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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Veröffentlicht in:Clinical EEG and neuroscience 2024-05, Vol.55 (3), p.371-383
Hauptverfasser: Bayat, Masoumeh, Boostani, Reza, Sabeti, Malihe, Yadegari, Fariba, Pirmoradi, Mohammadreza, Rao, KS, Nami, Mohammad
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container_end_page 383
container_issue 3
container_start_page 371
container_title Clinical EEG and neuroscience
container_volume 55
creator Bayat, Masoumeh
Boostani, Reza
Sabeti, Malihe
Yadegari, Fariba
Pirmoradi, Mohammadreza
Rao, KS
Nami, Mohammad
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.
doi_str_mv 10.1177/15500594221150638
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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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