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      The multiplex structure of the mental lexicon influences picture naming in people with aphasia

      1 , 2
      Journal of Complex Networks
      Oxford University Press (OUP)

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          Abstract

          An emerging area of research in cognitive science is the utilization of networks to model the structure and processes of the mental lexicon in healthy and clinical populations, like aphasia. Previous research has focused on only one type of word similarity at a time (e.g., semantic relationships), even though words are multi-faceted. Here, we investigate lexical retrieval in a picture naming task from people with Broca’s and Wernicke’s aphasia and healthy controls by utilizing a multiplex network structure that accounts for the interplay between multiple semantic and phonological relationships among words in the mental lexicon. Extending upon previous work, we focused on the global network measure of closeness centrality which is known to capture spreading activation, an important process supporting lexical retrieval. We conducted a series of logistic regression models predicting the probability of correct picture naming. We tested whether multiplex closeness centrality was a better predictor of picture naming performance than single-layer closeness centralities, other network measures assessing local and meso-scale structure, psycholinguistic variables and group differences. We also examined production gaps, or the difference between the likelihood of producing a word with the lowest and highest closeness centralities. Our results indicated that multiplex closeness centrality was a significant predictor of picture naming performance, where words with high closeness centrality were more likely to be produced than words with low closeness centrality. Additionally, multiplex closeness centrality outperformed single-layer closeness centralities and other multiplex network measures, and remained a significant predictor after controlling for psycholinguistic variables and group differences. Furthermore, we found that the facilitative effect of closeness centrality was similar for both types of aphasia. Our results underline the importance of integrating multiple measures of word similarities in cognitive language networks for better understanding lexical retrieval in aphasia, with an eye towards future clinical applications.

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          Most cited references30

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          Multilayer networks

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            Retrieval time from semantic memory

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              Reworking the language network.

              Prior investigations of functional specialization have focused on the response profiles of particular brain regions. Given the growing emphasis on regional covariation, we propose to reframe these questions in terms of brain 'networks' (collections of regions jointly engaged by some mental process). Despite the challenges that investigations of the language network face, a network approach may prove useful in understanding the cognitive architecture of language. We propose that a language network plausibly includes a functionally specialized 'core' (brain regions that coactivate with each other during language processing) and a domain-general 'periphery' (a set of brain regions that may coactivate with the language core regions at some times but with other specialized systems at other times, depending on task demands). Framing the debate around network properties such as this may prove to be a more fruitful way to advance our understanding of the neurobiology of language. Copyright © 2013 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Journal of Complex Networks
                Oxford University Press (OUP)
                2051-1329
                April 23 2019
                April 23 2019
                Affiliations
                [1 ]School of Psychology, Georgia Institute of Technology, 654 Cherry Street, Atlanta, Georgia, 30332 USA
                [2 ]Institute for Complex Systems Simulation, University of Southampton, University Road 4, SO17 1BJ, Southampton, UK and Complex Science Consulting, Via Amilcare Foscarini 2, 73100, Lecce, Italy
                Article
                10.1093/comnet/cnz012
                6961494
                31984136
                d44957c9-d6ee-4f4c-bb7f-f8e2b6db4d79
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model


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