There has been a proliferation of proposed mental modules in an attempt to account for different cognitive functions but so far there has been no successful account of their integration. ACT-R (Anderson & Lebiere, 1998) has evolved into a theory that consists of multiple modules but also explains how they are integrated to produce coherent cognition. The perceptual-motor modules, the goal module, and the declarative memory module are presented as examples of specialized systems in ACT-R. These modules are associated with distinct cortical regions. These modules place chunks in buffers where they can be detected by a production system that responds to patterns of information in the buffers. At any point in time a single production rule is selected to respond to the current pattern. Subsymbolic processes serve to guide the selection of rules to fire as well as the internal operations of some modules. Much of learning involves tuning of these subsymbolic processes. Empirical examples are presented that illustrate the predictions of ACT-R’s modules. In addition, two models of complex tasks are described to illustrate how these modules result in strong predictions when they are brought together. One of these models is concerned with complex patterns of behavioral data in a dynamic task and the other is concerned with fMRI data obtained in a study of symbol manipulation.

It is demonstrated how a modality-specific semantic memory system can account for category-specific impairments after brain damage. In Experiment 1, the hypothesis that visual and functional knowledge play different roles in the representation of living things and nonliving things is tested and confirmed. A parallel distributed processing model of semantic memory in which knowledge is subdivided by modality into visual and functional components is described. In Experiment 2, the model is lesioned, and it is confirmed that damage to visual semantics primarily impairs knowledge of living things, and damage to functional semantics primarily impairs knowledge of non!iving things. In Experiment 3, it is demonstrated that the model accounts naturally for a finding that had appeared problematic for a modality-specific architec-ture, namely, impaired retrieval of functional knowledge about living things. Finally, in Experiment 4, it is shown how the model can account for a recent observation of impaired knowledge of living things only when knowledge is probed verbally.

Many theorists assume that the cognitive system is composed of a collection of encapsulated processing components or modules, each dedicated to performing a particular cognitive function. On this view, selective impairments of cognitive tasks following brain damage, as evidenced by double dissociations, are naturally interpreted in terms of the loss of particular processing components. By contrast, the current investigation examines in detail a double dissociation between concrete and abstract word reading after damage to a connectionist network that pronounces words via meaning and yet has no separable components (Plaut & Shallice, 1993). The functional specialization in the network that gives rise to the double dissociation is not transparently related to the network's structure, as modular theories assume. Furthermore, a consideration of the distribution of effects across quantitatively equivalent individual lesions in the network raises specific concerns about the interpretation of...

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.

Although perseveration---the inappropriate repetition of previous responses---is quite common among patients with neurological damage, relatively few detailed computational accounts of its various forms have been put forth. A particularly well-documented variety involves the pattern of errors made by "optic aphasic" patients, who have a selective deficit in naming visually-presented objects. Based on our previous work in modeling impaired reading for meaning in deep dyslexia, we develop a connectionist simulation of visual object naming. The major extension in the present work is the incorporation of short-term correlational weights that bias the network towards reproducing patterns of activity that have occurred on recently preceding trials. Under damage, the network replicates the complex semantic and perseverative effects found in the optic aphasic error pattern. Further analysis reveals that the perseverative effects are strongest when the lesions are near or within semanti...

We present a new account of the fine-grained structure of semantic categories derived from neuropsychological, behavioral, and developmental data. The account places theoretical emphasis on the functions of the referents of concepts. We claim (i) that the distinctiveness of functional features correlated with perceptual features varies across semantic domains; and (ii) that category structure emerges from the complex interaction of these variables. The representational assumptions that follow from these claims make strong predictions about what types of semantic information are preserved in patients showing category-specific deficits following brain damage. These claims are illustrated with a connectionist simulation which, when damaged, shows patterns of preservation of distinctive and shared functional and perceptual information which varies across semantic domains. The data model both dissociations between knowledge for artifacts and for living things and recent neuropsychological evidence concerning the robustness of functional information in the representation of concepts. © 2000 Academic Press

& Neuropsychological research showing that the regular (‘‘jump–jumped’’) and irregular (‘‘drive/drove’’) past tense inflectional morphology can dissociate following brain damage has been important in testing claims about the cognitive and neural status of linguistic rules. These dissociations have been interpreted as evidence for two different computational systems—a rule-based system underlying the processing of regulars and the irregulars being individually listed in the mental lexicon. In contrast, connectionist accounts claim that these dissociations can be modeled within a single system. Combining behavioral data from patients with detailed information about their neuropathology can, in principle, provide strong constraints on accounts of the past tense. In this study, we tested five nonfluent aphasic patients, all of whom had extensive left hemisphere (LH) damage involving the left inferior frontal gyrus and underlying structures, and four patients with semantic deficits following herpes simplex encephalitis (HSE) who had extensive damage to the inferior temporal cortex. These patients were tested in experiments probing past tense processing. In a large priming study, the nonfluent patients showed no priming for the regular past tense but significant priming for the irregulars (whereas controls show priming for both). In contrast, the HSE patients showed significantly impaired performance for the irregulars in an elicitation task. These patterns of behavioral data and neuropathology suggest that two separable but interdependent systems underlie processing of the regular and irregular past tense. &

Findings in the social psychology literatures on attitudes, social perception, and emotion demonstrate that social information processing involves embodiment, where embodiment refers both to actual bodily states and to simulations of experience in the brain’s modality-specific systems for perception, action, and introspection. We show that embodiment underlies social information processing when the perceiver interacts with actual social objects (online cognition) and when the perceiver represents social objects in their absence (offline cognition). Although many empirical demonstrations of social embodiment exist, no particularly compelling account of them has been offered. We propose that theories of embodied cognition, such as the Perceptual Symbol Systems (PSS) account (Barsalou, 1999), explain and integrate these findings, and that they also suggest exciting new directions for research. We compare the PSS account to a variety of related proposals and show how it addresses criticisms that have previously posed problems for the general embodiment approach. Consider the following findings. Wells and Petty (1980) reported that nodding the head (as in agreement)

This article is about how the brain data mines its sensory inputs. There are several architectural principles of functional brain anatomy that have emerged from careful anatomic and physiologic studies over the past century. These principles are considered in the light of representational learning to see if they could have been predicted a priori on the basis of purely theoretical considerations. We first review the organisation of hierarchical sensory cortices, paying special attention to the distinction between forward and backward connections. We then review various approaches to representational learning as special cases of generative models, starting with supervised learning and ending with learning based upon empirical Bayes. The latter predicts many features, such as a hierarchical cortical system, prevalent top-down backward influences and functional asymmetries between forward and backward connections that are seen in the real brain. The key points made in this article are: (i) hierarchical generative models enable the learning of empirical priors and eschew prior assumptions about the causes of sensory input that are inherent in non-hierarchical models. These assumptions are necessary for learning schemes based on information theory and efficient or sparse coding, but are not necessary in a hierarchical context. Critically, the anatomical infrastructure that may implement generative models in the brain is hierarchical. Furthermore, learning based on empirical Bayes can proceed in a biologically plausible way. (ii) The second point is that backward connections are essential if the processes generating inputs cannot be inverted, or the inversion cannot be parameterised. Because these processes involve many-to-one mappings, are non-linear and dynamic in nature, they are generally non-invertible. This enforces an explicit parameterisation of generative models (i.e. backward

Is our knowledge about the appearance of objects more closely related to verbal thought or to perception? In a behavioural study using a property verification task, Kosslyn (1976) reported that there are both amodal and perceptual representations of concepts, but that amodal representations may be more easily accessed. However, Solomon (1997) argued that due to the nature of Kosslyn’s stimuli, subjects may be able to bypass semantics entirely and perform this task using differences in the strength of association between words in true trials (e.g., cat–whiskers) and those in false trials (e.g., mouse–stinger). Solomon found no evidence for amodal representations when the task materials were altered to include associated false trials (e.g., cat–litter), which require semantic processing, as opposed to associative strategies. In the current study, we used fMRI to examine the response of regions of visual association cortex while subjects performed a property verification task with either associated or unassociated false trials. We found reliable activity across subjects within the left fusiform gyrus when true trials were intermixed with associated false trials but not when true trials were intermixed with unassociated false trials. Our data support the idea that conceptual knowledge is organised visually and that it is grounded in the perceptual system. One of the leading theories of the organisation of