Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308779
Title: Connectionist architectures for language disorder simulation
Author: Wright, John F.
ISNI:       0000 0001 2448 0828
Awarding Body: University of Surrey
Current Institution: University of Surrey
Date of Award: 1995
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Abstract:
Our interdisciplinary research focuses on the application of connectionist modelling techniques to the study of language disorders. In recent years, artificial neural network models of aphasia have enabled cognitive neuropsychologists to explore contemporary theories of language processing. Such work may, in the future, lead to the development of innovative strategies for the rehabilitation of brain-damaged patients. The aim of our work has been to analyse the modelling techniques employed in existing connectionist accounts of language disorders, and, on the basis of our findings, to propose novel and computationally well-grounded architectures which may be used to explore cognitive neuropsychological theories. The majority of connectionist language disorder models reported in the literature may be categorised as network-level models, consisting of a single homogeneous structure built from identical processing elements. We believe that in order to simulate more fully the complexity of human language processing, it may be necessary to move away from this approach, in favour of nervous system-level models, in which a number of network-level models are interconnected to form a modular connectionist architecture. The suitability of these architectures for language disorder simulation has been assessed through the construction of LISA: a Language Impairment Simulation Architecture. LISA comprises a number of linked connectionist networks which have been collectively trained to simulate object naming and word repetition. By lesioning one or more components of our modular system, it is possible to simulate the impaired language production of an aphasic patient. We present our attempts to simulate an acquired disorder of repetition, deep dysphasia, and a progressive disorder, semantic dementia, using LISA. The results of our experiments are encouraging, and lead us to conclude that the cognitive neuropsychology community may indeed benefit from the use of modular connectionist architectures in the simulation of both progressive and acquired language disorders.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.308779  DOI: Not available
Keywords: Bionics
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