Literature DB >> 32831584

Contributions of modern network science to the cognitive sciences: revisiting research spirals of representation and process.

Nichol Castro1, Cynthia S Q Siew2.   

Abstract

Modelling the structure of cognitive systems is a central goal of the cognitive sciences-a goal that has greatly benefitted from the application of network science approaches. This paper provides an overview of how network science has been applied to the cognitive sciences, with a specific focus on the two research 'spirals' of cognitive sciences related to the representation and processes of the human mind. For each spiral, we first review classic papers in the psychological sciences that have drawn on graph-theoretic ideas or frameworks before the advent of modern network science approaches. We then discuss how current research in these areas has been shaped by modern network science, which provides the mathematical framework and methodological tools for psychologists to (i) represent cognitive network structure and (ii) investigate and model the psychological processes that occur in these cognitive networks. Finally, we briefly comment on the future of, and the challenges facing, cognitive network science.
© 2020 The Author(s).

Entities:  

Keywords:  cognitive processes; cognitive science; cognitive structures; mental lexicon; mental representations; network science

Year:  2020        PMID: 32831584      PMCID: PMC7428042          DOI: 10.1098/rspa.2019.0825

Source DB:  PubMed          Journal:  Proc Math Phys Eng Sci        ISSN: 1364-5021            Impact factor:   2.704


  76 in total

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Journal:  Behav Res Methods       Date:  2005-11

Review 3.  Maps of random walks on complex networks reveal community structure.

Authors:  Martin Rosvall; Carl T Bergstrom
Journal:  Proc Natl Acad Sci U S A       Date:  2008-01-23       Impact factor: 11.205

Review 4.  New Perspectives on the Aging Lexicon.

Authors:  Dirk U Wulff; Simon De Deyne; Michael N Jones; Rui Mata
Journal:  Trends Cogn Sci       Date:  2019-07-06       Impact factor: 20.229

5.  Complex network structure influences processing in long-term and short-term memory.

Authors:  Michael S Vitevitch; Kit Ying Chan; Steven Roodenrys
Journal:  J Mem Lang       Date:  2012-07-01       Impact factor: 3.059

Review 6.  Cognitive network neuroscience.

Authors:  John D Medaglia; Mary-Ellen Lynall; Danielle S Bassett
Journal:  J Cogn Neurosci       Date:  2015-03-24       Impact factor: 3.225

7.  Lexical access in aphasic and nonaphasic speakers.

Authors:  G S Dell; M F Schwartz; N Martin; E M Saffran; D A Gagnon
Journal:  Psychol Rev       Date:  1997-10       Impact factor: 8.934

Review 8.  Network neuroscience.

Authors:  Danielle S Bassett; Olaf Sporns
Journal:  Nat Neurosci       Date:  2017-02-23       Impact factor: 24.884

9.  spreadr: An R package to simulate spreading activation in a network.

Authors:  Cynthia S Q Siew
Journal:  Behav Res Methods       Date:  2019-04

10.  How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant's Age.

Authors:  Marc Brysbaert; Michaël Stevens; Paweł Mandera; Emmanuel Keuleers
Journal:  Front Psychol       Date:  2016-07-29
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Authors:  Nichol Castro; Stephen E Nadeau; Diane L Kendall
Journal:  Aphasiology       Date:  2021-01-25       Impact factor: 2.773

3.  Exploring the Complexity of Aphasia With Network Analysis.

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5.  Evidence for preferential attachment: Words that are more well connected in semantic networks are better at acquiring new links in paired-associate learning.

Authors:  Matthew H C Mak; Hope Twitchell
Journal:  Psychon Bull Rev       Date:  2020-10

Review 6.  Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Authors:  Aleksandra Kawala-Sterniuk; Natalia Browarska; Amir Al-Bakri; Mariusz Pelc; Jaroslaw Zygarlicki; Michaela Sidikova; Radek Martinek; Edward Jacek Gorzelanczyk
Journal:  Brain Sci       Date:  2021-01-03

7.  Revealing semantic and emotional structure of suicide notes with cognitive network science.

Authors:  Andreia Sofia Teixeira; Szymon Talaga; Trevor James Swanson; Massimo Stella
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Review 8.  Knowledge Representations Derived From Semantic Fluency Data.

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Journal:  Front Psychol       Date:  2022-03-11
  8 in total

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