Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation

描述(由申请者提供)：2010年健康人计划的一个目标是减少不同人群之间的健康差距。双语失语症的诊断和治疗是一个仍然存在差异的领域，尽管这一主题在日益增长的双语世界中非常重要。然而，目前关于这一主题的研究缺乏具体的建议，即双语失语症患者应该接受哪些语言的培训，以及康复后跨语言迁移发生的程度。导致这一领域研究匮乏的因素涉及双语个体的多种可能的语言组合，双语个体两种语言的相对能力，以及局灶性脑损伤对双语语言表征的影响。然而，如果不在这一人群中进行大规模的纵向研究，研究这些问题是不可行的。作为一种潜在的解决办法，拟议的项目将使用计算模型系统地审查康复后跨语言迁移的程度。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，语言表征可以随着习得年龄和相对熟练程度的不同而变化，随后将进行学习和再培训，以提高输出。培训将以一种语言提供，并将审查跨语言迁移的程度。据预测，习得年龄、病前语言水平和病后语言表现会影响跨语言迁移的性质和程度。此外，该模型预测最佳治疗语言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。这项拟议的工作是创新的，因为它使用计算模型来预测最优的康复方案，以促进双语失语症的最大程度的语言恢复。该项目的成功完成预计将对中风和双语失语的康复以及计算模型的应用产生重要影响。公共卫生相关性这个项目之所以重要，是因为它将通过比较接受治疗的双语失语症患者的表现与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。确定双语失语症患者每种语言的康复效果很重要，因为目前还没有关于双语失语症康复的最佳方法的明确建议。

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.