effect of target-distractor similarity in neural representation on attentional modulation in the human visual cortex using univariate and multivariate pattern analyses. Using stimuli from four object categories (human bodies, cats, cars and houses), we investigated attentional effects in the primary visual area V1, the object-selective regions LO and pFs, the body-selective region EBA, and the scene-selective region PPA. We demonstrated that the strength of the attentional bias towards the target is not fixed but decreases with increasing target-distractor similarity. Simulations provided evidence that this result pattern is explained by tuning sharpening rather than an increase in gain. Our findings provide a mechanistic explanation for behavioral effects of target-distractor similarity on attentional biases and suggest tuning sharpening as the underlying mechanism in object-based attention.

The large-scale organization of shape processing in the ventral and dorsal pathways is dissociable from attention

The two visual pathways model posits that visual information is processed through two distinct cortical systems: The ventral pathway promotes visual recognition, while the dorsal pathway supports visuomotor control. Recent evidence suggests the dorsal pathway is also involved in shape processing and may contribute to object perception, but it remains unclear whether this sensitivity is independent of attentional mechanisms that were localized to overlapping cortical regions. To address this question, we conducted two fMRI experiments that utilized different parametric scrambling manipulations in which human participants viewed novel objects in different levels of scrambling and were instructed to attend to either the object or to another aspect of the image (e.g. color of the background). Univariate and multivariate analyses revealed that the large-scale organization of shape selectivity along the dorsal and ventral pathways was preserved regardless of the focus of attention. Attention did modulate shape sensitivity, but these effects were similar across the two pathways. These findings support the idea that shape processing is at least partially dissociable from attentional processes and relies on a distributed set of cortical regions across the visual pathways.

Naturalistic Object Representations Depend on Distance and Size Cues

Egocentric distance and real-world size are important cues for object perception and action. Nevertheless, most studies of human vision rely on two-dimensional pictorial stimuli that convey ambiguous distance and size information. Here, we use fMRI to test whether pictures are represented differently in the human brain from real, tangible objects that convey unambiguous distance and size cues. Participants directly viewed stimuli in two display formats (real objects and matched printed pictures of those objects) presented at different egocentric distances (near and far). We measured the effects of format and distance on fMRI response amplitudes and response patterns. We found that fMRI response amplitudes in the lateral occipital and posterior parietal cortices were stronger overall for real objects than for pictures. In these areas and many others, including regions involved in action guidance, responses to real objects were stronger for near vs. far stimuli, whereas distance had little effect on responses to pictures-suggesting that distance determines relevance to action for real objects, but not for pictures. Although stimulus distance especially influenced response patterns in dorsal areas that operate in the service of visually guided action, distance also modulated representations in ventral cortex, where object responses are thought to remain invariant across contextual changes. We observed object size representations for both stimulus formats in ventral cortex but predominantly only for real objects in dorsal cortex. Together, these results demonstrate that whether brain responses reflect physical object characteristics depends on whether the experimental stimuli convey unambiguous information about those characteristics.

Significance Statement

Classic frameworks of vision attribute perception of inherent object characteristics, such as size, to the ventral visual pathway, and processing of spatial characteristics relevant to action, such as distance, to the dorsal visual pathway. However, these frameworks are based on studies that used projected images of objects whose actual size and distance from the observer were ambiguous. Here, we find that when object size and distance information in the stimulus is less ambiguous, these characteristics are widely represented in both visual pathways. Our results provide valuable new insights into the brain representations of objects and their various physical attributes in the context of naturalistic vision.

A focus on the multiple interfaces between action and perception and their neural correlates

Successful behaviour relies on the appropriate interplay between action and perception. The well-established dorsal and ventral stream theories depicted two distinct functional pathways for the processes of action and perception, respectively. In physiological conditions, the two pathways closely cooperate in order to produce successful adaptive behaviour. As the coupling between perception and action exists, this requires an interface that is responsible for a common reading of the two functions. Several studies have proposed different types of perception and action interfaces, suggesting their role in the creation of the shared interaction channel. In the present review, we describe three possible perception and action interfaces: i) the motor code, including common coding approaches, ii) attention, and iii) object affordance; we highlight their potential neural correlates. From this overview, a recurrent neural substrate that underlies all these interface functions appears to be crucial: the parieto-frontal circuit. This network is involved in the mirror mechanism which underlies the perception and action interfaces identified as common coding and motor code theories. The same network is also involved in the spotlight of attention and in the encoding of potential action towards objects; these are manifested in the perception and action interfaces for common attention and object affordance, respectively. Within this framework, most studies were dedicated to the description of the role of the inferior parietal lobule; growing evidence, however, suggests that the superior parietal lobule also plays a crucial role in the interplay between action and perception. The present review proposes a novel model that is inclusive of the superior parietal regions and their relative contribution to the different action and perception interfaces.

Parietal-driven visual working memory representation in occipito-temporal cortex

Human fMRI studies have documented extensively that the content of visual working memory (VWM) can be reliably decoded from fMRI voxel response patterns during the delay period in both the occipito-temporal cortex (OTC), including early visual areas (EVC), and the posterior parietal cortex (PPC).1,2,3,4 Further work has revealed that VWM signal in OTC is largely sustained by feedback from associative areas such as prefrontal cortex (PFC) and PPC.4,5,6,7,8,9 It is unclear, however, if feedback during VWM simply restores sensory representations initially formed in OTC or if it can reshape the representational content of OTC during VWM delay. Taking advantage of a recent finding showing that object representational geometry differs between OTC and PPC in perception,10 here we find that, during VWM delay, the object representational geometry in OTC becomes more aligned with that of PPC during perception than with itself during perception. This finding supports the role of feedback in shaping the content of VWM in OTC, with the VWM content of OTC more determined by information retained in PPC than by the sensory information initially encoded in OTC.

From intermediate shape-centered representations to the perception of oriented shapes: response to commentaries

In this response paper, we start by addressing the main points made by the commentators on the target article's main theoretical conclusions: the existence and characteristics of the intermediate shape-centered representations (ISCRs) in the visual system, their emergence from edge detection mechanisms operating on different types of visual properties, and how they are eventually reunited in higher order frames of reference underlying conscious visual perception. We also address the much-commented issue of the possible neural mechanisms of the ISCRs. In the final section, we address more specific and general comments, questions, and suggestions which, albeit very interesting, were less directly focused on the main conclusions of the target paper.

Two distinct networks containing position-tolerant representations of actions in the human brain

Humans can recognize others' actions in the social environment. This action recognition ability is rarely hindered by the movement of people in the environment. The neural basis of this position tolerance for observed actions is not fully understood. Here, we aimed to identify brain regions capable of generalizing representations of actions across different positions and investigate the representational content of these regions. In a functional magnetic resonance imaging experiment, participants viewed point-light displays of different human actions. Stimuli were presented in either the upper or the lower visual field. Multivariate pattern analysis and a surface-based searchlight approach were employed to identify brain regions that contain position-tolerant action representation: Classifiers were trained with patterns in response to stimuli presented in one position and were tested with stimuli presented in another position. Results showed above-chance classification in the left and right lateral occipitotemporal cortices, right intraparietal sulcus, and right postcentral gyrus. Further analyses exploring the representational content of these regions showed that responses in the lateral occipitotemporal regions were more related to subjective judgments, while those in the parietal regions were more related to objective measures. These results provide evidence for two networks that contain abstract representations of human actions with distinct representational content.

Disentangling Object Category Representations Driven by Dynamic and Static Visual Input

Humans can label and categorize objects in a visual scene with high accuracy and speed, a capacity well characterized with studies using static images. However, motion is another cue that could be used by the visual system to classify objects. To determine how motion-defined object category information is processed by the brain in the absence of luminance-defined form information, we created a novel stimulus set of "object kinematograms" to isolate motion-defined signals from other sources of visual information. Object kinematograms were generated by extracting motion information from videos of 6 object categories and applying the motion to limited-lifetime random dot patterns. Using functional magnetic resonance imaging (fMRI) (n = 15, 40% women), we investigated whether category information from the object kinematograms could be decoded within the occipitotemporal and parietal cortex and evaluated whether the information overlapped with category responses to static images from the original videos. We decoded object category for both stimulus formats in all higher-order regions of interest (ROIs). More posterior occipitotemporal and ventral regions showed higher accuracy in the static condition, while more anterior occipitotemporal and dorsal regions showed higher accuracy in the dynamic condition. Further, decoding across the two stimulus formats was possible in all regions. These results demonstrate that motion cues can elicit widespread and robust category responses on par with those elicited by static luminance cues, even in ventral regions of visual cortex that have traditionally been associated with primarily image-defined form processing.SIGNIFICANCE STATEMENT Much research on visual object recognition has focused on recognizing objects in static images. However, motion is a rich source of information that humans might also use to categorize objects. Here, we present the first study to compare neural representations of several animate and inanimate objects when category information is presented in two formats: static cues or isolated dynamic motion cues. Our study shows that, while higher-order brain regions differentially process object categories depending on format, they also contain robust, abstract category representations that generalize across format. These results expand our previous understanding of motion-derived animate and inanimate object category processing and provide useful tools for future research on object category processing driven by multiple sources of visual information.

Decision-making from temporally accumulated conflicting evidence: The more the merrier

How do humans evaluate temporally accumulated discrete pieces of evidence and arrive at a decision despite the presence of conflicting evidence? In the present study, we showed human participants a sequential presentation of objects drawn from two novel object categories and asked them to decide whether a given presentation contained more objects from one or the other category. We found that both a more disparate ratio and greater numerosity of objects improved both reaction time (RT) and accuracy. The effect of numerosity was separate from ratio, where with a fixed object ratio, sequences with more total objects had lower RT and lower error rates than those with fewer total objects. We replicated these results across three experiments. Additionally, even with the total presentation duration equated and with the motor response assignment varied from trial to trial, an effect of numerosity was still found in RT. The same RT benefit was also present when objects were shown simultaneously, rather than sequentially. Together, these results showed that, for comparative numerosity judgment involving sequential displays, there was a benefit of numerosity, such that showing more objects independent of the object ratio and the total presentation time led to faster decision performance.

Does the brain's ventral visual pathway compute object shape?

A rich behavioral literature has shown that human object recognition is supported by a representation of shape that is tolerant to variations in an object's appearance. Such 'global' shape representations are achieved by describing objects via the spatial arrangement of their local features, or structure, rather than by the appearance of the features themselves. However, accumulating evidence suggests that the ventral visual pathway - the primary substrate underlying object recognition - may not represent global shape. Instead, ventral representations may be better described as a basis set of local image features. We suggest that this evidence forces a reevaluation of the role of the ventral pathway in object perception and posits a broader network for shape perception that encompasses contributions from the dorsal pathway.

Predicting Identity-Preserving Object Transformations in Human Posterior Parietal Cortex and Convolutional Neural Networks

Previous research shows that, within human occipito-temporal cortex (OTC), we can use a general linear mapping function to link visual object responses across nonidentity feature changes, including Euclidean features (e.g., position and size) and non-Euclidean features (e.g., image statistics and spatial frequency). Although the learned mapping is capable of predicting responses of objects not included in training, these predictions are better for categories included than those not included in training. These findings demonstrate a near-orthogonal representation of object identity and nonidentity features throughout human OTC. Here, we extended these findings to examine the mapping across both Euclidean and non-Euclidean feature changes in human posterior parietal cortex (PPC), including functionally defined regions in inferior and superior intraparietal sulcus. We additionally examined responses in five convolutional neural networks (CNNs) pretrained with object classification, as CNNs are considered as the current best model of the primate ventral visual system. We separately compared results from PPC and CNNs with those of OTC. We found that a linear mapping function could successfully link object responses in different states of nonidentity transformations in human PPC and CNNs for both Euclidean and non-Euclidean features. Overall, we found that object identity and nonidentity features are represented in a near-orthogonal, rather than complete-orthogonal, manner in PPC and CNNs, just like they do in OTC. Meanwhile, some differences existed among OTC, PPC, and CNNs. These results demonstrate the similarities and differences in how visual object information across an identity-preserving image transformation may be represented in OTC, PPC, and CNNs.

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks

Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural networks (CNNs) to exhibit human-like object categorization performance, whether CNNs form tolerance similar to that of the human brain is unknown. Here we provide the first comprehensive documentation and comparison of three tolerance measures in the human brain and CNNs. We measured fMRI responses from human ventral visual areas to real-world objects across both Euclidean and non-Euclidean feature changes. In single fMRI voxels in higher visual areas, we observed robust object response rank-order preservation across feature changes. This is indicative of functional smoothness in tolerance at the fMRI meso-scale level that has never been reported before. At the voxel population level, we found highly consistent object representational structure across feature changes towards the end of ventral processing. Rank-order preservation, consistency, and a third tolerance measure, cross-decoding success (i.e., a linear classifier's ability to generalize performance across feature changes) showed an overall tight coupling. These tolerance measures were in general lower for Euclidean than non-Euclidean feature changes in lower visual areas, but increased over the course of ventral processing for all feature changes. These characteristics of tolerance, however, were absent in eight CNNs pretrained with ImageNet images with varying network architecture, depth, the presence/absence of recurrent processing, or whether a network was pretrained with the original or stylized ImageNet images that encouraged shape processing. CNNs do not appear to develop the same kind of tolerance as the human brain over the course of visual processing.

The Dorsal Visual Pathway Represents Object-Centered Spatial Relations for Object Recognition

Although there is mounting evidence that input from the dorsal visual pathway is crucial for object processes in the ventral pathway, the specific functional contributions of dorsal cortex to these processes remain poorly understood. Here, we hypothesized that dorsal cortex computes the spatial relations among an object's parts, a process crucial for forming global shape percepts, and transmits this information to the ventral pathway to support object categorization. Using fMRI with human participants (females and males), we discovered regions in the intraparietal sulcus (IPS) that were selectively involved in computing object-centered part relations. These regions exhibited task-dependent functional and effective connectivity with ventral cortex, and were distinct from other dorsal regions, such as those representing allocentric relations, 3D shape, and tools. In a subsequent experiment, we found that the multivariate response of posterior (p)IPS, defined on the basis of part-relations, could be used to decode object category at levels comparable to ventral object regions. Moreover, mediation and multivariate effective connectivity analyses further suggested that IPS may account for representations of part relations in the ventral pathway. Together, our results highlight specific contributions of the dorsal visual pathway to object recognition. We suggest that dorsal cortex is a crucial source of input to the ventral pathway and may support the ability to categorize objects on the basis of global shape.SIGNIFICANCE STATEMENT Humans categorize novel objects rapidly and effortlessly. Such categorization is achieved by representing an object's global shape structure, that is, the relations among object parts. Yet, despite their importance, it is unclear how part relations are represented neurally. Here, we hypothesized that object-centered part relations may be computed by the dorsal visual pathway, which is typically implicated in visuospatial processing. Using fMRI, we identified regions selective for the part relations in dorsal cortex. We found that these regions can support object categorization, and even mediate representations of part relations in the ventral pathway, the region typically thought to support object categorization. Together, these findings shed light on the broader network of brain regions that support object categorization.

Predicting Identity-Preserving Object Transformations across the Human Ventral Visual Stream

In everyday life, we have no trouble categorizing objects varying in position, size, and orientation. Previous fMRI research shows that higher-level object processing regions in the human lateral occipital cortex may link object responses from different affine states (i.e., size and viewpoint) through a general linear mapping function capable of predicting responses to novel objects. In this study, we extended this approach to examine the mapping for both Euclidean (e.g., position and size) and non-Euclidean (e.g., image statistics and spatial frequency) transformations across the human ventral visual processing hierarchy, including areas V1, V2, V3, V4, ventral occipitotemporal cortex, and lateral occipitotemporal cortex. The predicted pattern generated from a linear mapping function could capture a significant amount of the changes associated with the transformations throughout the ventral visual stream. The derived linear mapping functions were not category independent as performance was better for the categories included than those not included in training and better between two similar versus two dissimilar categories in both lower and higher visual regions. Consistent with object representations being stronger in higher than in lower visual regions, pattern selectivity and object category representational structure were somewhat better preserved in the predicted patterns in higher than in lower visual regions. There were no notable differences between Euclidean and non-Euclidean transformations. These findings demonstrate a near-orthogonal representation of object identity and these nonidentity features throughout the human ventral visual processing pathway with these nonidentity features largely untangled from the identity features early in visual processing.SIGNIFICANCE STATEMENT Presently we still do not fully understand how object identity and nonidentity (e.g., position, size) information are simultaneously represented in the primate ventral visual system to form invariant representations. Previous work suggests that the human lateral occipital cortex may be linking different affine states of object representations through general linear mapping functions. Here, we show that across the entire human ventral processing pathway, we could link object responses in different states of nonidentity transformations through linear mapping functions for both Euclidean and non-Euclidean transformations. These mapping functions are not identity independent, suggesting that object identity and nonidentity features are represented in a near rather than a completely orthogonal manner.

Limits to visual representational correspondence between convolutional neural networks and the human brain

Convolutional neural networks (CNNs) are increasingly used to model human vision due to their high object categorization capabilities and general correspondence with human brain responses. Here we evaluate the performance of 14 different CNNs compared with human fMRI responses to natural and artificial images using representational similarity analysis. Despite the presence of some CNN-brain correspondence and CNNs' impressive ability to fully capture lower level visual representation of real-world objects, we show that CNNs do not fully capture higher level visual representations of real-world objects, nor those of artificial objects, either at lower or higher levels of visual representations. The latter is particularly critical, as the processing of both real-world and artificial visual stimuli engages the same neural circuits. We report similar results regardless of differences in CNN architecture, training, or the presence of recurrent processing. This indicates some fundamental differences exist in how the brain and CNNs represent visual information.

Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks

A visual object is characterized by multiple visual features, including its identity, position and size. Despite the usefulness of identity and nonidentity features in vision and their joint coding throughout the primate ventral visual processing pathway, they have so far been studied relatively independently. Here in both female and male human participants, the coding of identity and nonidentity features was examined together across the human ventral visual pathway. The nonidentity features tested included two Euclidean features (position and size) and two non-Euclidean features (image statistics and spatial frequency (SF) content of an image). Overall, identity representation increased and nonidentity feature representation decreased along the ventral visual pathway, with identity outweighing the non-Euclidean but not the Euclidean features at higher levels of visual processing. In 14 convolutional neural networks (CNNs) pretrained for object categorization with varying architecture, depth, and with/without recurrent processing, nonidentity feature representation showed an initial large increase from early to mid-stage of processing, followed by a decrease at later stages of processing, different from brain responses. Additionally, from lower to higher levels of visual processing, position became more underrepresented and image statistics and SF became more overrepresented compared with identity in CNNs than in the human brain. Similar results were obtained in a CNN trained with stylized images that emphasized shape representations. Overall, by measuring the coding strength of object identity and nonidentity features together, our approach provides a new tool for characterizing feature coding in the human brain and the correspondence between the brain and CNNs.SIGNIFICANCE STATEMENT This study examined the coding strength of object identity and four types of nonidentity features along the human ventral visual processing pathway and compared brain responses with those of 14 convolutional neural networks (CNNs) pretrained to perform object categorization. Overall, identity representation increased and nonidentity feature representation decreased along the ventral visual pathway, with some notable differences among the different nonidentity features. CNNs differed from the brain in a number of aspects in their representations of identity and nonidentity features over the course of visual processing. Our approach provides a new tool for characterizing feature coding in the human brain and the correspondence between the brain and CNNs.

Revisit once more the sensory storage account of visual working memory

Recent work has highlighted the role of early visual areas in visual working memory (VWM) storage and put forward a sensory storage account of VWM. Using a distractor interference paradigm, however, we previolsy showed that the contribution of early visual areas to VWM storage may not be essential. Instead, higher cortical regions such as the posterior parietal cortex may play a more significant role in VWM storage. This is consistent with reviews of other available behavioral, neuroimaging and neurophysiology results. Recently, a number of studies brought forward new evidence regarding this debate. Here I review these new pieces of evidence in detail and show that there is still no strong and definitive evidence supporting an essential role of the early visual areas in VWM storage. Instead, converging evidence suggests that early visual areas may contribute to the decision stage of a VWM task by facilitating target and probe comparison. Aside from further clarifying this debate, it is also important to note that whether or not VWM storage uses a sensory code depends on how it is defined, and that behavioral interactions between VWM and perception tasks do not necessarily support the involvement of sensory regions in VWM storage.

Altered large-scale organization of shape processing in visual agnosia

Recent findings suggest that both dorsal and ventral visual pathways process shape information. Nevertheless, a lesion to the ventral pathway alone can result in visual agnosia, an impairment in shape perception. Here, we explored the neural basis of shape processing in a patient with visual agnosia following a circumscribed right hemisphere ventral lesion and evaluated longitudinal changes in the neural profile of shape representations. The results revealed a reduction of shape sensitivity slopes along the patient's right ventral pathway and a similar reduction in the contralesional left ventral pathway. Remarkably, posterior parts of the dorsal pathway bilaterally also evinced a reduction in shape sensitivity. These findings were similar over a two-year interval, revealing that a focal cortical lesion can lead to persistent large-scale alterations of the two visual pathways. These alterations are consistent with the view that a distributed network of regions contributes to shape perception.

What Does Dorsal Cortex Contribute to Perception?

According to the influential "Two Visual Pathways" hypothesis, the cortical visual system is segregated into two pathways, with the ventral, occipitotemporal pathway subserving object perception, and the dorsal, occipitoparietal pathway subserving the visuomotor control of action. However, growing evidence suggests that the dorsal pathway also plays a functional role in object perception. In the current article, we present evidence that the dorsal pathway contributes uniquely to the perception of a range of visuospatial attributes that are not redundant with representations in ventral cortex. We describe how dorsal cortex is recruited automatically during perception, even when no explicit visuomotor response is required. Importantly, we propose that dorsal cortex may selectively process visual attributes that can inform the perception of potential actions on objects and environments, and we consider plausible developmental and cognitive mechanisms that might give rise to these representations. As such, we consider whether naturalistic stimuli, such as real-world solid objects, might engage dorsal cortex more so than simplified or artificial stimuli such as images that do not afford action, and how the use of suboptimal stimuli might limit our understanding of the functional contribution of dorsal cortex to visual perception.

Recent advances in understanding object recognition in the human brain: deep neural networks, temporal dynamics, and context

Object recognition is the ability to identify an object or category based on the combination of visual features observed. It is a remarkable feat of the human brain, given that the patterns of light received by the eye associated with the properties of a given object vary widely with simple changes in viewing angle, ambient lighting, and distance. Furthermore, different exemplars of a specific object category can vary widely in visual appearance, such that successful categorization requires generalization across disparate visual features. In this review, we discuss recent advances in understanding the neural representations underlying object recognition in the human brain. We highlight three current trends in the approach towards this goal within the field of cognitive neuroscience. Firstly, we consider the influence of deep neural networks both as potential models of object vision and in how their representations relate to those in the human brain. Secondly, we review the contribution that time-series neuroimaging methods have made towards understanding the temporal dynamics of object representations beyond their spatial organization within different brain regions. Finally, we argue that an increasing emphasis on the context (both visual and task) within which object recognition occurs has led to a broader conceptualization of what constitutes an object representation for the brain. We conclude by identifying some current challenges facing the experimental pursuit of understanding object recognition and outline some emerging directions that are likely to yield new insight into this complex cognitive process.

Task modulation of the 2-pathway characterization of occipitotemporal and posterior parietal visual object representations

Recent studies have reported the existence of rich non-spatial visual object representations in both human and monkey posterior parietal cortex (PPC), similar to those found in occipito-temporal cortex (OTC). Despite this similarity, we recently showed that visual object representation still differ between OTC and PPC in two aspects. In one study, by manipulating whether object shape or color was task relevant, we showed that visual object representations were under greater top-down attention and task control in PPC than in OTC (Vaziri-Pashkam & Xu, 2017, J Neurosci). In another study, using a bottom-up data driven approach, we showed that there exists a large separation between PPC and OTC regions in the representational space, with OTC regions lining up hierarchically along an OTC pathway and PPC regions lining up hierarchically along an orthogonal PPC pathway (Vaziri-Pashkam & Xu, 2019, Cereb Cortex). To understand the interaction of goal-driven visual processing and the two-pathway structure in the representational space, here we performed a set of new analyses of the data from the three experiments of Vaziri-Pashkam and Xu (2017) and directly compared the two-pathway separation of OTC and PPC regions when object shapes were attended and task relevant and when they were not. We found that in all three experiments the correlation of visual object representational structure between superior IPS (a key PPC visual region) and lateral and ventral occipito-temporal regions (higher OTC visual regions) became greater when object shapes were attended than when they were not. This modified the two-pathway structure, with PPC regions moving closer to higher OTC regions and a compression of the PPC pathway towards the OTC pathway in the representational space when shapes were attended. Consistent with this observation, the correlation between neural and behavioral measures of visual representational structure was also higher in superior IPS when shapes were attended than when they were not. By comparing representational structures across experiments and tasks, we further showed that attention to object shape resulted in the formation of more similar object representations in superior IPS across experiments than between the two tasks within the same experiment despite noise and stimulus differences across the experiments. Overall, these results demonstrated that, despite the separation of the OTC and PPC pathways in the representational space, the visual representational structure of PPC is flexible and can be modulated by the task demand. This reaffirms the adaptive nature of visual processing in PPC and further distinguishes it from the more invariant nature of visual processing in OTC.

An integrative computational architecture for object-driven cortex

Computational architecture for object-driven cortex Objects in motion activate multiple cortical regions in every lobe of the human brain. Do these regions represent a collection of independent systems, or is there an overarching functional architecture spanning all of object-driven cortex? Inspired by recent work in artificial intelligence (AI), machine learning, and cognitive science, we consider the hypothesis that these regions can be understood as a coherent network implementing an integrative computational system that unifies the functions needed to perceive, predict, reason about, and plan with physical objects-as in the paradigmatic case of using or making tools. Our proposal draws on a modeling framework that combines multiple AI methods, including causal generative models, hybrid symbolic-continuous planning algorithms, and neural recognition networks, with object-centric, physics-based representations. We review evidence relating specific components of our proposal to the specific regions that comprise object-driven cortex, and lay out future research directions with the goal of building a complete functional and mechanistic account of this system.

The Posterior Parietal Cortex in Adaptive Visual Processing

Although the primate posterior parietal cortex (PPC) has been largely associated with space, attention, and action-related processing, a growing number of studies have reported the direct representation of a diverse array of action-independent nonspatial visual information in the PPC during both perception and visual working memory. By describing the distinctions and the close interactions of visual representation with space, attention, and action-related processing in the PPC, here I propose that we may understand these diverse PPC functions together through the unique contribution of the PPC to adaptive visual processing and form a more integrated and structured view of the role of the PPC in vision, cognition, and action.

A Tale of Two Visual Systems: Invariant and Adaptive Visual Information Representations in the Primate Brain

Visual information processing contains two opposite needs. There is both a need to comprehend the richness of the visual world and a need to extract only pertinent visual information to guide thoughts and behavior at a given moment. I argue that these two aspects of visual processing are mediated by two complementary visual systems in the primate brain-specifically, the occipitotemporal cortex (OTC) and the posterior parietal cortex (PPC). The role of OTC in visual processing has been documented extensively by decades of neuroscience research. I review here recent evidence from human imaging and monkey neurophysiology studies to highlight the role of PPC in adaptive visual processing. I first document the diverse array of visual representations found in PPC. I then describe the adaptive nature of visual representation in PPC by contrasting visual processing in OTC and PPC and by showing that visual representations in PPC largely originate from OTC.