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dc.contributor.authorIssa, Mohamed F.
dc.contributor.authorKhan, Izhar
dc.contributor.authorRuzzoli, Manuela
dc.contributor.authorMolinaro, Nicola
dc.contributor.authorLizarazu, Mikel
dc.date.accessioned2024-07-08T09:38:28Z
dc.date.available2024-07-08T09:38:28Z
dc.date.issued2024
dc.identifier.citationIssa, M.F., Khan, I., Ruzzoli, M., Molinaro, N., & Lizarazu, M. (2024). On the Speech Envelope in the Cortical Tracking of Speech. NeuroImage, 297:120675. Doi:10.1016/j.neuroimage.2024.120675es_ES
dc.identifier.citationNeuroImage
dc.identifier.issn1053-8119
dc.identifier.urihttp://hdl.handle.net/10810/68825
dc.descriptionAvailable online 15 June 2024es_ES
dc.description.abstractThe synchronization between the speech envelope and neural activity in auditory regions, referred to as cortical tracking of speech (CTS), plays a key role in speech processing. The method selected for extracting the envelope is a crucial step in CTS measurement, and the absence of a consensus on best practices among the various methods can influence analysis outcomes and interpretation. Here, we systematically compare five standard envelope extraction methods the absolute value of Hilbert transform (absHilbert), gammatone filterbanks, heuristic approach, Bark scale, and vocalic energy), analyzing their impact on the CTS. We present performance metrics for each method based on the recording of brain activity from participants listening to speech in clear and noisy conditions, utilizing intracranial EEG, MEG and EEG data. As expected, we observed significant CTS in temporal brain regions below 10 Hz across all datasets, regardless of the extraction methods. In general, the gammatone filterbanks approach consistently demonstrated superior performance compared to other methods. Results from our study can guide scientists in the field to make informed decisions about the optimal analysis to extract the CTS, contributing to advancing the understanding of the neuronal mechanisms implicated in CTS.es_ES
dc.description.sponsorshipThis research is supported by the Basque Government through the BERC 2022-2025 program and funded by the Spanish State Research Agency (AEI) through BCBL Severo Ochoa excellence accreditation CEX2020-001010/AEI/10.13039/501100011033. Additionally, it is supported by project PDC2022-133917-I00 funded by the Spanish Ministry of Science, Innovation, and Universities (MICIU) and the AEI. M.L. acknowledges funding support from the Ramón y Cajal program of the Spanish MICIU (grant RYC2022-035497-I) and the PIBA-2022-1-0015 from the Basque Government. MR is supported by MICIU and the AEI under the Ramón y Cajal program (RYC2019-027538-I/10.13039/501100011033), as well as the Basque Foundation for Science (Ikerbasque). NM was supported by the Spanish MICIU (grants RTI2018-096311-B-I00, PCI2022-135031-2, PID2022-136991NB-I00), the AEI, and the European Regional Development Fund (FEDER). The authors express their gratitude to Prof. Mathieu Bourguignon for sharing the MEG and EEG data at the CUB Hôpital Erasme.es_ES
dc.language.isoenges_ES
dc.publisherELSEVIERes_ES
dc.relationinfo:eu-repo/grantAgreement/GV/BERC2022-2025es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/CEX2020-001010-Ses_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/PDC2022-133917-I00es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/RYC2022-035497-Ies_ES
dc.relationinfo:eu-repo/grantAgreement/GV/PIBA-2022-1-0015es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/RYC2019-027538-Ies_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/RTI2018-096311-B-I00es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/PCI2022-135031-2es_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/PID2022-136991NB-I00es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectCortical tracking of speeches_ES
dc.subjectEnvelope extraction methodses_ES
dc.subjectFunctional neurolmaging techniqueses_ES
dc.subjectGrammatone filterbankses_ES
dc.titleOn the speech envelope in the cortical tracking of speeches_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder/© 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/bync/4.0/).es_ES
dc.relation.publisherversionhttps://www.sciencedirect.com/journal/neuroimagees_ES
dc.identifier.doi10.1016/j.neuroimage.2024.120675


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