Computational and Behavioral Evidence for Bilingual Aphasia Rehabilitation

描述（由申请人提供）：2010年健康人群方案的目标之一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，尽管这个话题在越来越多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关于双语失语症患者应该训练哪些语言以及康复后跨语言迁移的程度的具体建议。导致该领域研究缺乏的因素与双语个体可能存在的多种语言组合、双语个体的两种语言相对能力以及局灶性脑损伤对双语语言表征的影响有关。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。作为一种潜在的解决方案，拟议的项目将使用计算模型系统地检查康复后跨语言迁移的程度。该模型将用于模拟一个双语语言系统，在该系统中，语言表示可以根据习得年龄和相对熟练程度而变化，随后将进行损伤和再培训，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。我们预测，习得年龄、病前语言熟练程度和病后语言表现水平会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中获得的行为干预数据进行比较。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最大程度的语言恢复。该项目的成功完成有望对脑卒中和双语失语症的康复以及计算建模的应用产生重要影响。这个项目是相关的，因为它将通过比较治疗后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。对双语失语症个体的每一种语言的康复效果的建立是很重要的，因为目前还没有明确的关于双语失语症康复的最佳方法的建议。

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.