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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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Example of a partial error, along with the extracted indices. a Typical electromyographic (EMG) recording showing a partial error. Time 0 is stimulus onset, and the long vertical dashed line indicates the mechanical response. The bottom trace presents the rectified EMG activity of the muscle involved in the correct response. A large EMG burst starts slightly before the mechanical response. This correct EMG burst is preceded by a small burst on the incorrect muscle (top trace), which is far too small to produce an overt response. The extracted indices are the latency of the partial error (IncLat), the correction time (CT, between the incorrect and the correct EMG burst onsets), and the motor time between the correct EMG burst onset and the mechanical response. b Zoom depiction of the partial error, depicting the extracted EMG burst parameters. First, we computed the maximum of the rectified trace. Then we extracted the earliest point preceding, and the latest point following, the peak whose amplitudes were equal to or larger than half of the max amplitude. The time separating the two values was taken as the measure of EMG burst duration (IncDur and CorDur, for incorrect and correct EMG bursts, respectively). The surface under the curve between these two points (shaded area in panel b) was taken as a measure of the EMG burst amplitude (IncSurf and CorSurf, for incorrect and correct bursts, respectively). c Slope extraction: The cumulative sum of the rectified EMG trace was computed, becoming monotonically increasing. The linear trend was then removed to get a “flat” signal. A linear regression was computed on the first 30 points of the cumulative signal following the burst onset (i.e., on about the first 15 ms), and the slope of the regression (dashed line in panel c) is taken as a measure of the steepness of the EMG burst (IncSlope and CorSlope, for incorrect and correct EMG bursts, respectively)
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Fig1: Example of a partial error, along with the extracted indices. a Typical electromyographic (EMG) recording showing a partial error. Time 0 is stimulus onset, and the long vertical dashed line indicates the mechanical response. The bottom trace presents the rectified EMG activity of the muscle involved in the correct response. A large EMG burst starts slightly before the mechanical response. This correct EMG burst is preceded by a small burst on the incorrect muscle (top trace), which is far too small to produce an overt response. The extracted indices are the latency of the partial error (IncLat), the correction time (CT, between the incorrect and the correct EMG burst onsets), and the motor time between the correct EMG burst onset and the mechanical response. b Zoom depiction of the partial error, depicting the extracted EMG burst parameters. First, we computed the maximum of the rectified trace. Then we extracted the earliest point preceding, and the latest point following, the peak whose amplitudes were equal to or larger than half of the max amplitude. The time separating the two values was taken as the measure of EMG burst duration (IncDur and CorDur, for incorrect and correct EMG bursts, respectively). The surface under the curve between these two points (shaded area in panel b) was taken as a measure of the EMG burst amplitude (IncSurf and CorSurf, for incorrect and correct bursts, respectively). c Slope extraction: The cumulative sum of the rectified EMG trace was computed, becoming monotonically increasing. The linear trend was then removed to get a “flat” signal. A linear regression was computed on the first 30 points of the cumulative signal following the burst onset (i.e., on about the first 15 ms), and the slope of the regression (dashed line in panel c) is taken as a measure of the steepness of the EMG burst (IncSlope and CorSlope, for incorrect and correct EMG bursts, respectively)

Mentions: In such RT tasks, errors are traditionally defined in a binary fashion, on the basis of the overt behavior: The buttonpress is classified as being either correct or erroneous. However, analyses of response-related EMG activity have revealed that erring is not all or none: About 15 %–20 % of correct overt responses are preceded by an early, subthreshold EMG burst from the hand that is associated with the incorrect response (Burle, Possamaï, Vidal, Bonnet, & Hasbroucq, 2002; Eriksen, Coles, Morris, & O’Hara, 1985; Gratton, Coles, & Donchin, 1992; Smid, Mulder, & Mulder, 1990), which is called a “partial error.” In such trials, the incorrect response activation has been successfully suppressed, preventing an overt error (see Fig. 1a and the “Method” section for more details).Fig. 1


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)

Example of a partial error, along with the extracted indices. a Typical electromyographic (EMG) recording showing a partial error. Time 0 is stimulus onset, and the long vertical dashed line indicates the mechanical response. The bottom trace presents the rectified EMG activity of the muscle involved in the correct response. A large EMG burst starts slightly before the mechanical response. This correct EMG burst is preceded by a small burst on the incorrect muscle (top trace), which is far too small to produce an overt response. The extracted indices are the latency of the partial error (IncLat), the correction time (CT, between the incorrect and the correct EMG burst onsets), and the motor time between the correct EMG burst onset and the mechanical response. b Zoom depiction of the partial error, depicting the extracted EMG burst parameters. First, we computed the maximum of the rectified trace. Then we extracted the earliest point preceding, and the latest point following, the peak whose amplitudes were equal to or larger than half of the max amplitude. The time separating the two values was taken as the measure of EMG burst duration (IncDur and CorDur, for incorrect and correct EMG bursts, respectively). The surface under the curve between these two points (shaded area in panel b) was taken as a measure of the EMG burst amplitude (IncSurf and CorSurf, for incorrect and correct bursts, respectively). c Slope extraction: The cumulative sum of the rectified EMG trace was computed, becoming monotonically increasing. The linear trend was then removed to get a “flat” signal. A linear regression was computed on the first 30 points of the cumulative signal following the burst onset (i.e., on about the first 15 ms), and the slope of the regression (dashed line in panel c) is taken as a measure of the steepness of the EMG burst (IncSlope and CorSlope, for incorrect and correct EMG bursts, respectively)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4125819&req=5

Fig1: Example of a partial error, along with the extracted indices. a Typical electromyographic (EMG) recording showing a partial error. Time 0 is stimulus onset, and the long vertical dashed line indicates the mechanical response. The bottom trace presents the rectified EMG activity of the muscle involved in the correct response. A large EMG burst starts slightly before the mechanical response. This correct EMG burst is preceded by a small burst on the incorrect muscle (top trace), which is far too small to produce an overt response. The extracted indices are the latency of the partial error (IncLat), the correction time (CT, between the incorrect and the correct EMG burst onsets), and the motor time between the correct EMG burst onset and the mechanical response. b Zoom depiction of the partial error, depicting the extracted EMG burst parameters. First, we computed the maximum of the rectified trace. Then we extracted the earliest point preceding, and the latest point following, the peak whose amplitudes were equal to or larger than half of the max amplitude. The time separating the two values was taken as the measure of EMG burst duration (IncDur and CorDur, for incorrect and correct EMG bursts, respectively). The surface under the curve between these two points (shaded area in panel b) was taken as a measure of the EMG burst amplitude (IncSurf and CorSurf, for incorrect and correct bursts, respectively). c Slope extraction: The cumulative sum of the rectified EMG trace was computed, becoming monotonically increasing. The linear trend was then removed to get a “flat” signal. A linear regression was computed on the first 30 points of the cumulative signal following the burst onset (i.e., on about the first 15 ms), and the slope of the regression (dashed line in panel c) is taken as a measure of the steepness of the EMG burst (IncSlope and CorSlope, for incorrect and correct EMG bursts, respectively)
Mentions: In such RT tasks, errors are traditionally defined in a binary fashion, on the basis of the overt behavior: The buttonpress is classified as being either correct or erroneous. However, analyses of response-related EMG activity have revealed that erring is not all or none: About 15 %–20 % of correct overt responses are preceded by an early, subthreshold EMG burst from the hand that is associated with the incorrect response (Burle, Possamaï, Vidal, Bonnet, & Hasbroucq, 2002; Eriksen, Coles, Morris, & O’Hara, 1985; Gratton, Coles, & Donchin, 1992; Smid, Mulder, & Mulder, 1990), which is called a “partial error.” In such trials, the incorrect response activation has been successfully suppressed, preventing an overt error (see Fig. 1a and the “Method” section for more details).Fig. 1

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