Visual Agnosia is a comprehensive and up-to-date review of disorders of higher vision that relates these disorders to current conceptions of higher vision from cognitive science, illuminating both the neuropsychological disorders and the nature of normal visual object recognition.Brain damage can lead to selective problems with visual perception, including visual agnosia the inability to recognize objects even though elementary visual functions remain unimpaired. Such disorders are relatively rare, yet they provide a window onto how the normal brain might (...) accomplish the complex task of vision. Visual Agnosia reviews a century of case studies of higher-level visual deficits following brain damage, places them in the general context of current neuroscience, and draws relevant conclusions about the organization of normal visual processing. It is unique in drawing on research in cognitive psychology, computational vision, visual neurophysiology, and neuropsychology to interpret the agnosias and draw inferences from them about visual object recognition.Following a historical account of agnosia research, Visual Agnosia offers a taxonomy of a wide range of agnosia syndromes, describing and interpreting the syndromes in terms of the latest theoretical models of visual processing and ultimately bringing them to bear as evidence on a variety of questions in the study of higher vision.Martha J. Farah is Associate Professor of Psychology at Carnegie Mellon University. Visual Agnosia is included in the Issues in Biology of Language and Cognition series, edited by John Marshall. (shrink)

Predicates involved in language and reasoning are claimed to radically differ from categories applied to objects. Human predicates are the cognitive result of a contrast between perceived objects. Object recognition alone cannot generate such operations as modification and explicit negation. The mechanism studied by Hurford constitutes at best an evolutionary prerequisite of human predication ability.

AimVisual functions of the dorsal stream are considered vulnerable in children with early brain damage. Considering the recognition of objects in suboptimal representations a dorsal stream dysfunction, we examined whether children with early brain damage and impaired object recognition had either general or selective dorsal stream dysfunctions.MethodIn a group of children with early brain damage we evaluated the dorsal stream functioning. To determine whether these patients had an increased risk of a dorsal stream dysfunction we compared the (...) percentage of patients with impaired object recognition, assessed with the L94, with the estimated base rate. Then we evaluated the performance levels on motion perception, visual attention and visuomotor tasks in patients with and without object recognition abnormalities. A general dorsal stream dysfunction was considered present if a patient showed at least one abnormally low score in two out of three additional dorsal stream functions.ResultsSix of the eighteen patients with object recognition problems scored abnormally low on at least two additional dorsal stream functions. This was significantly higher than the base rate. The difference of 24.1% between the patients with and without object recognition problems was not significant. Of the patients with object recognition problems 72.2% had at least 1 dorsal weakness, whereas this was only the case in 27.3% of patients without object recognition problems. Compared to patients with normal object recognition, patients with object recognition problems scored significantly more abnormally low on motion perception and visual attention but did not differ on visuomotor skills.ConclusionChildren with object recognition problems seem at risk for other dorsal stream dysfunctions, but dysfunctions might be rather specific than general. Multiple functions/aspects should be evaluated in neuropsychological assessment of children at risk. (shrink)

The question of whether object recognition is orientation-invariant or orientation-dependent was investigated using a repetition blindness (RB) paradigm. In RB, the second occurrence of a repeated stimulus is less likely to be reported, compared to the occurrence of a different stimulus, if it occurs within a short time of the first presentation. This failure is usually interpreted as a difficulty in assigning two separate episodic tokens to the same visual type. Thus, RB can provide useful information about which (...) representations are treated as the same by the visual system. Two experiments tested whether RB occurs for repeated objects that were either in identical orientations, or differed by 30, 60, 90, or 180°. Significant RB was found for all orientation differences, consistent with the existence of orientation-invariant object representations. However, under some circumstances, RB was reduced or even eliminated when the repeated object was rotated by 180°, suggesting easier individuation of the repeated objects in this case. A third experiment confirmed that the upside-down orientation is processed more easily than other rotated orientations. The results indicate that, although object identity can be determined independently of orientation, orientation plays an important role in establishing distinct episodic representations of a repeated object, thus enabling one to report them as separate events. (shrink)

Predictive processing models of perception take issue with standard models of perception as hierarchical bottom-up processing modulated by memory and attention. The predictive framework posits that the brain generates predictions about stimuli, which are matched to the incoming signal. Mismatches between predictions and the incoming signal – so-called prediction errors – are then used to generate new and better predictions until the prediction errors have been minimized, at which point a perception arises. Predictive models hold that all bottom-up processes are (...) signals conveying prediction errors to higher areas, which respond by updating their predictions. We take issue with this claim and argue that object recognition requires bottom-up processing that cannot be understood in terms of prediction errors. Along the way, we expand on previous work casting doubt on the framework's ability to account for attention. Specifically, we argue that the type of attention that allows us to rapidly extract the gist of an object or scene presents an additional challenge to the predictive approach. We conclude by considering how the framework may be augmented to avoid these problems. (shrink)

Puzzles concerning attitude reports are at the origin of traditional theories of content. According to most of these theories, content has to involve some sort of conceptual entities, like senses, which determine reference. Conceptual views, however, have been challenged by direct reference theories and informational perspectives on content. In this paper we lay down the central elements of the more relevant strategies for solving cognitive puzzles. We then argue that the best solution available to those who maintain a view of (...) content as truth conditions is to abandon the idea that content is the only element of mental attitudes that can make a difference as to the truth value of attitude reports. We finally resort to means of recognition of objects as one obvious element that helps explain differences in attitudes. (shrink)

differentiaily rated pairwise similarity when confronted with two pairs of objects, each revolving in a separate window on a computer screen. Subject data were pooled using individually weighted MDS (ref. 11; in all the experiments, the solutions were consistent among subjects). In each trial, the subject had to select among two pairs of shapes the one consisting of the most similar shapes. The subjects were allowed to respond at will; most responded within 10 sec. Proximity (that is, perceived similarity) tables (...) derived from the judgments were processed to verify their degree of transitivity (4% of all triplets were found intransitive) and then submitted to MDS. In the long-term memory (LTM) variant of this experiment, the subjects were first trained to associate a label (a three-letter nonsensical string, such as "BON" or "POM") with each object and then carried out the pairs of pairs comparison task from memory, prompted by the object labels rather than by the objects themselves. Six subjects participated in each of the two LTM experiments (Star and Triangle). The subjects were taught each shape in a separate session and had to discriminate between that shape and six similar nontargets from various viewpoints. Training continued until the recognition rate reached 90%, over a period of several days. The subjects were never exposed to more than one target in one session and were not told the ultimate purpose of the experiment. After 2 to 3 days of rest, they were tested with questions such as: "is the BON more similar to POM than TOC to ROX?", for all pairs of pairs of stimuli. In the LTM experiments, 8% of the.. (shrink)

How do newborns learn to recognize objects? According to temporal learning models in computational neuroscience, the brain constructs object representations by extracting smoothly changing features from the environment. To date, however, it is unknown whether newborns depend on smoothly changing features to build invariant object representations. Here, we used an automated controlled-rearing method to examine whether visual experience with smoothly changing features facilitates the development of view-invariant object recognition in a newborn animal model—the domestic chick. When (...) newborn chicks were reared with a virtual object that moved smoothly over time, the chicks created view-invariant representations that were selective for object identity and tolerant to viewpoint changes. Conversely, when newborn chicks were reared with a temporally non-smooth object, the chicks developed less selectivity for identity features and less tolerance to viewpoint changes. These results provide evidence for a “smoothness constraint” on the development of invariant object recognition and indicate that newborns leverage the temporal smoothness of natural visual environments to build abstract mental models of objects. (shrink)

Haptic object recognition is usually an efficient process although slower and less accurate than its visual counterpart. The early loss of vision imposes a greater reliance on haptic perception for recognition compared to the sighted. Therefore, we may expect that congenitally blind persons could recognize objects through touch more quickly and accurately than late blind or sighted people. However, the literature provided mixed results. Furthermore, most of the studies on haptic object recognition focused on performance, (...) devoting little attention to the exploration procedures that conducted to that performance. In this study, we used iCube, an instrumented cube recording its orientation in space as well as the location of the points of contact on its faces. Three groups of congenitally blind, late blind and age and gender-matched blindfolded sighted participants were asked to explore the cube faces where little pins were positioned in varying number. Participants were required to explore the cube twice, reporting whether the cube was the same or it differed in pins disposition. Results showed that recognition accuracy was not modulated by the level of visual ability. However, congenitally blind touched more cells simultaneously while exploring the faces and changed more the pattern of touched cells from one recording sample to the next than late blind and sighted. Furthermore, the number of simultaneously touched cells negatively correlated with exploration duration. These findings indicate that early blindness shapes haptic exploration of objects that can be held in hands. (shrink)

Dustin Stokes’s book contributes to one of the continuing debates in empirically informed philosophy of mind and cognitive sciences which concerns the relation between thought and perception. The book sheds new light on such questions as: whether vision is modular, informationally encapsulated, and thus cognitively impenetrable or rather the opposite – whether it is malleable and sensitive to further improvements by cognitive states. Stokes supports the latter by referring to empirical evidence on perceptual expertise. Proponents of the modular and malleable (...) architectures of the mind offer different explanations of the phenomena involved in perceptual expertise, viz. object identification and categorization. Interestingly, both views assume some kind of automaticity of the recognitional capacities for identifying and categorizing objects. In this article, I examine the influence of perceptual expertise on object recognition and how the seeming automaticity of object recognition may be approached from the modularist and antimodularist (malleabilist) perspectives. (shrink)

Nearest-neighbor correlation-based similarity computation in the space of outputs of complex-type receptive elds can support robust recognition of 3D objects. Our experiments with four collections of objects resulted in mean recognition rates between 84% and 94%, over a 40 40 range of viewpoints, centered on a stored canonical view and related to it by rotations in depth. This result has interesting implications for the design of a front end to an arti cial object recognition system, and (...) for the understanding of the faculty of object recognition in primate vision. (shrink)

This commentary reviews recent evidence that some hippo- campal functions do not depend on perirhinal inputs and discusses how the multiple-process model of recognition may shed interpretive light on previous reports of DNMS reacquisition deficits in pretrained subjects with hippocampal damage. Suggestions are made for determining whether nonhuman subjects solve object-recognition tasks using recollective memory or familiarity judgments.

Automatic moving object detection and tracking is very important task in video surveillance applications. In the present work the well known background subtraction model and use of Gaussian Mixture Models have been used to implement a robust automated single object tracking system. In this implementation, background subtraction on subtracting consecutive frame-by-frame basis for moving object detection is done. Once the object has been detected it is tracked by employing an efficient GMM technique. After successful completion of (...) tracking, moving object recognition of those objects using well known Principal Component Analysis, which is used for extracting features and Manhattan based distance metric is used for subsequent classification purpose. The system is capable of handling entry and exit of an object. Such a tracking system is cost effective and can be used as an automated video conferencing system and also has applications like human tracking, vehicles monitoring, and event recognition for video surveillance. The proposed algorithm was tested on standard database on complex environments and the results were satisfactory. (shrink)

Category-specific impairments of object recognition and naming are among the most intriguing disorders in neuropsychology, affecting the retrieval of knowledge about either living or nonliving things. They can give us insight into the nature of our representations of objects: Have we evolved different neural systems for recognizing different categories of object? What kinds of knowledge are important for recognizing particular objects? How does visual similarity within a category influence object recognition and representation? What is the (...) nature of our semantic knowledge about different objects? We review the evidence on category-specific impairments, arguing that deficits even for one class of object cannot be accounted for in terms of a single information processing disorder across all patients; problems arise at contrasting loci in different patients. The same apparent pattern of impairment can be produced by damage to different loci. According to a new processing framework for object recognition and naming, the hierarchical interactive theory, we have a hierarchy of highly interactive stored representations. HIT explains the variety of patients in terms of lesions at different levels of processing and different forms of stored knowledge used both for particular tasks and for particular categories of object. Key Words: category-specific deficits; functional imaging; hierarchical models; interactive activation models; neuropsychology; object recognition; perceptual and functional knowledge. (shrink)

Face recognition is a computationally challenging classification task. Deep convolutional neural networks (DCNNs) are brain‐inspired algorithms that have recently reached human‐level performance in face and object recognition. However, it is not clear to what extent DCNNs generate a human‐like representation of face identity. We have recently revealed a subset of facial features that are used by humans for face recognition. This enables us now to ask whether DCNNs rely on the same facial information and whether this (...) human‐like representation depends on a system that is optimized for face identification. In the current study, we examined the representation of DCNNs of faces that differ in features that are critical or non‐critical for human face recognition. Our findings show that DCNNs optimized for face identification are tuned to the same facial features used by humans for face recognition. Sensitivity to these features was highly correlated with performance of the DCNN on a benchmark face recognition task. Moreover, sensitivity to these features and a view‐invariant face representation emerged at higher layers of a DCNN optimized for face recognition but not for object recognition. This finding parallels the division to a face and an object system in high‐level visual cortex. Taken together, these findings validate human perceptual models of face recognition, enable us to use DCNNs to test predictions about human face and object recognition as well as contribute to the interpretability of DCNNs. (shrink)

Based on theoretical considerations of Aurell (1979) and Block (1995), we argue that object recognition awareness is distinct from purely sensory awareness and that the former is mediated by neuronal activities in areas that are separate and distinct from cortical sensory areas. We propose that two of the principal functions of neuronal activities in sensory cortex, which are to provide sensory awareness and to effect the computations that are necessary for object recognition, are dissociated. We provide (...) examples of how this dissociation might be achieved and argue that the components of the neuronal activities which carry the computations do not directly enter the awareness of the subject. The results of these computations are sparse representations (i.e., vector or distributed codes) which are activated by the presentation of particular sensory objects and are essentially engrams for the recognition of objects. These final representations occur in the highest order areas of sensory cortex; in the visual analyzer, the areas include the anterior part of the inferior temporal cortex and the perirhinal cortex. We propose, based on lesion and connectional data, that the two areas in which activities provide recognition awareness are the temporopolar cortex and the medial orbitofrontal cortex. Activities in the temporopolar cortex provide the recognition awareness of objects learned in the remote past (consolidated object recognition), and those in the medial orbitofrontal cortex provide the recognition awareness of objects learned in the recent past. The activation of the sparse representation for a particular sensory object in turn activates neurons in one or both of these regions of cortex, and it is the activities of these neurons that provide the awareness of recognition of the object in question. The neural circuitry involved in the activation of these representations is discussed. (shrink)

People across the world seek out beautiful sounds in nature, such as a babbling brook or a nightingale song, for positive human experiences. However, it is unclear whether this positive aesthetic response is driven by a preference for the perceptual features typical of nature sounds versus a higher‐order association of nature with beauty. To test these hypotheses, participants provided aesthetic judgments for nature and urban soundscapes that varied on ease of recognition. Results demonstrated that the aesthetic preference for nature (...) soundscapes was eliminated for the sounds hardest to recognize, and moreover the relationship between aesthetic ratings and several measured acoustic features significantly changed as a function of recognition. In a follow‐up experiment, requiring participants to classify these difficult‐to‐identify sounds into nature or urban categories resulted in a robust preference for nature sounds and a relationship between aesthetic ratings and our measured acoustic features that was more typical of easy‐to‐identify sounds. This pattern of results was replicated with computer‐generated artificial noises, which acoustically shared properties with the nature and urban soundscapes but by definition did not come from these environments. Taken together, these results support the conclusion that the recognition of a sound as either natural or urban dynamically organizes the relationship between aesthetic preference and perceptual features and that these preferences are not inherent to the acoustic features. Implications for nature's role in cognitive and affective restoration are discussed. (shrink)