History of one’s own performance modulates evaluative processing of another’s action outcomes, but not vice versa

In action monitoring, i.e., evaluating an outcome of our behavior, a reward prediction error signal is calculated as the difference between actual and predicted outcomes and is used to adjust future behavior. Previous studies demonstrate that this signal, which is reflected by an event-related brain potential called feedback-related negativity (FRN), occurs in response to not only one's own outcomes, but also those of others. However, it is still unknown if predictions of different actors' performance interact with each other. Thus, we investigated how predictions from one’s own and another’s performance history affect each other by manipulating the task difficulty for participants themselves and their partners independently. Pairs of participants performed a time estimation task, randomly switching the roles of actor and observer from trial to trial. Results show that the history of the other’s performance did not modulate the amplitude of the FRN for the evaluation of one’s own outcomes. In contrast, the amplitude of the observer FRN for the other’s outcomes differed according to the frequency of one’s own action outcomes. In conclusion, the monitoring system tracks the histories of one’s own and observed outcomes separately and considers information related to one’s own action outcomes to be more important.

Optimal confidence for unaware visuomotor deviations

Numerous studies have shown that humans can successfully correct deviations to ongoing movements without being aware of them, suggesting limited conscious monitoring of visuomotor performance. Here, we ask whether such limited monitoring impairs the capacity to judiciously place confidence ratings to reflect decision accuracy (metacognitive sensitivity). To this end, we recorded functional magnetic resonance imaging data while thirty-one participants reported visuomotor cursor deviations and rated their confidence retrospectively. We show that participants use a summary statistic of the unfolding visual feedback (the maximum cursor error) to detect deviations but that this information alone is insufficient to explain detection performance. The same summary statistics is used by participants to optimally adjust their confidence ratings, even for unaware deviations. At the neural level, activity in the ventral striatum tracked high confidence, whereas a broad network including the anterior prefrontal cortex encoded cursor error but not confidence, shedding new light on a role of the anterior prefrontal cortex for action monitoring rather than confidence. Together, our results challenge the notion of limited action monitoring and uncover a new mechanism by which humans optimally monitor their movements as they unfold, even when unaware of ongoing deviations.

Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring

Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from the literature. We asked 12 participants to hold two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans. These results can improve communication between humans and robot with the use of neural activity in real-time.

The monitoring system is attuned to others' actions during dyadic motor interactions

Successful interpersonal motor interactions necessitate the simultaneous monitoring of our own and our partner's actions. To characterize the dynamics of the action monitoring system for tracking self and other behaviors during dyadic synchronous interactions, we combined EEG recordings and immersive Virtual Reality in two tasks where participants were asked to coordinate their actions with those of a Virtual Partner (VP). The two tasks differed in the features to be monitored: the Goal task required participants to predict and monitor the VP's reaching goal; the Spatial task required participants to predict and monitor the VP's reaching trajectory. In both tasks, the VP performed unexpected movement corrections to which the participant needed to adapt. By comparing the neural activity locked to the detection of unexpected changes in the VP action (other-monitoring) or to the participants' action-replanning (self-monitoring), we show that during interpersonal interactions the monitoring system is more attuned to others' than to one's own actions. Additionally, distinctive neural responses to VP's unexpected goals and trajectory corrections were found: goal corrections were reflected both in early fronto-central and later posterior neural responses while trajectory deviations from the expected movement were reflected only in later and posterior responses. Since these responses were locked to the partner's behavior and not to one's own, our results indicate that during interpersonal interactions the action monitoring system is dedicated to evaluating the partner's movements. Hence, our results reveal an eminently social role of the monitoring system during motor interactions.

Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing

Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from Hwang et al. (1). All 16 participants held two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. To explore the temporal and spatial differences in the two conditions, we used time-regression with overlap-control and corrected for multiple-comparisons using Threshold-Free-Cluster Enhancement. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans.

Faktor-faktor yang Berhubungan dengan Tindakan Tidak Aman pada Pekerja di Proyek Pembangunan Apartemen Evencho Margonda

Unsafe action becomes a problem for most work accidents. This study focuses on the factors associated with unsafe actions caused by various kinds of causes or factors both within the worker and the work environment. The construction industry cannot be separated from the potential hazards that can cause work accidents. Analysis of unsafe actions is needed in an effort to prevent the number of accidents at work. The research was conducted using a cross sectional research design or method and included in descriptive research. The interview questionnaire was addressed to workers as many as 75 workers. Research variables aimed at resource persons include knowledge, motivation, supervision, K3 training and the availability of PPE. The assessment of unsafe actions was carried out by entering the results of the interviewee's questionnaire using the SPSS V20 application. From the results of the questionnaire research, 70 workers found unsafe actions were carried out by 44% of the workers. the lack of knowledge factor was 18.7%, the low motivation factor was 46.7%, the supervisory factor was less than 9.3%, the factor of workers who did not attend K3 training was 17.3%, and the factor of lack of availability of Personal Protective Equipment was 10.7 % of all factors with the strongest association with unsafe action. Monitoring and training are required to increase the knowledge of workers so that they can better avoid accidents caused by the factors that have been studied.Keywords: Unsafe measures,Construction Industry, Factors Unsafe action factor (Tindakan yang tidak aman menjadi masalah bagi sebagian besar kecelakaan kerja. Penelitian ini memfokuskan pada faktor-faktor yang terkait dengan tindakan tidak aman yang disebabkan oleh berbagai macam penyebab atau faktor baik di lingkungan pekerja maupun lingkungan kerja. Industri konstruksi tidak lepas dari potensi bahaya yang dapat menyebabkan kecelakaan kerja. Analisis tindakan tidak aman diperlukan dalam upaya mencegah banyaknya kecelakaan kerja. Penelitian dilakukan dengan menggunakan desain atau metode penelitian cross sectional dan termasuk dalam penelitian deskriptif. Kuesioner wawancara ditujukan kepada pekerja sebanyak 75 pekerja. Variabel penelitian yang ditujukan pada nara sumber meliputi pengetahuan, motivasi, supervisi, pelatihan K3 dan ketersediaan APD. Penilaian tindakan tidak aman dilakukan dengan memasukkan hasil kuesioner narasumber menggunakan aplikasi SPSS V20. Dari hasil penelitian kuisioner, 70 pekerja menemukan tindakan tidak aman yang dilakukan oleh 44% pekerja. Faktor pengetahuan kurang 18,7%, faktor motivasi rendah 46,7%, faktor pengawasan kurang dari 9,3%, faktor pekerja yang tidak mengikuti pelatihan K3 sebanyak 17,3%, dan faktor kurangnya ketersediaan alat pelindung diri. Peralatan adalah 10,7% dari semua faktor dengan hubungan terkuat dengan tindakan tidak aman. Pemantauan dan pelatihan diperlukan untuk meningkatkan pengetahuan pekerja agar dapat lebih terhindar dari kecelakaan yang disebabkan oleh faktor-faktor yang telah dipelajari.Kata Kunci: Tindakan tidak aman, Industri Konstruksi, Faktor Faktor tindakan tidak aman.)

Monitoring and Evaluation

This chapter focuses on how monitoring and evaluation plays a pivotal role in the design and execution of initiatives leading up to social transformation. The work evidences that measuring effectiveness is one of the biggest challenges that many social change organizations face; this chapter addresses this issue. It explores and suggests qualitative and quantitative methods to track progress and how to measure growth. Among these methods is a narrative analysis tool that the authors have developed to evidence the ways in which a person's story of self, or the story of a group, transforms overtime. The methods suggested here respond to both local needs and global measures of success, such as the United Nations' sustainable development goals. Conceptually, this section draws from the notions of participatory action monitoring and evaluation as discussed by Chevalier and Buckles, and of the power relations that mediate processes of evaluation discussed by Chapela and Jarillo.

A causal role for frontal cortico-cortical coordination in social action monitoring

Decision-making via monitoring others’ actions is a cornerstone of interpersonal exchanges. Although the ventral premotor cortex (PMv) and the medial prefrontal cortex (MPFC) are cortical nodes in social brain networks, the two areas are rarely concurrently active in neuroimaging, inviting the hypothesis that they are functionally independent. Here we show in macaques that the ability of the MPFC to monitor others’ actions depends on input from the PMv. We found that delta-band coherence between the two areas emerged during action execution and action observation. Information flow especially in the delta band increased from the PMv to the MPFC as the biological nature of observed actions increased. Furthermore, selective blockade of the PMv-to-MPFC pathway using a double viral vector infection technique impaired the processing of observed, but not executed, actions. These findings demonstrate that coordinated activity in the PMv-to-MPFC pathway has a causal role in social action monitoring.