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Detecting and correcting partial errors: Evidence for efficient control without conscious access.

Rochet N, Spieser L, Casini L, Hasbroucq T, Burle B - Cogn Affect Behav Neurosci (2014)

Bottom Line: Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected).The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection.The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire de Neurosciences Cognitives, UMR 7291, Fédération de Recherche 3C, Aix-Marseille Université and CNRS, Case C, 3, Place Victor Hugo, 13331, Marseille, France.

ABSTRACT
Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed.

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a Grand average of the incorrect EMG bursts: The EMG bursts corresponding to partial errors or overt errors were averaged, time-locked to their onsets, for the three detection categories. b Grand average of the correct EMG bursts observed on partial-error trials for the three detection categories, and for pure-correct trials. For the sake of visibility, the averaged EMG bursts have been smoothed, but all analyses were performed on the raw, unfiltered signals. (Inset: Grand average of pure-correct and error trials.) c Mean cumulative density functions of partial-error surfaces (IncSurf ) for undetected (gray diamonds) and detected (black diamonds) partial errors. Although the lowest values of the two distributions are pretty similar, they quickly diverge. (Inset: For the sake of comparison, this graph also shows the cumulative density function of surfaces for overt errors [black crosses].) d Mean cumulative density functions of CTs for undetected (gray diamonds) and detected (black diamonds) partial errors. The two distribution shapes are more similar than for those for surfaces, showing a more constant shift.
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Fig2: a Grand average of the incorrect EMG bursts: The EMG bursts corresponding to partial errors or overt errors were averaged, time-locked to their onsets, for the three detection categories. b Grand average of the correct EMG bursts observed on partial-error trials for the three detection categories, and for pure-correct trials. For the sake of visibility, the averaged EMG bursts have been smoothed, but all analyses were performed on the raw, unfiltered signals. (Inset: Grand average of pure-correct and error trials.) c Mean cumulative density functions of partial-error surfaces (IncSurf ) for undetected (gray diamonds) and detected (black diamonds) partial errors. Although the lowest values of the two distributions are pretty similar, they quickly diverge. (Inset: For the sake of comparison, this graph also shows the cumulative density function of surfaces for overt errors [black crosses].) d Mean cumulative density functions of CTs for undetected (gray diamonds) and detected (black diamonds) partial errors. The two distribution shapes are more similar than for those for surfaces, showing a more constant shift.

Mentions: We then compared the EMG bursts of partial-error trials to the EMG bursts of pure-correct and error trials: The incorrect EMG bursts of partial errors were compared to the error EMG bursts (one-way ANOVA with four modalities of factor detection: detected, uncertain, undetected, and error; Fig. 2a), and the correct EMG bursts of partial-error trials were compared to pure-correct EMG bursts (one-way ANOVA with four modalities of factor detection: detected, uncertain, undetected, and pure-correct; Fig. 2b). Finally, we also compared the pure-correct EMG burst to the one observed on errors. Concerning the latter comparison, as has already been reported (Allain, Carbonnell, Burle, Hasbroucq, & Vidal, 2004), the mean EMG burst has a smaller amplitude on overt errors than on pure-correct responses [t(14) = 3.55, p < .002], whereas the initial slopes do not differ [t(14) = 0.3, p = .77; see Fig. 2b, inset]. Comparing the correct EMG bursts for pure-correct and the three categories of partial-error trials revealed clear effects on the initial slope [F(3, 42) = 6.72, p < .001], on the peak amplitude [F(3, 42) = 3.07, p < .05], and on MT [F(3, 42) = 4.44, p < .01]. No main effect on surface was observed [F(3, 42) < 1], but inspection of Fig. 2b makes it clear that this was due to a reduced amplitude being compensated for by a wider shape, with the two counteracting each other. Planned orthogonal contrasts revealed that the correct EMG burst of undetected partial errors did not differ from pure-correct trials in any of the significant parameters [slopes, F(1, 14) = 2.323, p = .15; peak amplitude, F(1, 14) < 1; MT, F(1, 14) = 1.94, p = .185], whereas these two trial types differed from the other two (uncertain and detected), which showed a less steep initial slope [F(1, 14) = 12.62, p < .005], a decreased peak amplitude [F(1, 14) = 9.43, p < .005], and a lengthened MT [F(1, 14) = 7.02, p < .02]. Finally, detected trials produced a longer MT than did uncertain ones [F(1, 14) = 10.57, p < .01]; these two categories did not differ in either slope [F(1, 14) < 1] or surface [F(1, 14) = 1.01, p = .33]. Concerning the final analysis, comparing the incorrect EMG bursts of partial-error and error trials, Fig. 2a (presenting the mean EMG bursts) shows that even the EMG burst of the largest partial errors (detected ones) differed from the overt-error bursts, with a smaller surface [t(14) = 5.16, p < .001] and a less steep initial slope [t(14) = 4.44, p < .001], although a clear overlap exists (Fig. 2c, inset).Fig. 2


Detecting and correcting partial errors: Evidence for efficient control without conscious access.

Rochet N, Spieser L, Casini L, Hasbroucq T, Burle B - Cogn Affect Behav Neurosci (2014)

a Grand average of the incorrect EMG bursts: The EMG bursts corresponding to partial errors or overt errors were averaged, time-locked to their onsets, for the three detection categories. b Grand average of the correct EMG bursts observed on partial-error trials for the three detection categories, and for pure-correct trials. For the sake of visibility, the averaged EMG bursts have been smoothed, but all analyses were performed on the raw, unfiltered signals. (Inset: Grand average of pure-correct and error trials.) c Mean cumulative density functions of partial-error surfaces (IncSurf ) for undetected (gray diamonds) and detected (black diamonds) partial errors. Although the lowest values of the two distributions are pretty similar, they quickly diverge. (Inset: For the sake of comparison, this graph also shows the cumulative density function of surfaces for overt errors [black crosses].) d Mean cumulative density functions of CTs for undetected (gray diamonds) and detected (black diamonds) partial errors. The two distribution shapes are more similar than for those for surfaces, showing a more constant shift.
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Fig2: a Grand average of the incorrect EMG bursts: The EMG bursts corresponding to partial errors or overt errors were averaged, time-locked to their onsets, for the three detection categories. b Grand average of the correct EMG bursts observed on partial-error trials for the three detection categories, and for pure-correct trials. For the sake of visibility, the averaged EMG bursts have been smoothed, but all analyses were performed on the raw, unfiltered signals. (Inset: Grand average of pure-correct and error trials.) c Mean cumulative density functions of partial-error surfaces (IncSurf ) for undetected (gray diamonds) and detected (black diamonds) partial errors. Although the lowest values of the two distributions are pretty similar, they quickly diverge. (Inset: For the sake of comparison, this graph also shows the cumulative density function of surfaces for overt errors [black crosses].) d Mean cumulative density functions of CTs for undetected (gray diamonds) and detected (black diamonds) partial errors. The two distribution shapes are more similar than for those for surfaces, showing a more constant shift.
Mentions: We then compared the EMG bursts of partial-error trials to the EMG bursts of pure-correct and error trials: The incorrect EMG bursts of partial errors were compared to the error EMG bursts (one-way ANOVA with four modalities of factor detection: detected, uncertain, undetected, and error; Fig. 2a), and the correct EMG bursts of partial-error trials were compared to pure-correct EMG bursts (one-way ANOVA with four modalities of factor detection: detected, uncertain, undetected, and pure-correct; Fig. 2b). Finally, we also compared the pure-correct EMG burst to the one observed on errors. Concerning the latter comparison, as has already been reported (Allain, Carbonnell, Burle, Hasbroucq, & Vidal, 2004), the mean EMG burst has a smaller amplitude on overt errors than on pure-correct responses [t(14) = 3.55, p < .002], whereas the initial slopes do not differ [t(14) = 0.3, p = .77; see Fig. 2b, inset]. Comparing the correct EMG bursts for pure-correct and the three categories of partial-error trials revealed clear effects on the initial slope [F(3, 42) = 6.72, p < .001], on the peak amplitude [F(3, 42) = 3.07, p < .05], and on MT [F(3, 42) = 4.44, p < .01]. No main effect on surface was observed [F(3, 42) < 1], but inspection of Fig. 2b makes it clear that this was due to a reduced amplitude being compensated for by a wider shape, with the two counteracting each other. Planned orthogonal contrasts revealed that the correct EMG burst of undetected partial errors did not differ from pure-correct trials in any of the significant parameters [slopes, F(1, 14) = 2.323, p = .15; peak amplitude, F(1, 14) < 1; MT, F(1, 14) = 1.94, p = .185], whereas these two trial types differed from the other two (uncertain and detected), which showed a less steep initial slope [F(1, 14) = 12.62, p < .005], a decreased peak amplitude [F(1, 14) = 9.43, p < .005], and a lengthened MT [F(1, 14) = 7.02, p < .02]. Finally, detected trials produced a longer MT than did uncertain ones [F(1, 14) = 10.57, p < .01]; these two categories did not differ in either slope [F(1, 14) < 1] or surface [F(1, 14) = 1.01, p = .33]. Concerning the final analysis, comparing the incorrect EMG bursts of partial-error and error trials, Fig. 2a (presenting the mean EMG bursts) shows that even the EMG burst of the largest partial errors (detected ones) differed from the overt-error bursts, with a smaller surface [t(14) = 5.16, p < .001] and a less steep initial slope [t(14) = 4.44, p < .001], although a clear overlap exists (Fig. 2c, inset).Fig. 2

Bottom Line: Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected).The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection.The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire de Neurosciences Cognitives, UMR 7291, Fédération de Recherche 3C, Aix-Marseille Université and CNRS, Case C, 3, Place Victor Hugo, 13331, Marseille, France.

ABSTRACT
Appropriate reactions to erroneous actions are essential to keeping behavior adaptive. Erring, however, is not an all-or-none process: electromyographic (EMG) recordings of the responding muscles have revealed that covert incorrect response activations (termed "partial errors") occur on a proportion of overtly correct trials. The occurrence of such "partial errors" shows that incorrect response activations could be corrected online, before turning into overt errors. In the present study, we showed that, unlike overt errors, such "partial errors" are poorly consciously detected by participants, who could report only one third of their partial errors. Two parameters of the partial errors were found to predict detection: the surface of the incorrect EMG burst (larger for detected) and the correction time (between the incorrect and correct EMG onsets; longer for detected). These two parameters provided independent information. The correct(ive) responses associated with detected partial errors were larger than the "pure-correct" ones, and this increase was likely a consequence, rather than a cause, of the detection. The respective impacts of the two parameters predicting detection (incorrect surface and correction time), along with the underlying physiological processes subtending partial-error detection, are discussed.

Show MeSH
Related in: MedlinePlus