Accounting for word production, comprehension, and repetition in semantic dementia, Alzheimer’s dementia, and mild cognitive impairment

IF 2.1 2区 心理学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY Brain and Language Pub Date : 2023-03-01 DOI:10.1016/j.bandl.2023.105243
Ardi Roelofs
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引用次数: 3

Abstract

It has been known since Pick (1892, 1904) that word retrieval is commonly impaired in left temporal lobe degeneration. Individuals with semantic dementia (SD), Alzheimer’s dementia (AD), and mild cognitive impairment (MCI) present with word retrieval difficulty, while comprehension is less affected and repetition is preserved. Whereas computational models have elucidated performance in poststroke and progressive aphasias, including SD, simulations are lacking for AD and MCI. Here, the WEAVER++/ARC model, which has provided neurocognitive computational accounts of poststroke and progressive aphasias, is extended to AD and MCI. Assuming a loss of activation capacity in semantic memory in SD, AD, and MCI, the simulations showed that severity variation accounts for 99% of the variance in naming, comprehension, and repetition at the group level and 95% at the individual patient level (N = 49). Other plausible assumptions do less well. This supports a unified account of performance in SD, AD, and MCI.

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在语义性痴呆、阿尔茨海默氏痴呆和轻度认知障碍中计算单词的产生、理解和重复
自Pick(18921904)以来,人们就知道单词检索通常在左颞叶退化中受损。患有语义痴呆(SD)、阿尔茨海默氏症(AD)和轻度认知障碍(MCI)的个体存在单词检索困难,而理解受到的影响较小,重复性也得到了保留。尽管计算模型已经阐明了卒中后和进行性失语症的表现,包括SD,但缺乏AD和MCI的模拟。在这里,WEAVER++/ARC模型提供了脑卒中后和进行性失语症的神经认知计算说明,并扩展到AD和MCI。假设SD、AD和MCI的语义记忆激活能力丧失,模拟显示,在组水平上,严重程度差异占命名、理解和重复差异的99%,在个体患者水平上占95%(N=49)。其他看似合理的假设效果不佳。这支持SD、AD和MCI中性能的统一说明。
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来源期刊
Brain and Language
Brain and Language 医学-神经科学
CiteScore
4.50
自引率
8.00%
发文量
82
审稿时长
20.5 weeks
期刊介绍: An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.
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