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.