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A Computational Evaluation of Two Models of Retrieval Processes in Sentence Processing in Aphasia
Cognitive Science ( IF 2.617 ) Pub Date : 2021-04-20 , DOI: 10.1111/cogs.12956
Paula Lissón 1 , Dorothea Pregla 1 , Bruno Nicenboim 1, 2 , Dario Paape 1 , Mick L van Het Nederend 3 , Frank Burchert 1 , Nicole Stadie 1 , David Caplan 4 , Shravan Vasishth 1
Affiliation  

Can sentence comprehension impairments in aphasia be explained by difficulties arising from dependency completion processes in parsing? Two distinct models of dependency completion difficulty are investigated, the Lewis and Vasishth (2005) activation‐based model and the direct‐access model (DA; McElree, 2000). These models' predictive performance is compared using data from individuals with aphasia (IWAs) and control participants. The data are from a self‐paced listening task involving subject and object relative clauses. The relative predictive performance of the models is evaluated using k‐fold cross‐validation. For both IWAs and controls, the activation‐based model furnishes a somewhat better quantitative fit to the data than the DA. Model comparisons using Bayes factors show that, assuming an activation‐based model, intermittent deficiencies may be the best explanation for the cause of impairments in IWAs, although slowed syntax and lexical delayed access may also play a role. This is the first computational evaluation of different models of dependency completion using data from impaired and unimpaired individuals. This evaluation develops a systematic approach that can be used to quantitatively compare the predictions of competing models of language processing.

中文翻译:

失语症句子加工中两种检索过程模型的计算评价

失语症中的句子理解障碍可以用解析中的依赖完成过程引起的困难来解释吗?研究了两种不同的依赖完成难度模型,Lewis 和 Vasishth(2005)基于激活的模型和直接访问模型(DA;McElree,2000)。这些模型的预测性能使用来自失语症患者 (IWA) 和对照参与者的数据进行比较。数据来自涉及主语和宾语关系从句的自定进度听力任务。模型的相对预测性能使用 k 折交叉验证进行评估。对于 IWA 和对照,基于激活的模型为数据提供了比 DA 更好的定量拟合。使用贝叶斯因子的模型比较表明,假设一个基于激活的模型,间歇性缺陷可能是 IWA 受损原因的最佳解释,尽管缓慢的语法和词汇延迟访问也可能起作用。这是第一次使用来自受损和未受损个体的数据对依赖完成的不同模型进行计算评估。该评估开发了一种系统方法,可用于定量比较语言处理竞争模型的预测。
更新日期:2021-04-21
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