Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1155/2015/865974 http://hdl.handle.net/11449/231365 |
Resumo: | Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (si) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(ei) provided by each electrode of the 10/20 system about the identified si. H(ei) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources si. This analysis evidenced 4 different patterns of H(ei) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies. |
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Repositório Institucional da UNESP |
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Combining Different Tools for EEG Analysis to Study the Distributed Character of Language ProcessingRecent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (si) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(ei) provided by each electrode of the 10/20 system about the identified si. H(ei) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources si. This analysis evidenced 4 different patterns of H(ei) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies.Research on Artificial and Natural Intelligence (RANI), Rua Tenente Ary Aps 172CEFAC-Saúde e Educação, Rua Anchieta 670, Sala 22Department of Education Institute of Biosciences University of São Paulo Campus Rubião Jr.Research on Artificial and Natural Intelligence (RANI)CEFAC-Saúde e EducaçãoUniversidade de São Paulo (USP)Da Rocha, Armando FreitasFoz, Flávia BenevidesPereira, Alfredo2022-04-29T08:44:58Z2022-04-29T08:44:58Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1155/2015/865974Computational Intelligence and Neuroscience, v. 2015.1687-52731687-5265http://hdl.handle.net/11449/23136510.1155/2015/8659742-s2.0-84950114885Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengComputational Intelligence and Neuroscienceinfo:eu-repo/semantics/openAccess2022-04-29T08:44:58Zoai:repositorio.unesp.br:11449/231365Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:40:21.317921Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
title |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
spellingShingle |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing Da Rocha, Armando Freitas |
title_short |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
title_full |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
title_fullStr |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
title_full_unstemmed |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
title_sort |
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing |
author |
Da Rocha, Armando Freitas |
author_facet |
Da Rocha, Armando Freitas Foz, Flávia Benevides Pereira, Alfredo |
author_role |
author |
author2 |
Foz, Flávia Benevides Pereira, Alfredo |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Research on Artificial and Natural Intelligence (RANI) CEFAC-Saúde e Educação Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Da Rocha, Armando Freitas Foz, Flávia Benevides Pereira, Alfredo |
description |
Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (si) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(ei) provided by each electrode of the 10/20 system about the identified si. H(ei) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources si. This analysis evidenced 4 different patterns of H(ei) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 2022-04-29T08:44:58Z 2022-04-29T08:44:58Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1155/2015/865974 Computational Intelligence and Neuroscience, v. 2015. 1687-5273 1687-5265 http://hdl.handle.net/11449/231365 10.1155/2015/865974 2-s2.0-84950114885 |
url |
http://dx.doi.org/10.1155/2015/865974 http://hdl.handle.net/11449/231365 |
identifier_str_mv |
Computational Intelligence and Neuroscience, v. 2015. 1687-5273 1687-5265 10.1155/2015/865974 2-s2.0-84950114885 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Computational Intelligence and Neuroscience |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129449415147520 |