Resilience in semantic networks: A new approach for studying language impairment in Alzheimer's disease

Document Type : Brief communications


1 Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran

2 Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Daneshjou Boulevard, District 1, Tehran, Iran


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.


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Volume 12, Issue 2
November 2021
Pages 1563-1566
  • Receive Date: 10 December 2020
  • Revise Date: 29 December 2020
  • Accept Date: 27 January 2021