Johns Brendan T, Taler Vanessa, Pisoni David B, Farlow Martin R, Hake Ann Marie, Kareken David A, Unverzagt Frederick W, Jones Michael N
Department of Communicative Disorders and Sciences, University at Buffalo.
School of Psychology, University of Ottawa.
Can J Exp Psychol. 2018 Jun;72(2):117-126. doi: 10.1037/cep0000132. Epub 2017 May 8.
Mild cognitive impairment (MCI) is characterised by subjective and objective memory impairment in the absence of dementia. MCI is a strong predictor for the development of Alzheimer's disease, and may represent an early stage in the disease course in many cases. A standard task used in the diagnosis of MCI is verbal fluency, where participants produce as many items from a specific category (e.g., animals) as possible. Verbal fluency performance is typically analysed by counting the number of items produced. However, analysis of the semantic path of the items produced can provide valuable additional information. We introduce a cognitive model that uses multiple types of lexical information in conjunction with a standard memory search process. The model used a semantic representation derived from a standard semantic space model in conjunction with a memory searching mechanism derived from the Luce choice rule (Luce, 1977). The model was able to detect differences in the memory searching process of patients who were developing MCI, suggesting that the formal analysis of verbal fluency data is a promising avenue to examine the underlying changes occurring in the development of cognitive impairment. (PsycINFO Database Record
轻度认知障碍(MCI)的特征是在没有痴呆的情况下存在主观和客观的记忆障碍。MCI是阿尔茨海默病发展的有力预测指标,在许多情况下可能代表疾病进程的早期阶段。用于诊断MCI的一项标准任务是言语流畅性,即参与者尽可能多地说出特定类别(如动物)中的项目。言语流畅性表现通常通过计算说出的项目数量来分析。然而,对说出的项目的语义路径进行分析可以提供有价值的额外信息。我们引入了一种认知模型,该模型将多种类型的词汇信息与标准的记忆搜索过程结合使用。该模型使用了从标准语义空间模型派生的语义表示,并结合了从卢斯选择规则(Luce,1977)派生的记忆搜索机制。该模型能够检测出正在发展为MCI的患者在记忆搜索过程中的差异,这表明对言语流畅性数据进行形式分析是研究认知障碍发展过程中潜在变化的一个有前景的途径。(PsycINFO数据库记录)