One goal of the Healthy People 2010 program is to reduce health disparities across different segments of the population. Diagnosis and treatment of bilingual aphasia is one area where disparities continue to exist even though this topic is of great importance in an increasingly bilingual world. The current research on this topic, however, lacks specific recommendations on which languages should be trained in a bilingual aphasic individual and to what extent cross-language transfer occurs subsequent to rehabilitation. Factors contributing to the paucity of research in this area relate to the multitude of possible language combinations in a bilingual individual, the relative competency of the two languages of the bilingual individual and the effect of focal brain damage on bilingual language representation. It is, however, unfeasible to examine these issues without undertaking a large scale longitudinal study in this population. As a potential solution, the proposed project will systematically examine the extent of cross-language transfer subsequent to rehabilitation using a computational model. This model will be developed to simulate a bilingual language system in which language representations can vary by age of acquisition and relative proficiency, and will be subsequently lesioned and retrained to improve output. The training will be provided in one language and the extent of cross-language transfer will be examined. It is predicted that age of acquisition, the level of pre-morbid language proficiency and post-morbid language performance will influence the nature and degree of cross-language transfer. Further, the model's power to predict the optimal language to be treated will be compared to data obtained from behavioral interventions from a sample of patients with bilingual aphasia. The proposed work is innovative, because it uses a computational model to predict optimal rehabilitation protocols to facilitate the greatest amount of language recovery in bilingual aphasia. The successful completion of this project is expected to have an important impact on rehabilitation of stroke and bilingual aphasia as well as on the applications of computational modeling.

Public Health Relevance

This project is relevant because it will address the important issue of language recovery following treatment in bilingual aphasic individuals by comparing performance in treated bilingual aphasic individuals with the performance of a computational model simulating aphasia in a bilingual lexicon. Establishment of the efficacy of rehabilitation in each of the languages of the bilingual aphasic individual is important because there are currently no clear recommendations on the best approach for rehabilitation of bilingual aphasia.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DC009446-02
Application #
7738509
Study Section
Language and Communication Study Section (LCOM)
Program Officer
Cooper, Judith
Project Start
2008-12-01
Project End
2011-11-30
Budget Start
2009-12-01
Budget End
2011-11-30
Support Year
2
Fiscal Year
2010
Total Cost
$180,460
Indirect Cost
Name
University of Texas Austin
Department
Other Health Professions
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
Kiran, Swathi; Balachandran, Isabel; Lucas, Jason (2014) The nature of lexical-semantic access in bilingual aphasia. Behav Neurol 2014:389565
Kiran, Swathi; Sandberg, Chaleece; Gray, Teresa et al. (2013) Rehabilitation in bilingual aphasia: evidence for within- and between-language generalization. Am J Speech Lang Pathol 22:S298-309
Kiran, Swathi; Grasemann, Uli; Sandberg, Chaleece et al. (2013) A Computational Account of Bilingual Aphasia Rehabilitation. Biling (Camb Engl) 16:325-342
Gray, Teresa; Kiran, Swathi (2013) A theoretical account of lexical and semantic naming deficits in bilingual aphasia. J Speech Lang Hear Res 56:1314-27
Hoffman, Ralph E; Grasemann, Uli; Gueorguieva, Ralitza et al. (2011) Using computational patients to evaluate illness mechanisms in schizophrenia. Biol Psychiatry 69:997-1005
Grasemann, Uli; Sandberg, Chaleece; Kiran, Swathi et al. (2011) Impairment and Rehabilitation in Bilingual Aphasia: A SOM-Based Model. Lect Notes Comput Sci 6731:207-217
Miikkulainen, Risto; Kiran, Swathi (2009) Modeling the Bilingual Lexicon of an Individual Subject. Lect Notes Comput Sci 5629:191-199