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Resilience in semantic networks: A new approach for studying language impairment in Alzheimer's disease | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، شماره 2، بهمن 2021، صفحه 1563-1566 اصل مقاله (343.97 K) | ||
| نوع مقاله: Brief communications | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.22221.2339 | ||
| نویسندگان | ||
| SomayehSadat HashemiKamangar1؛ Shahriar Gharibzadeh2؛ Fatemeh Bakouie* 1 | ||
| 1Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran | ||
| 2Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Daneshjou Boulevard, District 1, Tehran, Iran | ||
| تاریخ دریافت: 20 آذر 1399، تاریخ بازنگری: 09 دی 1399، تاریخ پذیرش: 08 بهمن 1399 | ||
| چکیده | ||
| Language Impairment in Alzheimer's disease can occur because of deficits in semantic levels of language processing. It can be studied using computational models of language such as complex semantic networks which are strongly related to semantic memory. We hypothesize that the concept of resilience in scale-free semantic networks can truly model and predict semantic language deficit in Alzheimer's disease. We suggest that increasing the variety of words in the lexicon of patients with Alzheimer's disease, improves the resilience of their semantic networks through breakdowns. Moreover, enlarging the size of the semantic networks of patients with Alzheimer's disease can make these networks more resilient. | ||
| کلیدواژه‌ها | ||
| Alzheimer's disease؛ Language Impairment؛ Semantic Networks؛ Resilience | ||
| مراجع | ||
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