Laboratory for Cognition and Neural Stimulation, University of Pennsylvania.
Department of Psychology, Pennsylvania State University.
Neuropsychology. 2024 Jan;38(1):42-57. doi: 10.1037/neu0000924. Epub 2023 Aug 3.
Although language is often considered to be largely intact in multiple sclerosis (MS), word-finding difficulties are a common complaint. Recent work suggests that declines in language are not solely the result of motoric and cognitive slowing that is most strongly associated with MS. Network science approaches have been effectively used to examine network structure as it relates to clinical conditions, aging, and language. The present study utilizes a network science approach to investigate whether individuals with MS exhibit less interconnected and resilient semantic networks compared to age-matched neurotypical peers.
We used semantic fluency data from 89 participants with MS and 88 neurotypical participants to estimate and analyze the semantic network structure for each participant group. Additionally, we conducted a percolation analysis to examine the resilience of each network.
Network measures showed that individuals with MS had lower local and global clustering coefficients, longer average shortest path lengths, and higher modularity values compared to neurotypical peers. Small-worldness, network portrait divergence measures, and community detection analyses were consistent with these results and indicated that macroscopic properties of the two networks differed and that the semantic network for individuals with MS was more fractured than the neurotypical peer network. Moreover, a spreading activation simulation and percolation analysis suggested that the semantic networks of individuals with MS are less flexible and activation degrades faster than those of age-matched neurotypical participants.
These differing semantic network structures suggest that language retrieval difficulties in MS partially result from decline in language-specific factors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
尽管语言在多发性硬化症（MS）中通常被认为基本完整，但找词困难是常见的主诉。最近的研究表明，语言的衰退不仅仅是与 MS 最密切相关的运动和认知减速的结果。网络科学方法已被有效地用于研究网络结构与临床状况、衰老和语言的关系。本研究采用网络科学方法，调查与年龄匹配的神经典型同龄人相比，MS 患者是否表现出语义网络连接性降低和弹性降低。
我们使用 89 名 MS 患者和 88 名神经典型参与者的语义流畅性数据来估计和分析每个参与者组的语义网络结构。此外，我们进行了渗流分析以检查每个网络的弹性。
网络指标表明，与神经典型同龄人相比，MS 患者的局部和全局聚类系数较低，平均最短路径长度较长，模块度值较高。小世界性、网络肖像发散度测量和社区检测分析与这些结果一致，表明两个网络的宏观性质不同，MS 患者的语义网络比神经典型患者的网络更破碎。此外，扩散激活模拟和渗流分析表明，MS 患者的语义网络灵活性较低，激活退化速度比年龄匹配的神经典型参与者快。
这些不同的语义网络结构表明，MS 中的语言检索困难部分是由于语言特定因素的下降所致。
