Delayed monitoring of accuracy errors compared to commission errors in ACC

Bediou, Benoît; Koban, Léonie; Rosset, Sébastien; Sander, David

doi:10.1016/j.neuroimage.2012.02.010

Cited by 27 publications

(17 citation statements)

References 92 publications

(120 reference statements)

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“…The temporal profile of the haptic interface execution error related ERP in a 3D motion task resembles classical ErrP (of conceptual errors and not motion errors), which is also characterized by a sharp negative peak, known as ERN or FRN, and a broader positive peak, known as Pe [9,10]. ErrPs in 2D continuous non-haptic motion task were characterized by four peaks [8], similar to our results in the 3D task.…”

Section: Discussionsupporting

confidence: 83%

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Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

Yazmir

Reiner

Pratt

et al. 2016

Haptics: Perception, Devices, Control, and Applications

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Abstract. We investigated brain potentials recorded by electroencephalography (EEG) signals in response to unpredictable haptic/kinesthetic disturbances to a continuously moving object in a hapto-visual 3D virtual world that highly resembles reality. Participants moved a virtual object from an initial position to a target position in the virtual environment. A large cylinder obscured part of the motion between the origin and the target. The position of the emerging object under the cylinder is disturbed, and hence unexpected, for part of the scenarios. This disturbance is perceived as an error. We examined the EEG signals locked to the error. Our results show a consistent disturbance-locked potential with an early negative peak followed by a positive peak. Peak-to-peak amplitude increased with the disturbance magnitude. Source estimation at the time of the negative and positive peaks revealed a strong activity in the vicinity of Brodmann area (BA) 7, known to be involved in hapto-visual integration and in the neural computation of dynamic motor errors. These results demonstrate the presence of haptic-disturbance-related brain activity under conditions of continuous motion. Results further suggest a feedback signal for error detection and correction in EEG-based Brain-Computer Interfaces (BCI) in applications such as telesurgery, manipulation of remote objects and rehabilitation.

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Section: Discussionsupporting

confidence: 83%

“…Feedback related negativity (FRN) is variation of ERN, evoked by presentation of feedback on incorrect action, and differs by latency range of 150-300 ms [10]. ERN of low amplitude can also be observed in trials with correct responses [9].…”

Section: Introductionmentioning

confidence: 99%

Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

Yazmir

Reiner

Pratt

et al. 2016

Haptics: Perception, Devices, Control, and Applications

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“…This study showed enhanced firing in a large number of MFC neurons during observed errors compared to observed correct actions of another monkey, as well as during reward delivery to the other monkey (Yoshida et al, 2012). Interestingly however, most of these neurons did not respond to self-generated errors, indicating parallel but separate neural populations for the monitoring of self-and other-generated actions (Yoshida et al, 2012 Koban et al, 2012). These authors demonstrated activation of dMFC for errors compared to hits independent of context, whereas the ventral striatum responded as a function of the subjective reward value of errors vs. hits (higher striatum activation for hits in cooperation, and for errors in competition).…”

Section: Monitoring and Evaluating The Actions Of Othersmentioning

confidence: 64%

“…FMRI results indicate that the dorsomedial prefrontal cortex shows higher activation during error monitoring in social relative to individual settings (Radke et al, 2011). In a recent ERP study, Koban et al (2012) showed that the FRN was increased in cooperative compared to competitive context, with underlying sources in the dorsomedial PFC, LPFC, and temporoparietal junction (TPJ), all these regions being typically involved in social cognition (see Figure 2, and cf. Kelley et al, 2002;Mitchell et al, 2005;Saxe and Wexler, 2005).…”

Section: Social Influences On the Monitoring Of Self-generated Actionsmentioning

confidence: 97%

Brain systems underlying the affective and social monitoring of actions: An integrative review

Koban

Pourtois

2014

Neuroscience & Biobehavioral Reviews

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155

159

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(max 170 words)Action monitoring allows the swift detection of conflicts, errors, and the rapid evaluation of outcomes. These processes are crucial for learning, adaptive behavior, and for the regulation of cognitive control. Our review discusses neuroimaging and electrophysiological studies that have explored the contribution of emotional and social factors during action monitoring. Metaanalytic brain activation maps demonstrate reliable overlap of error monitoring, emotional, and social processes in the dorsal mediofrontal cortex (dMFC), lateral prefrontal areas, and anterior insula (AI). Cumulating evidence suggests that action monitoring is modulated by trait anxiety and negative affect, and that activity of the dMFC and the amygdala during action monitoring might contribute to the 'affective tagging' of actions along a valence dimension. The role of AI in action monitoring may be the integration of outcome information with self-agency and social context factors, thereby generating more complex situation-specific and conscious emotional feeling states. Our review suggests that action-monitoring processes operate at multiple levels in the human brain, and are shaped by dynamic interactions with affective and social processes.Keywords: Anterior insula; dorsal cingulate cortex; mediofrontal cortex; amygdala; error monitoring; ERN; feedback processing; social cognition; emotions; cognitive control; emotioncognition interactions; meta-analysis 3 Overview and motivationIn order to adapt their behavior, to detect and learn from errors, and ultimately to increase their chances of survival, humans and other animals have to monitor their actions (Rabbitt, 1966). Flexible regulation of behavior requires its constant evaluation in terms of performance and outcomes, as well as in terms of costs and future consequences. Action and error monitoring have been studied for several decades in psychology and neuroscience (for previous reviews see (Etkin et al., 2011;Moser et al., 2013;Pessoa, 2008;Proudfit et al., 2013;Shackman et al., 2011;Shenhav et al., 2013), we propose that error and action monitoring is an intrinsically affective and social process. However, we show that meta-analytic activation maps support overlapping brain responses to error processing, emotional, and social information processing not only in dMFC, but also in several other brain regions, including anterior insula and lateral prefrontal cortex.Further, recent intracranial electrophysiological recordings showed error-related activity in the amygdala, suggesting this limbic region may contribute to affective responses to errors and negative action outcomes. In the closing part, we outline an integrative framework for 4 understanding the brain systems underlying affective and social interactions with action monitoring, which may be crucial to foster behavioral control in real life.

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“…Monitoring is mainly based on internal representation of own or observed motor action, when the information about the correctness or goal conduciveness of a given action is available already at the time of or even before the onset of the motor response. On the other hand, monitoring has to rely on external feedback when there is no reliable internal knowledge about the correctness or incorrectness at the time of action execution (Holroyd & Coles, 2002;(Bediou, Koban, Rosset, Pourtois, & Sander, 2012). When both types of information are available, later occurring external feedback might be redundant and low in predictive relevance, and thus not elicit a prediction error signal (Heldmann, et al, 2008;Holroyd & Coles, 2002).…”

Section: Effects Of Social Context and Predictive Relevance On Actionmentioning

confidence: 99%

Effects of social context and predictive relevance on action outcome monitoring

Koban

Pourtois

Bediou

et al. 2012

Cogn Affect Behav Neurosci

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Outcome monitoring is crucial for subsequent adjustments in behavior and is associated with a specific electrophysiological response, the feedback-related negativity (FRN). Besides feedback generated by one's own action, the performance of others may also be relevant for oneself, and the observation of outcomes for others' actions elicits an observer FRN (oFRN). To test how these components are influenced by social setting and predictive value of feedback information, we compared event-related potentials, as well as their topographies and neural generators, for performance feedback generated by oneself and others in a cooperative versus competitive context. Our results show that (1) the predictive relevance of outcomes is crucial to elicit an FRN in both players and observers, (2) cooperation increases FRN and P300 amplitudes, especially in individuals with high traits of perspective taking, and (3) contrary to previous findings on gambling outcomes, oFRN components are generated for both cooperating and competing observers, but with smaller amplitudes in the latter. Neural source estimation revealed medial prefrontal activity for both FRN and oFRN, but with additional generators for the oFRN in the dorsolateral and ventral prefrontal cortex, as well as the temporoparietal junction. We conclude that the latter set of brain regions could mediate social influences on action monitoring by representing agency and social relevance of outcomes and are, therefore, recruited in addition to shared prediction error signals generated in medial frontal areas during action outcome observation

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Delayed monitoring of accuracy errors compared to commission errors in ACC

Cited by 27 publications

References 92 publications

Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

Brain systems underlying the affective and social monitoring of actions: An integrative review

Effects of social context and predictive relevance on action outcome monitoring

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