dc.contributor.author | Janssen, Niels | |
dc.contributor.author | van der Meij, Maartje | |
dc.contributor.author | López-Pérez, Pedro Javier | |
dc.contributor.author | Barber, Horacio A. | |
dc.date.accessioned | 2020-03-23T08:23:07Z | |
dc.date.available | 2020-03-23T08:23:07Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Janssen, N., Meij, M.v.d., López-Pérez, P.J. et al. Exploring the temporal dynamics of speech production with EEG and group ICA. Sci Rep 10, 3667 (2020). https://doi.org/10.1038/s41598-020-60301-1 | es_ES |
dc.identifier.issn | 2045-2322 | |
dc.identifier.uri | http://hdl.handle.net/10810/42274 | |
dc.description | Published: 28 February 2020 | es_ES |
dc.description.abstract | Speech production is a complex skill whose neural implementation relies on a large number of different regions in the brain. How neural activity in these different regions varies as a function of time during the production of speech remains poorly understood. Previous MEG studies on this topic have concluded that activity proceeds from posterior to anterior regions of the brain in a sequential manner. Here we tested this claim using the EEG technique. Specifically, participants performed a picture naming task while their naming latencies and scalp potentials were recorded. We performed group temporal Independent Component Analysis (group tICA) to obtain temporally independent component timecourses and their corresponding topographic maps. We identified fifteen components whose estimated neural sources were located in various areas of the brain. The trial-by-trial component timecourses were predictive of the naming latency, implying their involvement in the task. Crucially, we computed the degree of concurrent activity of each component timecourse to test whether activity was sequential or parallel. Our results revealed that these fifteen distinct neural sources exhibit largely concurrent activity during speech production. These results suggest that speech production relies on neural activity that takes place in parallel networks of distributed neural sources. | es_ES |
dc.description.sponsorship | This work was supported by Spanish Ministry of Science Innovation and Universities (PSI2017-84933-P and PSI2017-91955-EXP to NJ). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Scientific Reports | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/PSI2017-84933-P | es_ES |
dc.relation | info:eu-repo/grantAgreement/MINECO/PSI2017-91955-EXP | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.title | Exploring the temporal dynamics of speech production with EEG and group ICA | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2020 | es_ES |
dc.relation.publisherversion | https://www.nature.com/srep/ | es_ES |
dc.identifier.doi | 10.1038/s41598-020-60301-1 | |