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S L Small

Publications and source records attributed to S L Small.

26 records · Page 2Linked to original sources
PubMed1995

Distributed representations of semantic knowledge in the brain.

Category-specific language impairments have been postulated to require the existence of an explicit category organization within semantic memory. However, it may be possible to demonstrate analytically that this is not necessary. We hypothesize that category-specific organization can emerge from perceptual, functional, and associative feature information about objects that is maintained in order to process language. In this paper, we conduct several experiments to test the computational validity of this hypothesis. Physical objects were encoded in terms of semantic features, based on basic perceptual and motor modalities and higher level knowledge of function, for use in artificial neural networks. Mathematical methods were used to analyse the encodings and the neural networks. The results demonstrate the emergence of semantic categories in the networks, although such information was not preprogrammed. We conclude that category-specific language organization can emerge from the inherent nature of semantic features themselves, and does not require special internal categorical organization of semantic memory.

Brain↗
PubMed1994

Connectionist networks and language disorders.

Although neuropsychological localization constitutes the principal approach to the study of language disorders, there is reason to think it may not be entirely correct. Recent anatomical studies suggest that cognitive brain functions do not localize to precise anatomical locations. Connectionist (parallel distributed processing) approaches to the study of language, which emphasize the distributed nature of computational processes, may help explain the variability found in these anatomical studies, and provide a new way to approach the neurological study of language. This combined computational and empirical method focuses on the interplay between a computational model and the appropriate neurological, neuropsychological, and speech and language data, the whole couched in connectionist mechanisms that map naturally to what is known of the neurophysiological structure of the brain. This paper introduces the concepts of connectionist modeling, with emphasis on their use in understanding language disorders.

Brain↗
PubMed1994

Pharmacotherapy of aphasia. A critical review.

BACKGROUND: Communication problems are a common sequela of cerebrovascular disease and other central nervous system disorders. Behavioral treatment of these disorders aims to harness uninjured parts of the brain to improve the communicative life of the individual. While pharmacotherapy has held promise for the treatment of aphasia for over 50 years, it has not fulfilled this promise. This article reviews both the promise and the disappointment of aphasia pharmacotherapy. SUMMARY OF REVIEW: Diverse theories of the underlying neurological deficits in aphasia have led to different pharmacologic rationales for therapy. Animal studies have demonstrated decreased levels of brain catecholamines after cortical stroke and more rapid stroke recovery with therapy aimed at augmenting brain norepinephrine and dopamine. These studies have led to recent attempts to hasten or extend language and sensorimotor rehabilitation after human stroke by administration of catecholaminergic drugs. When used as an adjunct to behavioral therapy, such pharmacotherapy appears to have benefit. CONCLUSIONS: While drug therapy is unlikely to revolutionize the treatment of aphasia, it nonetheless holds promise as an adjunct to behavioral speech and language therapy to decrease performance variability and consequently to improve mean performance in patients with mild to moderate language dysfunction. Additional studies with carefully designed methods are necessary to assess the full potential of aphasia pharmacotherapy.

Animals↗
PubMed1989

Heuristic determination of relevant diagnostic procedures in a medical expert system for gynecology.

Many professions including medicine have standard operating procedures for the performance of their tasks. In the construction of expert systems, knowledge engineers have exploited this fact in devising heuristic rules that mimic the standard practice among such personnel (i.e., experts). This article suggests that the expert system designer should not stop at the level of the standard operating procedure heuristic but should instead investigate the reasons that the standard procedures have become standard. Because the experts in a field often do not understand the reasons for the standard operating procedures of their profession, this effort not only rewards the system designer but the expert as well. Because medical training does not always emphasize the logical reasoning underlying certain standard operating procedures, the ability to perform this reasoning is especially important in medicine. Further, a medical expert system for consultation or education would make a valuable impact by incorporating such knowledge and inference rules. This article investigates the development of a computerized medical expert system that applies the principles of artificial intelligence by limiting the number of questions and tests to find the solution for an ill-defined complex problem. Finally, we describe a logic program that tests the basic ideas.

Artificial Intelligence↗
PubMedDate not supplied

A model of ocular dominance column development by competition for trophic factor: effects of excess trophic factor with monocular deprivation and effects of antagonist of trophic factor.

Recent experimental evidence has implicated neurotrophic factors (NTs) in the competitive process believed to drive the development of ocular dominance (OD) columns. Application of excess amounts of particular NTs can prevent the segregation process, suggesting that they could be the substance for which geniculocortical afferents compete during development. We have previously presented a model that accounts for normal OD development as well as the prevention of that development with excess NT. The model uses a Hebbian learning rule in combination with competition for a limiting supply of cortical trophic factor to drive OD segregation, without any weight normalization procedures. Subsequent experimental evidence has further suggested that NTs may be causally involved in the competitive process. Application of NT antagonist can prevent OD columns by causing inputs from both eyes to be eliminated, suggesting that NTs may be the substance for which geniculocortical afferents compete. Also, excess NT can mitigate the shift to the open eye normally caused by monocular deprivation (MD). In this article, we show that the current model can account for these subsequent experiments. We show that deprivation of NT causes inputs from both eyes to decay and that excess NT can mitigate the shift to the open eye normally seen with MD. We then present predictions of the model concerning the effects of NT on the length of the critical period during which MD is effective. The model presents a novel mechanism for competition between neural populations inspired by particular biological evidence. It accounts for three specific experimental results, and provides several testable predictions.

Age Factors↗