Three theories currently compete to explain the conceptual deficits that result from brain damage: sensory-functional theory, domain-specific theory, and conceptual structure theory. We argue that all three theories capture important aspects of conceptual deficits, and offer different insights into their origins. Conceptual topography theory (CTT) integrates these insights, beginning with A. R. Damasio’s (1989) convergence zone theory and elaborating it with the similarity-in-topography (SIT) principle. According to CTT, feature maps in sensory-motor systems represent the features of a category’s exemplars. A hierarchical system of convergence zones then conjoins these features to form both property and category representations. According to the SIT principle, the proximity of two conjunctive neurons in a convergence zone increases with the similarity of the features they conjoin. As a result, conjunctive neurons become topographically organised into local regions that represent properties and categories. Depending on the level and location of a lesion in this system, a wide variety of deficits is possible. Consistent with the literature, these deficits range from the loss of a single category to the loss of multiple categories that share sensory-motor properties.

nce is often relative rather than absolute. We conclude that learning to read results in the progressive development of an inferotemporal region increasingly responsive to visual words, which is aptly named the visual word form area (VWFA). D 2004 Elsevier Inc. All rights reserved. Keywords: Word recognition; Occipitotemporal; Specialization Introduction The efficiency of reading in literate adults rests on the ability to quickly identify visual words across large variations of irrelevant parameters such as position, size, color, font, or case. This perceptual expertise requires no less than 5 years of academic training in a specific writing system (Aghababian and Nazir, 2000). The outcome of this perceptual normalization process is an abstract representation of letter identities that has been termed the visual word form (Riesenhuber and Poggio, 1999; Warrington and Shallice, 1980). We formulated the idea that an area in the midportion of the left fusiform gyrus, which activates wh

this paper (see summary in Fig 4), the "preattentive dt " tasks that result in parallel visual search seem to rely on neuronal selectivities present in early visual areas (e.g. orientation, color), while those that result in serial visual search probably rely on higher-level neuronal selectivities (color-orientation conjunctions, animals, faces). These differences in neuronal selectivities are usually accompanied by differences in the size of the neuronal receptive fields (Desimone et al, 1988). Thus we propose that the extent to which our "preattentive dt " features can be discriminated in parallel is an inverse function of the receptive field size of the neurons that represent this feature. At higher levels of the ventral hierarchy, only very few "features" can be processed in parallel, and the corresponding stimuli must be well enough separated to avoid having a target and a distractor falling within a single receptive field. This could explain why a recent study by Rousselet et al (2002) found that 2 natural scenes can be processed in parallel (in an "animal vs. non-animal" Figure 4. Summary of results and hypothesis. A. Two independent dimensions are needed to account for the variety of visual discrimination tasks: one with respect to visual search performance (the "parallel vs

cade (Rensink, O'Regan, & Clark, 1997), or is otherwise masked or hidden from view at the time of the change (e.g., Simons & Levin, 1998). This "change blindness" effect is striking because it seemingly undermines a long-standing assumption in vision science that the visual system constructs a complete and integrated representation of the visual world across glimpses. Furthermore, the effect has been taken to call into question the intuition that perceptual experience directly reflects the nature of the underlying visual representation; instead, change blindness appears to indicate that our experience of a complete and detailed visual world is based on what is in fact a sparse and incomplete visual representation (Dennett, 1991). Recent theoretical treatments of scene perception based on the change blindness effect have converged on two assumptions concerning visual representation. First, all forms of visual representation of a scene element are assumed to be lost once attention is wi

Our mental representation of object categories is hierarchically organized, and our rapid and seemingly effortless categorization ability is crucial for our daily behavior. Here, we examine responses of a large number (>600) of neurons in monkey inferior temporal (IT) cortex with a large number (>1000) of natural and artificial object images. During the recordings the monkeys performed a passive fixation task. We found that the categorical structure of objects is represented by the pattern of activity distributed over the cell population. Animate and inanimate objects created distinguishable clusters in the population code.

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space, and object-space representations in the primate hippocampus. J

This book is about the interface between natural language and the sensorimotor system. It is obvious that there is an interface between language and sensorimotor cognition, because we can talk about what we see and do. The main proposal in the book is that the interface is more direct than is commonly assumed. To argue for this proposal I focus on a simple concrete episode—a man grabbing a cup—which can be reported in a simple transitive sentence (e.g. the English sentence The man grabbed a cup). In the first part of the book I present a detailed model of the sensorimotor processes involved in experiencing this episode, both as the agent bringing it about and as an observer watching it happen. The model draws on a large body of research in neuroscience and psychology. I also present a model of the syntactic structure of the associated transitive sentence, developed within the entirely separate discipline of theoretical linguistics. This latter model is a version of Chomsky’s ‘Minimalist ’ syntactic theory, which assumes that a sentence reporting the episode has the same underlying syntactic structure (called ‘logical form’) regardless of which language it is in. My main proposal is that these two independently motivated models are in fact closely

Abstract — The neocortex appears to be a very efficient, uniformly structured, and hierarchical computational system [25], [23], [24]. Researchers have made significant efforts to model intelligent systems that mimic these neocortical properties to perform a broad variety of pattern recognition and learning tasks. Unfortunately, many of these systems have drifted away from their cortical origins and incorporate or rely on attributes and algorithms that are not biologically plausible. In contrast, this paper describes a model for an intelligent system that is motivated by the properties of cortical columns, which can be viewed as the basic functional unit of the neocortex [35], [16]. Our model extends predictability minimization [30] to mimic the behavior of cortical columns and incorporates neocortical properties such as hierarchy, structural uniformity, and plasticity, and enables adaptive, hierarchical independent feature detection. Initial results for an unsupervised learning task–identifying independent features in image data–are quite promising, both in a single-level and a hierarchical organization modeled after the visual cortex. The model is also able to forget learned patterns that no longer appear in the dataset, demonstrating its adaptivity, resilience, and stability under changing input conditions. I.

Research, 45(13), 1707–1724) reported, in contradiction to several earlier studies, that photographs of human faces can be searched for efficiently (i.e., ‘‘pop out’’) among photographs of other objects (as long as these objects are not ‘‘too similar’ ’ to faces). An apparent search asymmetry between faces and other categories (houses, cars) pointed to the existence of a specialized ‘‘face map’’. Findings of impaired performance for scrambled images were presented as evidence that this face pop out is a high-level, ‘‘holistic’ ’ effect. While the main pop-out effect cannot be disputed, several choices made in that study in terms of experiment design, analysis and interpretation are questionable. After discussing these issues, I report novel experiments which show that (i) the face pop-out effect can be replicated, but under controlled conditions there is no asymmetry between faces and other objects (cars); (ii) inverting pictures and hence disrupting holistic face processing has only a minor effect on search performance; (iii) finally, search becomes inefficient when Fourier amplitude information (which carries global low-level statistical properties of images) is made irrelevant, and only phase information (carrying contour localization) can be used to detect faces. These results imply, contrary to the target article, that the face pop-out effect is mostly based on low-level factors.