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Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances.
Bayat, Masoumeh; Boostani, Reza; Sabeti, Malihe; Yadegari, Fariba; Pirmoradi, Mohammadreza; Rao, K S; Nami, Mohammad.
Afiliação
  • Bayat M; Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Boostani R; Department of Computer Sciences and Engineering, School of Engineering, Shiraz University, Shiraz, Iran.
  • Sabeti M; Department of Computer Engineering, Islamic Azad University, North Tehran Branch, Tehran, Iran.
  • Yadegari F; Department of Speech and Language Pathology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
  • Pirmoradi M; Department of Clinical Psychology, School of Behavioral Sciences and Mental Health, Iran University of Medical Sciences, Tehran, Iran.
  • Rao KS; Neuroscience Center, INDICASAT-AIP, Panama City, Republic of Panama.
  • Nami M; Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
Clin EEG Neurosci ; 55(3): 371-383, 2024 May.
Article em En | MEDLINE | ID: mdl-36627837
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Gagueira / Córtex Motor Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Gagueira / Córtex Motor Idioma: En Ano de publicação: 2024 Tipo de documento: Article