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Detecting self-produced speech errors before and after articulation: an ERP investigation.

Trewartha KM, Phillips NA - Front Hum Neurosci (2013)

Bottom Line: The data also revealed that general conflict monitoring mechanisms are involved during this task as both correct and incorrect responses elicited an anterior N2 component typically associated with conflict monitoring.The response-locked analyses corroborated previous observations that self-produced speech errors led to a fronto-central error-related negativity (ERN).These results demonstrate that speech errors can be detected prior to articulation, and that speech error monitoring relies on a central error monitoring mechanism.

View Article: PubMed Central - PubMed

Affiliation: Centre for Neuroscience Studies, Queen's University Kingston ON, Canada ; Centre for Research in Human Development Montreal, QC, Canada ; Department of Psychology, Concordia University Montreal, QC, Canada.

ABSTRACT
It has been argued that speech production errors are monitored by the same neural system involved in monitoring other types of action errors. Behavioral evidence has shown that speech errors can be detected and corrected prior to articulation, yet the neural basis for such pre-articulatory speech error monitoring is poorly understood. The current study investigated speech error monitoring using a phoneme-substitution task known to elicit speech errors. Stimulus-locked event-related potential (ERP) analyses comparing correct and incorrect utterances were used to assess pre-articulatory error monitoring and response-locked ERP analyses were used to assess post-articulatory monitoring. Our novel finding in the stimulus-locked analysis revealed that words that ultimately led to a speech error were associated with a larger P2 component at midline sites (FCz, Cz, and CPz). This early positivity may reflect the detection of an error in speech formulation, or a predictive mechanism to signal the potential for an upcoming speech error. The data also revealed that general conflict monitoring mechanisms are involved during this task as both correct and incorrect responses elicited an anterior N2 component typically associated with conflict monitoring. The response-locked analyses corroborated previous observations that self-produced speech errors led to a fronto-central error-related negativity (ERN). These results demonstrate that speech errors can be detected prior to articulation, and that speech error monitoring relies on a central error monitoring mechanism.

No MeSH data available.


Related in: MedlinePlus

Response-locked, grand averaged waveforms for fronto-central electrode sites: FCz and Cz. Figure shows the average waveform for correct (dashed line) and incorrect (solid line) responses (panels on the left side). The ERN can be observed after the response, peaking at ~75 ms post-error response. The panels on the right side show the averaged amplitudes within the 50–100 ms post-response interval, with standard error bars.
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Figure 2: Response-locked, grand averaged waveforms for fronto-central electrode sites: FCz and Cz. Figure shows the average waveform for correct (dashed line) and incorrect (solid line) responses (panels on the left side). The ERN can be observed after the response, peaking at ~75 ms post-error response. The panels on the right side show the averaged amplitudes within the 50–100 ms post-response interval, with standard error bars.

Mentions: In order to corroborate previous observations that speech errors elicit an ERN similar to the ERN observed for other types of action errors, we also conducted response-locked analyses. To characterize the ERN we compared the averaged amplitude in the 50–100 ms interval after the response between correct and incorrect responses in the substitution trials over the fronto-central electrode sites: FCz and Cz (e.g., Holroyd and Coles, 2002; Yeung et al., 2004). As a baseline comparison, the averaged amplitude in the 50 ms interval immediately before the response was compared between correct and incorrect responses. For the response-locked analyses, the number of error trials that survived artefact rejection ranged from 5 to 32 trials (M = 14.0, SD = 7.7) whereas the number of correct trials included in the averages ranged from 61 to 166 trials (M = 122.0, SD = 35.9). These data were subjected to separate 2 (electrode site) × 2 (response type) ANOVAs. In the 50–100 ms interval there was a significant main effect of response accuracy, F(14,1) = 9.9, MSE = 11.1, η2p = 0.41, p < 0.05, such that there was a larger negative waveform for incorrect compared to correct responses over both electrode sites (Figure 2). The comparison between correct and incorrect responses was not significant during the 50 ms interval prior to the response [F(14,1) = 1.0, MSE = 0.008, η2p = 0.07, p = 0.34]. This finding confirms the prediction that an ERN with typical topography and latency would be associated with self-produced speech errors.


Detecting self-produced speech errors before and after articulation: an ERP investigation.

Trewartha KM, Phillips NA - Front Hum Neurosci (2013)

Response-locked, grand averaged waveforms for fronto-central electrode sites: FCz and Cz. Figure shows the average waveform for correct (dashed line) and incorrect (solid line) responses (panels on the left side). The ERN can be observed after the response, peaking at ~75 ms post-error response. The panels on the right side show the averaged amplitudes within the 50–100 ms post-response interval, with standard error bars.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3822290&req=5

Figure 2: Response-locked, grand averaged waveforms for fronto-central electrode sites: FCz and Cz. Figure shows the average waveform for correct (dashed line) and incorrect (solid line) responses (panels on the left side). The ERN can be observed after the response, peaking at ~75 ms post-error response. The panels on the right side show the averaged amplitudes within the 50–100 ms post-response interval, with standard error bars.
Mentions: In order to corroborate previous observations that speech errors elicit an ERN similar to the ERN observed for other types of action errors, we also conducted response-locked analyses. To characterize the ERN we compared the averaged amplitude in the 50–100 ms interval after the response between correct and incorrect responses in the substitution trials over the fronto-central electrode sites: FCz and Cz (e.g., Holroyd and Coles, 2002; Yeung et al., 2004). As a baseline comparison, the averaged amplitude in the 50 ms interval immediately before the response was compared between correct and incorrect responses. For the response-locked analyses, the number of error trials that survived artefact rejection ranged from 5 to 32 trials (M = 14.0, SD = 7.7) whereas the number of correct trials included in the averages ranged from 61 to 166 trials (M = 122.0, SD = 35.9). These data were subjected to separate 2 (electrode site) × 2 (response type) ANOVAs. In the 50–100 ms interval there was a significant main effect of response accuracy, F(14,1) = 9.9, MSE = 11.1, η2p = 0.41, p < 0.05, such that there was a larger negative waveform for incorrect compared to correct responses over both electrode sites (Figure 2). The comparison between correct and incorrect responses was not significant during the 50 ms interval prior to the response [F(14,1) = 1.0, MSE = 0.008, η2p = 0.07, p = 0.34]. This finding confirms the prediction that an ERN with typical topography and latency would be associated with self-produced speech errors.

Bottom Line: The data also revealed that general conflict monitoring mechanisms are involved during this task as both correct and incorrect responses elicited an anterior N2 component typically associated with conflict monitoring.The response-locked analyses corroborated previous observations that self-produced speech errors led to a fronto-central error-related negativity (ERN).These results demonstrate that speech errors can be detected prior to articulation, and that speech error monitoring relies on a central error monitoring mechanism.

View Article: PubMed Central - PubMed

Affiliation: Centre for Neuroscience Studies, Queen's University Kingston ON, Canada ; Centre for Research in Human Development Montreal, QC, Canada ; Department of Psychology, Concordia University Montreal, QC, Canada.

ABSTRACT
It has been argued that speech production errors are monitored by the same neural system involved in monitoring other types of action errors. Behavioral evidence has shown that speech errors can be detected and corrected prior to articulation, yet the neural basis for such pre-articulatory speech error monitoring is poorly understood. The current study investigated speech error monitoring using a phoneme-substitution task known to elicit speech errors. Stimulus-locked event-related potential (ERP) analyses comparing correct and incorrect utterances were used to assess pre-articulatory error monitoring and response-locked ERP analyses were used to assess post-articulatory monitoring. Our novel finding in the stimulus-locked analysis revealed that words that ultimately led to a speech error were associated with a larger P2 component at midline sites (FCz, Cz, and CPz). This early positivity may reflect the detection of an error in speech formulation, or a predictive mechanism to signal the potential for an upcoming speech error. The data also revealed that general conflict monitoring mechanisms are involved during this task as both correct and incorrect responses elicited an anterior N2 component typically associated with conflict monitoring. The response-locked analyses corroborated previous observations that self-produced speech errors led to a fronto-central error-related negativity (ERN). These results demonstrate that speech errors can be detected prior to articulation, and that speech error monitoring relies on a central error monitoring mechanism.

No MeSH data available.


Related in: MedlinePlus