Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research

Detalhes bibliográficos
Autor(a) principal: Mota, Natália Bezerra
Data de Publicação: 2018
Outros Autores: Copelli, Mauro, Ribeiro, Sidarta Tollendal Gomes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRN
Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/25465
https://doi.org/10.1017/9781316676974.004
Resumo: 2019-07-30
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spelling Mota, Natália BezerraCopelli, MauroRibeiro, Sidarta Tollendal Gomes2018-06-19T16:45:46Z2018MOTA, N.B.; COPELLI, M.; RIBEIRO, S. Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research. In: POIBEAU, T.; VILLAVICENCIO, A. Language, cognition, and computational models. United Kingdom: Cambridge University Press, 2018. Cap. 4.https://repositorio.ufrn.br/jspui/handle/123456789/25465https://doi.org/10.1017/9781316676974.004enggraph theorypsychiatric diagnosisGraph theory applied to speech: insights on cognitive deficit diagnosis and dream researchinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article2019-07-30In the past ten years, graph theory has been widely employed in the study of natural and technological phenomena. The representation of the relationships among the units of a network allow for a quantitative analysis of its overall structure, beyond what can be understood by considering only a few units. Here we discuss the application of graph theory to psychiatric diagnosis of psychoses and dementias. The aim is to quantify the flow of thoughts of psychiatric patients, as expressed by verbal reports of dream or waking events. This flow of thoughts is hard to measure but is at the roots of psychiatry as well as psychoanalysis. To this end, speech graphs were initially designed with nodes representing lexemes and edges representing the temporal sequence between consecutive words, leading to directed multigraphs. In a subsequent study, individual words were considered as nodes and their temporal sequence as edges; this simplification allowed for the automatization of the process, effected by the free software Speech Graphs. Using this approach, one can calculate local and global attributes that characterize the network structure, such as the total number of nodes and edges, the number of nodes present in the largest connected and the largest strongly connected components, measures of recurrence such as loops of 1, 2, and 3 nodes, parallel and repeated edges, and global measures such as the average degree, density, diameter, average shortest path, and clustering coefficient. Using these network attributes we were able to automatically sort schizophrenia and bipolar patients undergoing psychosis, and also to separate these psychotic patients from subjects without psychosis, with more than 90% sensitivity and specificity. In addition to the use of the method for strictly clinical purposes, we found that differences in the content of the verbal reports correspond to structural differences at the graph level. When reporting a dream, healthy subjects without psychosis and psychotic subjects with bipolar disorder produced more complex graphs than when reporting waking activities of the previous day; this difference was not observed in psychotic subjects with schizophrenia, which produced equally poor reports irrespective of the content. As a consequence, graphs of dream reports were more efficient for the differential diagnosis of psychosis than graphs of daily reports. Based on these results we can conclude that graphs from dream reports are more informative about mental states, echoing the psychoanalytic notion that dreams are a privileged window into thought.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNORIGINALSidartaRibeiro_ICe_Graph Theory_2018.pdfSidartaRibeiro_ICe_Graph Theory_2018.pdfSidartaRibeiro_ICe_Graph Theory_2018application/pdf817847https://repositorio.ufrn.br/bitstream/123456789/25465/1/SidartaRibeiro_ICe_Graph%20Theory_2018.pdf2e1cc2854649459dd09ff902872a78daMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.ufrn.br/bitstream/123456789/25465/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52TEXTSidartaRibeiro_ICe_Graph Theory_2018.pdf.txtSidartaRibeiro_ICe_Graph Theory_2018.pdf.txtExtracted texttext/plain49315https://repositorio.ufrn.br/bitstream/123456789/25465/3/SidartaRibeiro_ICe_Graph%20Theory_2018.pdf.txt81d86e6f785767aa41daa884d64d1d1cMD53THUMBNAILSidartaRibeiro_ICe_Graph Theory_2018.pdf.jpgSidartaRibeiro_ICe_Graph Theory_2018.pdf.jpgIM Thumbnailimage/jpeg6730https://repositorio.ufrn.br/bitstream/123456789/25465/4/SidartaRibeiro_ICe_Graph%20Theory_2018.pdf.jpge288e4504b4448ecfd44996a60859efbMD54123456789/254652024-03-19 01:02:50.33oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2024-03-19T04:02:50Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.pt_BR.fl_str_mv Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
title Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
spellingShingle Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
Mota, Natália Bezerra
graph theory
psychiatric diagnosis
title_short Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
title_full Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
title_fullStr Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
title_full_unstemmed Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
title_sort Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research
author Mota, Natália Bezerra
author_facet Mota, Natália Bezerra
Copelli, Mauro
Ribeiro, Sidarta Tollendal Gomes
author_role author
author2 Copelli, Mauro
Ribeiro, Sidarta Tollendal Gomes
author2_role author
author
dc.contributor.author.fl_str_mv Mota, Natália Bezerra
Copelli, Mauro
Ribeiro, Sidarta Tollendal Gomes
dc.subject.por.fl_str_mv graph theory
psychiatric diagnosis
topic graph theory
psychiatric diagnosis
description 2019-07-30
publishDate 2018
dc.date.accessioned.fl_str_mv 2018-06-19T16:45:46Z
dc.date.issued.fl_str_mv 2018
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.citation.fl_str_mv MOTA, N.B.; COPELLI, M.; RIBEIRO, S. Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research. In: POIBEAU, T.; VILLAVICENCIO, A. Language, cognition, and computational models. United Kingdom: Cambridge University Press, 2018. Cap. 4.
dc.identifier.uri.fl_str_mv https://repositorio.ufrn.br/jspui/handle/123456789/25465
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1017/9781316676974.004
identifier_str_mv MOTA, N.B.; COPELLI, M.; RIBEIRO, S. Graph theory applied to speech: insights on cognitive deficit diagnosis and dream research. In: POIBEAU, T.; VILLAVICENCIO, A. Language, cognition, and computational models. United Kingdom: Cambridge University Press, 2018. Cap. 4.
url https://repositorio.ufrn.br/jspui/handle/123456789/25465
https://doi.org/10.1017/9781316676974.004
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language eng
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