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Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Bowers A, Saltuklaroglu T, Harkrider A, Cuellar M - PLoS ONE (2013)

Bottom Line: EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri.Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Disorders, University of Arkansas, Fayetteville, Arkansas, United States of America.

ABSTRACT

Background: Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.).

Methods: Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.

Results: ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset.

Conclusions: Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

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Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the right-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
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pone-0072024-g007: Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the right-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.

Mentions: The initial permutation analysis revealed significant ERSPs at pFDR<.05 in the 15–25 Hz range (beta) for the right µ component (Figure 5). Significant time-frequency values corrected across the entire time-frequency matrix (pFDR<.05; 69×92) were found in the time-periods prior to, during, and after stimulus onset with a peak event-related decrease in spectral power in the time period after stimulus onset. To determine the sources of condition effects, a 1× design for the passive conditions (PasN, PasSp+4 dB, and PasTn+4 dB conditions) was conducted. The ANOVA revealed no significant differences (69×92; pFDR>.05). Analysis of the active conditions in which a sensory-decision was required (1×4; ActSp+4 dB, ActSp−6 dB, ActTn+4 dB, and ActTn−18 dB), revealed no significant differences (pFDR<.05; 69×92). To assess which conditions were significantly different from the PasN condition (i.e., the baseline), a series of paired contrasts were performed. Significant differences (pFDR<.05; 69×92) for the time periods before, during, and after stimulus onset were found for correct trials in the ActS+4 dB and chance trials in the ActSp−6 dB conditions. For the tone-sweep conditions, significant suppression occurred only after stimulus onset (pFDR<.05; 69×92). Although ERDs were found for individual participants in the time-period prior to tone-sweep discrimination trials, overall results did not fall below the significance threshold. Thus, although active tone discrimination conditions differed from the passive noise baseline in the time period following stimulus onset, no significant differences were noted between the active conditions (Figure 7).


Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Bowers A, Saltuklaroglu T, Harkrider A, Cuellar M - PLoS ONE (2013)

Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the right-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3750026&req=5

pone-0072024-g007: Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the right-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
Mentions: The initial permutation analysis revealed significant ERSPs at pFDR<.05 in the 15–25 Hz range (beta) for the right µ component (Figure 5). Significant time-frequency values corrected across the entire time-frequency matrix (pFDR<.05; 69×92) were found in the time-periods prior to, during, and after stimulus onset with a peak event-related decrease in spectral power in the time period after stimulus onset. To determine the sources of condition effects, a 1× design for the passive conditions (PasN, PasSp+4 dB, and PasTn+4 dB conditions) was conducted. The ANOVA revealed no significant differences (69×92; pFDR>.05). Analysis of the active conditions in which a sensory-decision was required (1×4; ActSp+4 dB, ActSp−6 dB, ActTn+4 dB, and ActTn−18 dB), revealed no significant differences (pFDR<.05; 69×92). To assess which conditions were significantly different from the PasN condition (i.e., the baseline), a series of paired contrasts were performed. Significant differences (pFDR<.05; 69×92) for the time periods before, during, and after stimulus onset were found for correct trials in the ActS+4 dB and chance trials in the ActSp−6 dB conditions. For the tone-sweep conditions, significant suppression occurred only after stimulus onset (pFDR<.05; 69×92). Although ERDs were found for individual participants in the time-period prior to tone-sweep discrimination trials, overall results did not fall below the significance threshold. Thus, although active tone discrimination conditions differed from the passive noise baseline in the time period following stimulus onset, no significant differences were noted between the active conditions (Figure 7).

Bottom Line: EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri.Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Disorders, University of Arkansas, Fayetteville, Arkansas, United States of America.

ABSTRACT

Background: Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.).

Methods: Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.

Results: ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset.

Conclusions: Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

Show MeSH
Related in: MedlinePlus