Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances

Area of Science:

• Neuroscience
• Speech and Language Sciences
• Biomedical Engineering

Background:

• Stuttering is a complex speech disorder affecting adults.
• Understanding the neural underpinnings of stuttering is crucial for developing effective interventions.
• Quantitative electroencephalography (qEEG) offers a non-invasive method to study brain activity during speech production.

Purpose of the Study:

• To investigate power spectral dynamics in adults who stutter (AWS) during fluent and dysfluent speech states.
• To identify specific electroencephalography (EEG) patterns associated with stuttering.
• To explore the neural correlates of stuttering using quantitative EEG.

Main Methods:

• Utilized a 64-channel electroencephalography (EEG) setup for data acquisition in 20 AWS.
• Employed speech preparation (SP) and imagined speech (IS) conditions to minimize speech-related noise.
• Decomposed EEG signals into 6 frequency bands and localized sources using standard low-resolution electromagnetic tomography (sLORETA).

Main Results:

• Significant differences in time-locked EEG signals were observed between fluent and dysfluent speech.
• Poor alpha and beta suppression in the left frontotemporal areas (and partly right frontal) characterized dysfluent states.
• Increased theta band activation in motor areas and delta/beta2 power in motor/parietal regions were associated with fluent speech.

Conclusions:

• Neural circuitries involved in stuttering likely require examination across the entire speech frequency spectrum.
• Specific EEG frequency bands and their spatial localization provide insights into the neural basis of stuttering.
• Findings contribute to a more comprehensive understanding of the neurophysiology of stuttering.