Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances
Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). Method: A 64-channel electroencephalography (EEG) setup was used for data acquisit...
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description | Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). Method: A 64-channel electroencephalography (EEG) setup was used for data acquisition at 20 AWS. Since the speech, especially stuttering, causes significant noise in the EEG, 2 conditions of speech preparation (SP) and imagined speech (IS) were considered. EEG signals were decomposed into 6 bands. The corresponding sources were localized using the standard low-resolution electromagnetic tomography (sLORETA) tool in both fluent and dysfluent states. Results: Significant differences were noted after analyzing the time-locked EEG signals in fluent and dysfluent utterances. Consistent with previous studies, poor alpha and beta suppression in SP and IS conditions were localized in the left frontotemporal areas in a dysfluent state. This was partly true for the right frontal regions. In the theta range, disfluency was concurrence with increased activation in the left and right motor areas. Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech. |
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Method: A 64-channel electroencephalography (EEG) setup was used for data acquisition at 20 AWS. Since the speech, especially stuttering, causes significant noise in the EEG, 2 conditions of speech preparation (SP) and imagined speech (IS) were considered. EEG signals were decomposed into 6 bands. The corresponding sources were localized using the standard low-resolution electromagnetic tomography (sLORETA) tool in both fluent and dysfluent states. Results: Significant differences were noted after analyzing the time-locked EEG signals in fluent and dysfluent utterances. Consistent with previous studies, poor alpha and beta suppression in SP and IS conditions were localized in the left frontotemporal areas in a dysfluent state. This was partly true for the right frontal regions. In the theta range, disfluency was concurrence with increased activation in the left and right motor areas. Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech.</description><identifier>ISSN: 1550-0594</identifier><identifier>EISSN: 2169-5202</identifier><identifier>DOI: 10.1177/15500594221150638</identifier><identifier>PMID: 36627837</identifier><language>eng</language><publisher>Los Angeles, CA: SAGE Publications</publisher><subject>Data acquisition ; EEG ; Electroencephalography ; Localization ; Speech ; Stuttering</subject><ispartof>Clinical EEG and neuroscience, 2024-05, Vol.55 (3), p.371-383</ispartof><rights>EEG and Clinical Neuroscience Society (ECNS) 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-c7382b9ef7f09d3410ec8b7d31ddb7dae4e569dedd5449f4bb586f7b95a197513</citedby><cites>FETCH-LOGICAL-c368t-c7382b9ef7f09d3410ec8b7d31ddb7dae4e569dedd5449f4bb586f7b95a197513</cites><orcidid>0000-0002-0013-4450</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/15500594221150638$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/15500594221150638$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36627837$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bayat, Masoumeh</creatorcontrib><creatorcontrib>Boostani, Reza</creatorcontrib><creatorcontrib>Sabeti, Malihe</creatorcontrib><creatorcontrib>Yadegari, Fariba</creatorcontrib><creatorcontrib>Pirmoradi, Mohammadreza</creatorcontrib><creatorcontrib>Rao, KS</creatorcontrib><creatorcontrib>Nami, Mohammad</creatorcontrib><title>Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances</title><title>Clinical EEG and neuroscience</title><addtitle>Clinical EEG and Neuroscience</addtitle><description>Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). Method: A 64-channel electroencephalography (EEG) setup was used for data acquisition at 20 AWS. Since the speech, especially stuttering, causes significant noise in the EEG, 2 conditions of speech preparation (SP) and imagined speech (IS) were considered. EEG signals were decomposed into 6 bands. The corresponding sources were localized using the standard low-resolution electromagnetic tomography (sLORETA) tool in both fluent and dysfluent states. Results: Significant differences were noted after analyzing the time-locked EEG signals in fluent and dysfluent utterances. Consistent with previous studies, poor alpha and beta suppression in SP and IS conditions were localized in the left frontotemporal areas in a dysfluent state. This was partly true for the right frontal regions. In the theta range, disfluency was concurrence with increased activation in the left and right motor areas. Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech.</description><subject>Data acquisition</subject><subject>EEG</subject><subject>Electroencephalography</subject><subject>Localization</subject><subject>Speech</subject><subject>Stuttering</subject><issn>1550-0594</issn><issn>2169-5202</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLw0AUhQdRtFZ_gBsZcOMmdd6TWUqtVSi4qF2HycxNSUmTmpks6q83oT5AcXXg3u-cyz0IXVEyoVTrOyolIdIIxiiVRPH0CI0YVSaRjLBjNBr2yQCcofMQNoRwxbg4RWdcKaZTrkcoWzZd6wAvGmer8t3GsqmxrT1e7sDFttvi-9pW-_eyXuOmwLPZHJc1XsYuRmiH4TLaCLjb9baHfSiqDuqIV8PW1g7CBTopbBXg8lPHaPU4e50-JYuX-fP0fpE4rtKYOM1TlhsodEGM54IScGmuPafe92JBgFTGg_dSCFOIPJepKnRupKVGS8rH6PaQu2ubtw5CzLZlcFBVtoamCxnTSgjBtGE9evML3fQd9F-GjBNuKNei1zGiB8q1TQgtFNmuLbe23WeUZEP72Z_2e8_1Z3KXb8F_O77q7oHJAQh2DT9n_0_8AP6CjFo</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Bayat, Masoumeh</creator><creator>Boostani, Reza</creator><creator>Sabeti, Malihe</creator><creator>Yadegari, Fariba</creator><creator>Pirmoradi, Mohammadreza</creator><creator>Rao, KS</creator><creator>Nami, Mohammad</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>4T-</scope><scope>7TK</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-0013-4450</orcidid></search><sort><creationdate>20240501</creationdate><title>Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances</title><author>Bayat, Masoumeh ; Boostani, Reza ; Sabeti, Malihe ; Yadegari, Fariba ; Pirmoradi, Mohammadreza ; Rao, KS ; Nami, Mohammad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-c7382b9ef7f09d3410ec8b7d31ddb7dae4e569dedd5449f4bb586f7b95a197513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Data acquisition</topic><topic>EEG</topic><topic>Electroencephalography</topic><topic>Localization</topic><topic>Speech</topic><topic>Stuttering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bayat, Masoumeh</creatorcontrib><creatorcontrib>Boostani, Reza</creatorcontrib><creatorcontrib>Sabeti, Malihe</creatorcontrib><creatorcontrib>Yadegari, Fariba</creatorcontrib><creatorcontrib>Pirmoradi, Mohammadreza</creatorcontrib><creatorcontrib>Rao, KS</creatorcontrib><creatorcontrib>Nami, Mohammad</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Docstoc</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical EEG and neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bayat, Masoumeh</au><au>Boostani, Reza</au><au>Sabeti, Malihe</au><au>Yadegari, Fariba</au><au>Pirmoradi, Mohammadreza</au><au>Rao, KS</au><au>Nami, Mohammad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances</atitle><jtitle>Clinical EEG and neuroscience</jtitle><addtitle>Clinical EEG and Neuroscience</addtitle><date>2024-05-01</date><risdate>2024</risdate><volume>55</volume><issue>3</issue><spage>371</spage><epage>383</epage><pages>371-383</pages><issn>1550-0594</issn><eissn>2169-5202</eissn><abstract>Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). 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Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech.</abstract><cop>Los Angeles, CA</cop><pub>SAGE Publications</pub><pmid>36627837</pmid><doi>10.1177/15500594221150638</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-0013-4450</orcidid></addata></record> |
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subjects | Data acquisition EEG Electroencephalography Localization Speech Stuttering |
title | Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances |
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