Journal Title: Frontiers in Human Neuroscience
ISSN: 1662-5161 (Online)
Publisher: Frontiers Media S.A.
LCC Subject Category: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Country of publisher: Switzerland
Language of fulltext: English
Full-text formats available: PDF, HTML, ePUB, XML
Bertille Somon (ONERA, Information Processing and Systems DepartmentSalon Air, France)
Bertille Somon (Univ. Grenoble Alpes, CNRS, LPNC UMR 5105Grenoble, France)
Aurélie Campagne (Univ. Grenoble Alpes, CNRS, LPNC UMR 5105Grenoble, France)
Arnaud Delorme (Centre de Recherche Cerveau & Cognition, Pavillon Baudot, Hopital Purpan, BP-25202Toulouse, France)
Arnaud Delorme (Swartz Center for Computational Neurosciences, University of California, San DiegoSan Diego, La Jolla, CA, United States)
Bruno Berberian (ONERA, Information Processing and Systems DepartmentSalon Air, France)
Abstract | Full Text
Nowadays, automation is present in every aspect of our daily life and has some benefits. Nonetheless, empirical data suggest that traditional automation has many negative performance and safety consequences as it changed task performers into task supervisors. In this context, we propose to use recent insights into the anatomical and neurophysiological substrates of action monitoring in humans, to help further characterize performance monitoring during system supervision. Error monitoring is critical for humans to learn from the consequences of their actions. A wide variety of studies have shown that the error monitoring system is involved not only in our own errors, but also in the errors of others. We hypothesize that the neurobiological correlates of the self-performance monitoring activity can be applied to system supervision. At a larger scale, a better understanding of system supervision may allow its negative effects to be anticipated or even countered. This review is divided into three main parts. First, we assess the neurophysiological correlates of self-performance monitoring and their characteristics during error execution. Then, we extend these results to include performance monitoring and error observation of others or of systems. Finally, we provide further directions in the study of system supervision and assess the limits preventing us from studying a well-known phenomenon: the Out-Of-the-Loop (OOL) performance problem.