Literature DB >> 34262122

Unveiling the nature of interaction between semantics and phonology in lexical access based on multilayer networks.

Orr Levy1, Yoed N Kenett2, Orr Oxenberg3, Nichol Castro4, Simon De Deyne5, Michael S Vitevitch6, Shlomo Havlin3.   

Abstract

An essential aspect of human communication is the ability to access and retrieve information from ones' 'mental lexicon'. This lexical access activates phonological and semantic components of concepts, yet the question whether and how these two components relate to each other remains widely debated. We harness tools from network science to construct a large-scale linguistic multilayer network comprising of phonological and semantic layers. We find that the links in the two layers are highly similar to each other and that adding information from one layer to the other increases efficiency by decreasing the network overall distances, but specifically affecting shorter distances. Finally, we show how a multilayer architecture demonstrates the highest efficiency, and how this efficiency relates to weak semantic relations between cue words in the network. Thus, investigating the interaction between the layers and the unique benefit of a linguistic multilayer architecture allows us to quantify theoretical cognitive models of lexical access.
© 2021. The Author(s).

Entities:  

Year:  2021        PMID: 34262122     DOI: 10.1038/s41598-021-93925-y

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  21 in total

1.  When SOFA primes TOUCH: interdependence of spelling, sound, and meaning in "semantically mediated" phonological priming.

Authors:  W T Farrar; G C Van Orden; V Hamouz
Journal:  Mem Cognit       Date:  2001-04

Review 2.  Stages of lexical access in language production.

Authors:  G S Dell; P G O'Seaghdha
Journal:  Cognition       Date:  1992-03

Review 3.  Networks in cognitive science.

Authors:  Andrea Baronchelli; Ramon Ferrer-i-Cancho; Romualdo Pastor-Satorras; Nick Chater; Morten H Christiansen
Journal:  Trends Cogn Sci       Date:  2013-05-30       Impact factor: 20.229

4.  The "Small World of Words" English word association norms for over 12,000 cue words.

Authors:  Simon De Deyne; Danielle J Navarro; Amy Perfors; Marc Brysbaert; Gert Storms
Journal:  Behav Res Methods       Date:  2019-06

Review 5.  Using network science in the language sciences and clinic.

Authors:  Michael S Vitevitch; Nichol Castro
Journal:  Int J Speech Lang Pathol       Date:  2014-12-24       Impact factor: 2.484

6.  How do associative and phonemic overlap interact to boost illusory recollection?

Authors:  Keith A Hutchison; Michelle L Meade; Nikolas S Williams; Krista D Manley; Jaimie C McNabb
Journal:  Memory       Date:  2017-10-24

Review 7.  The structure and dynamics of multilayer networks.

Authors:  S Boccaletti; G Bianconi; R Criado; C I Del Genio; J Gómez-Gardeñes; M Romance; I Sendiña-Nadal; Z Wang; M Zanin
Journal:  Phys Rep       Date:  2014-07-10       Impact factor: 25.600

Review 8.  Local Patterns to Global Architectures: Influences of Network Topology on Human Learning.

Authors:  Elisabeth A Karuza; Sharon L Thompson-Schill; Danielle S Bassett
Journal:  Trends Cogn Sci       Date:  2016-06-29       Impact factor: 20.229

9.  Multiplex model of mental lexicon reveals explosive learning in humans.

Authors:  Massimo Stella; Nicole M Beckage; Markus Brede; Manlio De Domenico
Journal:  Sci Rep       Date:  2018-02-02       Impact factor: 4.379

10.  Multiplex lexical networks reveal patterns in early word acquisition in children.

Authors:  Massimo Stella; Nicole M Beckage; Markus Brede
Journal:  Sci Rep       Date:  2017-04-24       Impact factor: 4.379

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  2 in total

Review 1.  Knowledge Representations Derived From Semantic Fluency Data.

Authors:  Jeffrey C Zemla
Journal:  Front Psychol       Date:  2022-03-11

2.  Brands, networks, communities: How brand names are wired in the mind.

Authors:  László Kovács; András Bóta; László Hajdu; Miklós Krész
Journal:  PLoS One       Date:  2022-08-25       Impact factor: 3.752

  2 in total

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