Translation and Clinical Implementation of a Test of Language and Short-term Memory (STM) in Aphasia

近50年来对失语症的研究增加了我们对失语症本质的理解， 指导其补救模式。这些知识大部分来自单个病例或病例系列 语言障碍的研究，这已被用来测试理论的认知和神经基础， 语言，并制定诊断和治疗方案。从这项研究中，失语症的分类有 从对受损语言能力的广泛描述演变而来（例如，命名）与受损神经 区域到语言过程的认知成分的更详细描述（例如，受损的检索 词的语义和语音成分）。这种进步的一个缺点是， 导致更多的独特配置文件，每个组中的成员较少， 完成大规模的失语症及其治疗研究。此外，衡量标准几乎没有一致性， 在这些研究中使用。建立失语症研究科学家合作的网络空间 其补救措施将有助于收集足够的数据，以支持急需的大规模研究， 更精确定义的失语症损害类别，包括随机临床试验（RCT）。它将 还有助于在不同实验室的研究中采用共同的措施。我们的目标是建立一个 在线开源研究空间，科学家可以在语言和沟通方面进行合作 失语症的评估和治疗研究，使数据的汇总，以支持研究， 更大的样本，包括RCT研究。我们是一个领先的研究团队，调查口头短- 术语工作记忆在语言能力中的作用及其在失语症中的损害。因此，我们有（1） 积累了一个与这个研究问题有关的大型数据集，（2）开发了寺庙评估， 失语症的语言和短期记忆（TALSA）以及失语症的新疗法。塔尔萨 提供了一个独特的评估语言能力的条件下增加STM-WM负荷。该数据 基地将用于开始一个开源空间，供科学家与我们的实验室和其他人建立网络， 产生对失语症的语言和认知障碍的研究。在这个项目中，我们将使用NIH- 支持，基于云的架构（希望-健康成果和政策评估平台），以建立一个公开的 可访问的基于云的网络，失语症语言和认知合作研究网络， 核心失语症）。该网络将包括两个实验室和一个资源中心（CORE-REED）， 研究失语症的科学家可以（1）从TALSA数据库（CORE- TALSA）和（2）实施大规模的合作研究，重点是语言和认知的治疗 失语症（核心治疗）。我们预期核心失语症将发展成为一个高度互动的开放科学 网络，可以完成失语症的语言和认知障碍的大规模研究， 多个实验室的合作为共同的研究方案提供数据。

Research on aphasia in the last 50 years has increased our understanding of the nature of aphasia and guided models of its remediation. Much of this knowledge has been gained from single case or case series studies of language impairment, which have been used to test theories of the cognitive and neural bases of language and to develop diagnostic and treatment protocols. From this research, taxonomies of aphasia have evolved from broad descriptions of impaired language abilities (e.g., naming) associated with lesioned neural regions to more detailed descriptions of cognitive components of language processes (e.g., impaired retrieval of semantic and phonological components of words). A downside of this advance is that more precise descriptions of impairment lead to a greater number of unique profiles with fewer members in each group, making it difficult to complete large scale studies of aphasia and its treatment. Additionally, there is little consistency of measures used in these studies. Establishing a network space for collaboration among scientists on studies of aphasia and its remediation would facilitate aggregation of sufficient data to support much needed large scale studies of the more precisely defined categories of aphasic impairment, including randomized clinical trials (RCT). It will also facilitate adoption of common measures across studies in different laboratories. Our aim is to build an online open source research space where scientists can collaborate on language and communication assessment and treatment research in aphasia, enabling the aggregation of data to support studies requiring larger samples, including RCT studies. We are a leading research team investigating the role of verbal short- term-working memory (STM-WM) in language ability and its impairment in aphasia. As such, we have (1) amassed a large dataset relating to this research question and (2) developed the Temple Assessment of Language and Short-term Memory in Aphasia (TALSA) as well as novel treatments for aphasia. The TALSA provides a unique assessment of language abilities under conditions of increased STM-WM load. This data base will be used to begin an open source space for scientists to network with our laboratory and others to generate research on language and cognitive impairments in aphasia. In this project, we will use an NIH- supported, cloud-based architecture (HOPE- Health Outcomes and Policy Evaluation Platform) to build a publicly accessible cloud-based network, Collaborative Research Network on Language and Cognition in Aphasia, CORE-Aphasia). This network will include two laboratories and a resource center (CORE-REED) where scientists who study aphasia can (1) retrieve data from and contribute data to the TALSA database (CORE- TALSA) and (2) implement large scale collaborative studies focused on the treatment of language and cognition in aphasia (CORE-TREAT). We anticipate that CORE-Aphasia will develop into a highly interactive open science network where large scale studies of language and cognitive impairments in aphasia can be completed as collaborations of multiple laboratories contributing data to a common study protocol.