EEG-Based Cognitive Control Behaviour Assessment: an Ecological study with Professional Air Traffic Controllers

Gianluca Borghini,Fabio Babiloni,Simone Pozzi,Géraud Granger,Jean Paul Imbert,Stefano Bonelli,Railane Benhacene,Alessia Golfetti,Giulia Cartocci,Alfredo Colosimo,Gianluca Di Flumeri,Pietro Aricò

doi:10.1038/s41598-017-00633-7

Abstract

Several models defining different types of cognitive human behaviour are available. For this work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by Rasmussen in 1983. This model is currently broadly used in safety critical domains, such as the aviation. Nowadays, there are no tools able to assess at which level of cognitive control the operator is dealing with the considered task, that is if he/she is performing the task as an automated routine (skill level), as procedures-based activity (rule level), or as a problem-solving process (knowledge level). Several studies tried to model the SRK behaviours from a Human Factor perspective. Despite such studies, there are no evidences in which such behaviours have been evaluated from a neurophysiological point of view, for example, by considering brain activity variations across the different SRK levels. Therefore, the proposed study aimed to investigate the use of neurophysiological signals to assess the cognitive control behaviours accordingly to the SRK taxonomy. The results of the study, performed on 37 professional Air Traffic Controllers, demonstrated that specific brain features could characterize and discriminate the different SRK levels, therefore enabling an objective assessment of the degree of cognitive control behaviours in realistic settings.

Highlights

Is due to the ability to compose, from a large repertoire of automated subroutines, the sets suited for specific purposes
The ANOVA performed on the parietal theta Power Spectral Density (PSD) (Fig. 5), demonstrated that it significantly changed across the SRK levels (F(2, 64) = 4.11; p = 0.021)
It has been demonstrated that it was possible to assess, with a high reliability, the ATCOs’ cognitive control behaviour (SRK) while performing realistic Air-Traffic-Management (ATM) scenario by means of specific brain features. Such brain features were selected with the aim to characterize the different SRK levels in terms of “cognitive automatism”, minimizing possible influences of motor activity

Summary

Introduction

Is due to the ability to compose, from a large repertoire of automated subroutines, the sets suited for specific purposes. At the level of rule-based behaviour, the composition of such a sequence of subroutines in a familiar working situation is typically controlled by a stored rule or procedure, which may have been empirically derived during previous occasions, or it may be prepared in correspondence of conscious problem-solving and planning In this case, the performance is goal-oriented but structured by “feedforward control” through stored rules. One aspect of the categorization of human performance in skill/rule/knowledge-based behaviour is the role of the information derived from the environment, which is basically different in the various categories This is the case of unfamiliar situations, when same information or events could be perceived in many different ways depending on the operator’s expertise level[8]. Dorsal frontoparietal network (top-down, endogenous attention) is guided by cognition, involved in control of goal-driven attention, and preparation and application of relevant stimuli selection

Objectives

Methods

Results

Discussion

Conclusion