Dementia is a common and debilitating condition that typically gives rise to increasing language impairment. There is a need to understand the nature of this impairment further so that therapies may be developed, particularly in the case of bilinguals. This paper extends BiLex, an existing computational model of bilingual lexical access, to simulate language decline in dementia. Six lesion types are evaluated for their ability to reproduce the pattern of decline in the semantic variant primary progressive aphasia (svPPA) subtype of dementia. Semantic memory lesions reproduce this pattern of decline best in monolinguals, and further suggest patterns that are likely to be found in longitudinal data from bilingual dementia patients in the future.

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In Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022.

@inproceedings{fidelman:cogsci22, title={Constructing Individualized Computational Models for Dementia Patients}, author={Peggy Fidelman and Uli Grasemann and Claudia Penaloza and Michael Scimeca and Yakeel T. Quiroz and Swathi Kiran and Risto Miikkulainen}, booktitle={Proceedings of the 44th Annual Meeting of the Cognitive Science Society}, month={ }, url="http://nn.cs.utexas.edu/?fidelman:cogsci22", year={2022} }

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