Journal article
Sensorimotor activity measured via oscillations of EEG mu rhythms in speech and non-speech discrimination tasks with and without segmentation demands
Brain and language, Vol.187, pp.62-73
12/01/2018
PMID: 28431691
Abstract
Better understanding of the role of sensorimotor processing in speech and non-speech segmentation can be achieved with more temporally precise measures. Twenty adults made same/different discriminations of speech and non-speech stimuli pairs, with and without segmentation demands. Independent component analysis of 64-channel EEG data revealed clear sensorimotor mu components, with characteristic alpha and beta peaks, localized to premotor regions in 70% of participants.Time-frequency analyses of mu components from accurate trials showed that (1) segmentation tasks elicited greater event-related synchronization immediately following offset of the first stimulus, suggestive of inhibitory activity; (2) strong late event-related desynchronization in all conditions, suggesting that working memory/covert replay contributed substantially to sensorimotor activity in all conditions; (3) stronger beta desynchronization in speech versus non-speech stimuli during stimulus presentation, suggesting stronger auditory-motor transforms for speech versus non-speech stimuli. Findings support the continued use of oscillatory approaches for helping understand segmentation and other cognitive tasks.
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Details
- Title
- Sensorimotor activity measured via oscillations of EEG mu rhythms in speech and non-speech discrimination tasks with and without segmentation demands
- Creators
- David Thornton (Author) - University of Tennessee Health Science Center, United States. Electronic address: dthornt9@uthsc.eduAshley Harkrider (Author) - University of Tennessee Health Science Center, United StatesDavid Jenson (Author)Tim Saltuklaroglu (Author) - University of Tennessee Health Science Center, United States. Electronic address: tsaltukl@uthsc.edu
- Publication Details
- Brain and language, Vol.187, pp.62-73
- Academic Unit
- Speech and Hearing Sciences, Department of
- Identifiers
- 99901007438601842
- Language
- English
- Resource Type
- Journal article