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The Resilience of the Phonological Network May Have Implications for Developmental and Acquired Disorders

  • Michael S. Vitevitch
  • , Nichol Castro
  • , Gavin J.D. Mullin
  • , Zoe Kulphongpatana
  • University of Kansas

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

A central tenet of network science states that the structure of the network influences processing. In this study of a phonological network of English words we asked: how does damage alter the network structure (Study 1)? How does the damaged structure influence lexical processing (Study 2)? How does the structure of the intact network “protect” processing with a less efficient algorithm (Study 3)? In Study 1, connections in the network were randomly removed to increasingly damage the network. Various measures showed the network remained well-connected (i.e., it is resilient to damage) until ~90% of the connections were removed. In Study 2, computer simulations examined the retrieval of a set of words. The performance of the model was positively correlated with naming accuracy by people with aphasia (PWA) on the Philadelphia Naming Test (PNT) across four types of aphasia. In Study 3, we demonstrated another way to model developmental or acquired disorders by manipulating how efficiently activation spread through the network. We found that the structure of the network “protects” word retrieval despite decreases in processing efficiency; words that are relatively easy to retrieve with efficient transmission of priming remain relatively easy to retrieve with less efficient transmission of priming. Cognitive network science and computer simulations may provide insight to a wide range of speech, language, hearing, and cognitive disorders.

Original languageEnglish
Article number188
JournalBrain Sciences
Volume13
Issue number2
DOIs
StatePublished - Feb 2023

Keywords

  • aphasia
  • computer simulation
  • network science
  • phonological network
  • resilience

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