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 i s 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.
Research on the cognitive-linguistic foundations of aphasia traditionally relies on research designs with small sample sizes, such as single case or case series studies. Our aim is to create a cloud-based open science environment for scientists to collaborate, which will enable aggregation of data from many labs. This increase in power will add to the validity of research on treatment efficacy and models of aphasia rehabilitation.
| Martin, Nadine; Minkina, Irene; Kohen, Francine P et al. (2018) Assessment of linguistic and verbal short-term memory components of language abilities in aphasia. J Neurolinguistics 48:199-225 |
