How the workload impacts on cognitive cooperation: A pilot study

Multivariate model for cooperation: bridging social physiological compliance and hyperscanning

The neurophysiological analysis of cooperation has evolved over the past 20 years, moving towards the research of common patterns in neurophysiological signals of people interacting. Social physiological compliance (SPC) and hyperscanning represent two frameworks for the joint analysis of autonomic and brain signals, respectively. Each of the two approaches allows to know about a single layer of cooperation according to the nature of these signals: SPC provides information mainly related to emotions, and hyperscanning that related to cognitive aspects. In this work, after the analysis of the state of the art of SPC and hyperscanning, we explored the possibility to unify the two approaches creating a complete neurophysiological model for cooperation considering both affective and cognitive mechanisms We synchronously recorded electrodermal activity, cardiac and brain signals of 14 cooperative dyads. Time series from these signals were extracted, and multivariate Granger causality was computed. The results showed that only when subjects in a dyad cooperate there is a statistically significant causality between the multivariate variables representing each subject. Moreover, the entity of this statistical relationship correlates with the dyad’s performance. Finally, given the novelty of this approach and its exploratory nature, we provided its strengths and limitations.

Toward a cooperation index based on EEG-workload causality: preliminary findings on aerospace-like tasks

According to Human-System Integration analyses, cooperation between humans is one of the most relevant factors in many of today's human activities: do not take it into account in models of working environments is highly farfetched. Although the Human Factor aspects have obtained much benefit from the use of neurophysiological signals to estimate human-machine interaction, very few are the indications about neurophysiological analysis of human cooperation deviating from typical laboratory tasks. Among these, some evidence showed that there is a relationship between the mental workload experienced by the subjects cooperating and some characteristics of the brain network obtained through multi-subjects connectivity analysis. Accordingly, this work aimed to identify common dynamics in time series that describe the EEG-based mental workload of cooperating subjects and to exploit this information to create an index of cooperation. In order to answer the question whether a causality between the workload values of the two subjects can be in some way discerned and related to the cooperation required by the task, Granger's causality test has been performed. This method was applied to two different tasks simulating features of the aerospace domain. The results showed that the causality test was statistically significant for the most collaborating couple. In addition, causality values are modulated by the presence of real couples compared to fake couples. The extension of the experimental sample could open up the possibility for the development of an objective and neurophysiological signals-based cooperation index.