Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation

描述（由申请人提供）：2010年健康人计划的一个目标是减少不同人群的健康差距。双语失语症的诊断和治疗是一个领域的差距继续存在，即使这一主题是非常重要的，在一个日益双语的世界。然而，目前关于这一主题的研究缺乏具体的建议，哪些语言应该在双语失语症患者中进行训练，以及在多大程度上跨语言迁移发生在康复之后。在这一领域的研究不足的因素涉及到众多的可能的语言组合在一个双语的个人，双语的个人的两种语言的相对能力和局部脑损伤对双语语言的代表性的影响。然而，如果不对这一人群进行大规模的纵向研究，就不可能检查这些问题。作为一个潜在的解决方案，拟议的项目将使用计算模型系统地检查康复后的跨语言迁移的程度。这个模型将被开发来模拟一个双语语言系统，在这个系统中，语言表征可以根据习得年龄和相对熟练程度而变化，并且随后将被损伤和再训练以提高输出。培训将以一种语文提供，并将审查跨语文迁移的程度。据预测，习得年龄、病前语言水平和病后语言表现将影响跨语言迁移的性质和程度。此外，该模型预测最佳语言治疗的能力将与从双语失语症患者样本的行为干预中获得的数据进行比较。这项工作是创新的，因为它使用了一个计算模型来预测最佳的康复方案，以促进双语失语症的语言恢复的最大量。该项目的成功完成对脑卒中和双语失语症的康复以及计算机建模的应用具有重要意义。公共卫生相关性这个项目是相关的，因为它将通过比较治疗的双语失语症患者的表现与在双语词典中模拟失语症的计算模型的表现，来解决双语失语症患者治疗后语言恢复的重要问题。建立双语失语症患者每种语言的康复效果是很重要的，因为目前还没有明确的建议双语失语症的最佳康复方法。

DESCRIPTION (provided by applicant): 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.