Cyber operations unfold at superhuman speeds where cyber defense decisions are based on human-to-human communication aiming to achieve a shared cyber situational awareness. The recently proposed Orient, Locate, Bridge (OLB) model suggests a three-phase metacognitive approach for successful communication of cyber situational awareness for good cyber defense decision-making. Successful OLB execution implies applying cognitive control to coordinate self-referential and externally directed cognitive processes. In the brain, this is dependent on the frontoparietal control network and its connectivity to the default mode network. Emotional reactions may increase default mode network activity and reduce attention allocation to analytical processes resulting in sub-optimal decision-making. Vagal tone is an indicator of activity in the dorsolateral prefrontal node of the frontoparietal control network and is associated with functional connectivity between the frontoparietal control network and the default mode network. The aim of the present study was to assess whether indicators of neural activity relevant to the processes outlined by the OLB model were related to outcomes hypothesized by the model. Cyber cadets ( = 36) enrolled in a 3-day cyber engineering exercise organized by the Norwegian Defense Cyber Academy participated in the study. Differences in prospective metacognitive judgments of cyber situational awareness, communication demands, and mood were compared between cyber cadets with high and low vagal tone. Vagal tone was measured at rest prior to the exercise. Affective states, communication demands, cyber situational awareness, and metacognitive accuracy were measured on each day of the exercise. We found that cyber cadets with higher vagal tone had better metacognitive judgments of cyber situational awareness, imposed fewer communication demands on their teams, and had more neutral moods compared to cyber cadets with lower vagal tone. These findings provide neuroergonomic support for the OLB model and suggest that it may be useful in education and training. Future studies should assess the effect of OLB-ing as an intervention on communication and performance.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850429PMC
http://dx.doi.org/10.3389/fnhum.2022.1092056DOI Listing

Publication Analysis

Top Keywords

cyber situational
24
situational awareness
24
vagal tone
20
cyber
16
cyber cadets
16
olb model
12
frontoparietal control
12
control network
12
default mode
12
mode network
12

Similar Publications

Motion Cognitive Decoding of Cross-Subject Motor Imagery Guided on Different Visual Stimulus Materials.

J Integr Neurosci

December 2024

Department of Computer Science and Engineering, Shaoxing University, 312000 Shaoxing, Zhejiang, China.

Background: Motor imagery (MI) plays an important role in brain-computer interfaces, especially in evoking event-related desynchronization and synchronization (ERD/S) rhythms in electroencephalogram (EEG) signals. However, the procedure for performing a MI task for a single subject is subjective, making it difficult to determine the actual situation of an individual's MI task and resulting in significant individual EEG response variations during motion cognitive decoding.

Methods: To explore this issue, we designed three visual stimuli (arrow, human, and robot), each of which was used to present three MI tasks (left arm, right arm, and feet), and evaluated differences in brain response in terms of ERD/S rhythms.

View Article and Find Full Text PDF

Dissecting the Predictors of Cyber-Aggression Through an Explainable Machine Learning Model.

Aggress Behav

January 2025

Key Research Base of Humanities and Social Sciences of the Ministry of Education, Academy of Psychology and Behavior, Tianjin Normal University, Tianjin, China.

The general aggression model (GAM) suggests that cyber-aggression stems from individual characteristics and situational contexts. Previous studies have focused on limited factors using linear models, leading to oversimplified predictions. This study used the light gradient boosting machine (LightGBM) to identify and rank the importance of various risk and protective factors in cyber-aggression.

View Article and Find Full Text PDF

Were You Joking? Interpreting and Responding to Hostile Messages Among Spanish Adolescents.

Psychol Rep

December 2024

Departamento de Metodología de las Ciencias del Comportamiento, Facultad de Psicología, Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain.

This study aims to investigate whether the socio-emotional contextualization of envy influences the interpretation of and reaction to hostile messages on WhatsApp among Spanish adolescents. A total of 190 high school students participated. Participants read two stories containing a hostile message.

View Article and Find Full Text PDF

Random subspace ensemble-based detection of false data injection attacks in automatic generation control systems.

Heliyon

October 2024

Department of Electrical Engineering, Faculty of Engineering, Jouf University, Sakaka, 72388, Saudi Arabia.

Automatic Generation Control (AGC) systems in smart grids are increasingly vulnerable to cyber-attacks, particularly False Data Injection (FDI) attacks, due to their reliance on information and communication technologies. These vulnerabilities pose significant threats to the reliable operation of power systems. To address this challenge, this research paper introduces the machine learning (ML) based cyberattack detection technique designed to identify FDI attacks with the highest accuracy proficiently.

View Article and Find Full Text PDF

EXPRESS: Moral virtues inferences: When limited information affects our attribution of virtues.

Q J Exp Psychol (Hove)

December 2024

Department of Human sciences, Experimental and Applied Psychology Laboratory, Università Europea di Roma, 00163, Rome, Italy.

In everyday life, when we have to formulate judgments, we often end up being influenced by information that is not directly related to the matter at hand. This happens both when we encounter the person in the real-life world, but also in the cyber-world, when for example, we use social networks. In both cases, indeed, based simply on a few images or short stories, we may start to believe fake news or judge someone by generalizing limited information to the overall judgment of that person/situation, as it happens in the halo effect.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!