Cyber operations unfold at superhuman speeds, which pose high demands on human cyber operators. Due to the growing global network coverage and increasing interconnectedness between cyber and physical domains, cyber operations are conducted in a complex socio-technical system consisting of diverse human-machine and human-human interactions. Performance in this socio-technical system is influenced by several factors across multiple contexts including unique challenges spanning cyber, physical, cognitive, and social domains (Jøsok et al., 2016, 2017; Agyepong et al., 2019). The resulting working-environment poses a complex selective pressure requiring a seemingly unique but currently understudied competency profile (Jøsok et al., 2017, 2019; Knox et al., 2017, 2018; Lugo and Sütterlin, 2018).

Organizations source their cyber operations to Security Operation Centers (SOCs) consisting of teams and organizational units that work around the clock to detect, assess, and respond to cyber threats. SOCs are usually hierarchically organized where analyst-level responsibilities such as detecting, investigating, and reporting on cyber threats are assigned to technical personnel (cyber operators), while decision-making responsibilities are assigned to other individuals higher up in the SOC hierarchy (Staheli et al., 2016). Thus, cyber operators are responsible for establishing situational awareness (SA) during cyber threat situations and communicating their SA to decision-makers. According to the SA model (Endsley, 1995), establishing SA for decision-making in a socio-technical system is achieved in three levels (Figure 1A), where all levels must be achieved in order to have full SA. SA Level 1 entails perceiving the elements of the situation, SA Level 2 entails comprehending the relationship between these elements, and SA Level 3 entails using the comprehension to predict possible future situational states (Endsley, 1995).

Seven requirements for achieving cyber SA (CSA) for decision-making during cyber threat situations have been proposed (Barford et al., 2009). These requirements can be arranged under the SA model (Figure 1B) where the establishment of SA Level 1 starts with having perceived indicators of compromise (Barford et al., 2009). Establishing shared CSA during a cyber threat situation depends on both technical expertise and socio-cognitive abilities (Franke and Brynielsson, 2014; Jøsok et al., 2016, 2019). The outcome of cyber defense decision-making is based on how well the cyber operators can communicate their CSA to decision-makers that are often less technically competent (Knox et al., 2018; Ask et al., 2021a). Cyber operators must therefore be capable of flexibly transitioning between cyber-oriented analytical processes and socially oriented processes such as adjusting communication to the needs of the recipient. This makes communication for shared CSA a dynamic and challenging process where the same complex information is communicated in different ways depending on the recipient’s background (Ahrend et al., 2016; Staheli et al., 2016). The Hybrid Space framework (Figure 2A) was developed to illustrate the interconnectedness between the cyber and physical (cyber-physical) domains, and the tension between strategic and tactical goals in decision-making and action, thus outlining the cognitive landscape that cyber operators must navigate (Jøsok et al., 2016).

Transitioning between quadrants in the Hybrid Space to relay technical information to non-technical individuals, will in theory require the cyber operator to switch between mindsets (Jøsok et al., 2016; Knox et al., 2018). Doing this effectively depends on the cyber operator’s ability to monitor and regulate their cognitions. Metacognition is the ability to direct attention internally to observe one’s own cognitions, emotions, and behaviors, and assess if they align with goals, and consciously regulate them if needed (Flavell, 1979; Efklides, 2008). Metacognition is required for establishing accurate SA (Endsley, 2020). Previous studies on cyber cadets have shown that self-location and movements in the Hybrid Space is predicted by metacognition and self-regulation (Figure 2B; Knox et al., 2017, 2019; Jøsok et al., 2019) and team communication measurements (Lugo et al., 2017a). When individuals are processing information in different domains, their cognitive focus is in different quadrants of the Hybrid Space. Communicating across quadrants of the Hybrid Space (Figure 2C) requires constant re-adjustment of communication flow and message content (Jøsok et al., 2017; Knox et al., 2018).

Recent reviews suggest that there is a lack of research on individual- and team-level SOC team communication and performance indicators (Agyepong et al., 2019; Ask et al., 2021a). The Orient, Locate, Bridge (OLB) model (Figure 2D; Knox et al., 2018) was developed based on the Hybrid Space framework to serve as a metacognitive tool supporting communication and sharing of CSA between individuals located in different quadrants of the Hybrid Space. The OLB model is a three-phase model where each phase builds on the previous phase to facilitate efficient communication (Knox et al., 2018). In the orienting phase, the cyber operator applies metacognition to self-locate in the Hybrid Space to get a grasp of their current mindset (e.g., where their focus is, if they are stressed, etc.) and their CSA. In the locating phase, the cyber operator applies perspective taking to understand the specific information and communication needs of the recipient based on their location in the Hybrid Space. In the bridging phase, the cyber operator uses the insights from the orienting and locating phases as a guide for adapting communication style and content. This last phase ensures that communication can be grounded and CSA can be shared and calibrated between the cyber operator and the communication partner.

In more general terms, OLB-ing can be understood as a stepwise cognitive control process involving the deliberate (endogenously controlled) and flexible transition between attention to internal and self-referential states (e.g., Hybrid Space location, stress levels) and externally oriented cognitive processes. Cognitive control is the goal-directed coordination of task-relevant cognitive processes while inhibiting task-irrelevant automatic processes (Friedman and Robbins, 2022). In the brain, goal-directed cognitive processes are organized by a network of brain areas called the frontoparietal control network (FPN; Duncan, 2010; Menon and D’Esposito, 2022). This includes integrating attention to information from the external-present task environment and attention to internal-future goal-representations to coordinate externally directed cognitive processes and behaviors towards goal attainment (Nee and D’Esposito, 2016; Nee, 2021). On the other hand, attention to internal and self-referential information such as thoughts or the intensity and significance of one’s emotional state is processed and maintained by the default mode network (DMN; Raichle et al., 2001; Raichle, 2015).

Both the FPN and DMN have anatomical hubs in the prefrontal cortex (PFC; Raichle, 2015; Menon and D’Esposito, 2022). The dorsolateral PFC (DLPFC) is one of the main hubs in the FPN (Menon and D’Esposito, 2022), while medial PFC structures (MPFC) constitute one of the main hubs of the DMN (Raichle, 2015). Activity in the FPN and DMN is often anticorrelated (Raichle et al., 2001; Fox et al., 2005; Chang and Glover, 2009), and DLPFC and MPFC activity is often anti-correlated during FPN-related tasks (Chen et al., 2013; Liston et al., 2014).

Both the DLPFC and MPFC are involved in metacognitive processes (Fleur et al., 2021). The DLPFC is specifically involved in metacognitive decision-making, while both DLPFC and MPFC are involved in prospective metacognitive judgments (Vaccaro and Fleming, 2018; Fleur et al., 2021). Cognitive processes can go from being metacognitively controlled (Shimamura, 2008; Friedman and Robbins, 2022) to reactive (stimulus-driven) when individuals are subjected to stress or under emotional influence (Baek and Falk, 2018; Poth, 2021). Previous studies on cyber operators identified several emotional processes that may have differing effects on teamwork and communication (Lugo et al., 2016, 2017b, 2021; Ask et al., 2021b). Emotions can be interpreted according to intensity (arousal) and whether they are positive, negative, or neutral (valence; or mood), and are processed differently by DMN and FPN structures (Golkar et al., 2012; Terasawa et al., 2013; Fujimoto et al., 2021; Nejati et al., 2021). Stress reduces connectivity between the DMN and FPN (Chand et al., 2020), suggesting ways for how environmental pressures can disturb the flexible transition between self-referential and analytical processing.

From a neuroergonomics perspective, when faced with a challenging environment, the brain will find something akin to “the path of least resistance” to optimal performance (Botvinick, 2007; Wickens et al., 2015; Hagura et al., 2017; Khalil et al., 2019). This means initiating the cognitive processes and behaviors that are the least taxing to apply in order to reach a goal, given the environmental demands. If resulting in goal-attainment, they become part of a strategy for reaching the same goals under similar circumstances. The precision, combination, and order of the cognitions and behaviors, or trying new strategies to compare efficiency with older successful ones, are deliberately or unconsciously adjusted with experience via metacognitive and cognitive control processes (Flavell, 1979; Efklides, 2008; Khalil et al., 2019). Because the cybersecurity working-environment places such a heavy cognitive load on cyber operators (Jøsok et al., 2016; Agyepong et al., 2019), strategies for improved communication must not only be successful, but they must also be neuroergonomic to be sustainable. If the processes outlined by the OLB model are both successful and neuroergonomic in a cybersecurity working-environment, then they should be selected through evolutionary processes by the individuals working in those environments. If so, correlates of the neurocognitive processes underlying OLB-ing should be related to the outcomes predicted by the model (Knox et al., 2018).

Expert cyber incident response teams impose less communication demands on their teams compared to novices (Buchler et al., 2016; Lugo et al., 2017a). Because experts have spent more time in cybersecurity working-environments, they have also had more time to go through evolutionary cycles for selecting neuroergonomic approaches to make communication more efficient. If the OLB model is neuroergonomic, the discrepancy in imposed communication demands between novices and experts may suggest that expert teams have a higher conscious or unconscious adoption rate of OLB-related cognitive processes for communication.

The main aim of this study is to assess some of the neurocognitive assumptions of the OLB model (Knox et al., 2018) to begin validating its potential as a neuroergonomic approach for CSA communication in cyber threat situations. This is done using peripheral proxies for DLPFC activity and FPN-DMN connectivity, and measurements of CSA, metacognition, and team communication. Prefrontally modulated vagal tone, quantified as vagally mediated heart rate variability (vmHRV), represents the beat to beat variations in heart rate that are influenced by the vagus nerve and modulated by the PFC (Appelhans and Luecken, 2006; Thayer et al., 2012). Vagal tone is an indicator of DLPFC activity (Brunoni et al., 2013a; Nikolin et al., 2017) and functional connectivity between the FPN and the DMN at rest (Chand et al., 2020). Associations have been found between metacognition and vagal tone in non-cyber tasks (Meessen et al., 2018). Vagal tone may therefore serve as a potential marker for the FPN-DMN interactions relevant for OLB-ing during cyber operations. Thus, we hypothesize that individuals with higher vagal tone have higher metacognitive accuracy and impose lower communication demands on their teams than individuals with lower vagal tone (hypothesis 1: H₁).

The processing of emotional stimuli may influence cyber team performance (Lugo et al., 2016, 2017b, 2021; Ask et al., 2021b) for example by diverting attention away from externally directed and endogenously controlled cognitive processing and more towards stimulus-driven external (Poth, 2021) or internally directed self-referential processing (Baek and Falk, 2018). The DLPFC is involved in the self-report of valence (Nejati et al., 2021) and can be distinguished from other prefrontal structures based on this function (Terasawa et al., 2013; Fujimoto et al., 2021; Nejati et al., 2021). Higher vagal tone is associated with stress resilience (Hildebrandt et al., 2016) and endogenous control over attention during emotional distractors (Geisler and Kubiak, 2009; Park et al., 2012, 2013) known to elicit DMN processing (Winston et al., 2003; Zhou et al., 2020). Thus, we hypothesize that individuals with higher vagal tone, which reflects DLPFC function, will have different self-reported mood ratings than individuals with lower vagal tone (H₂).

Metacognition is required for establishing accurate SA (Endsley, 2020). The Hybrid Space framework and the OLB model suggest that metacognition is required for efficient communication of CSA with other individuals in the Hybrid Space (Jøsok et al., 2016; Knox et al., 2018). Metacognitive accuracy, how correctly an individual is in evaluating their own performance, can manifest as correctly judging performance as bad or good. Because both establishing SA and sharing CSA through communication is reliant on metacognition (Jøsok et al., 2016; Knox et al., 2018; Endsley, 2020), we hypothesize that individuals with more correct CSA ratings have higher metacognitive accuracy than individuals with less correct CSA ratings (H₃).

In this study, we aimed to assess some of the neurocognitive assumptions of the OLB model (Knox et al., 2018) to begin validating its potential as a neuroergonomic approach for CSA communication in cyber threat situations. This was done in a sample of cyber cadets participating in a cyber engineering exercise by using a combination of psychophysiological, CSA, metacognitive, and team measurements targeted at assessing some of the OLB model’s implicit underlying neurocognitive assumptions (Jøsok et al., 2016; Knox et al., 2018). The OLB model outlines an adaptive three-step metacognitive control process for how to communicate efficiently between individuals under varying cyber situational dynamics (Knox et al., 2018). In the OLB model, the communicator integrates self-referential, self-other, situational, and task-goal information to ground communication and establish a shared CSA. This requires the prefrontal part of the brain to coordinate activity across brain structures and networks (Nee and D’Esposito, 2016; Morales et al., 2018; Nee, 2021; Friedman and Robbins, 2022).

Being a proxy for activity in prefrontal structures relevant for OLB-ing (Brunoni et al., 2013a; Nikolin et al., 2017; Chand et al., 2020), we hypothesized that individuals with high vagal tone had higher metacognitive accuracy and imposed less communication demands on their teams compared to individuals with low vagal tone (H₁). In our initial analyses, we found that vagal tone was associated with higher metacognitive accuracy for prospective judgments about individual performance and team performance. This is in line with previous studies suggesting that the DLPFC is involved in prospective metacognitive performance estimations (Vaccaro and Fleming, 2018; Fleur et al., 2021). In our between-group analyses comparing differences in metacognitive accuracy and communication demands between individuals with low and high vagal tone, we found that team-level metacognitive accuracy was significantly higher in the high vagal tone groups. Individual-level metacognitive accuracy was not significantly different between vagal tone groups. That the findings regarding individual metacognitive accuracy for the whole sample could not be replicated in the sub-group analysis could be due to the size of the sub-groups. Both vagal tone (Brunoni et al., 2013a; Nikolin et al., 2017; Chand et al., 2020) and prospective metacognitive judgments are influenced by activity in the DLPFC (Fleur et al., 2021). Vagal tone is, however, influenced by several physiological processes other than DLPFC activity (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996), as opposed to prospective metacognitive judgments which are dependent on the DLPFC (Vaccaro and Fleming, 2018). Thus, to make sure to account for this possible influence on our results, we did a follow-up analysis assessing differences in vagal tone between individuals with high and low individual and team-level metacognitive accuracy. Vagal tone was higher in individuals with higher metacognitive accuracy for both individual and team-level performance estimations. Finally, in line with our hypothesis, we also found that individuals with high vagal tone imposed lower communication demands on their team compared to individuals with low vagal tone.

Our findings should be interpreted in light of previous research suggesting that communication inefficiencies are one of the main problems facing SOC teams (Agyepong et al., 2019; Ask et al., 2021a). These inefficiencies occur both between analyst-level personnel, for example where cyber operators fail to communicate threat and defense knowledge, ultimately resulting in team members wasting time researching a problem that someone on the team has already solved (Jariwala et al., 2012; Ahrend et al., 2016; Skopik et al., 2016; Staheli et al., 2016). Communication inefficiencies also occur between analysts-level and decision-making personnel, where critical information for establishing CSA may get lost as it is communicated from technical personnel and upwards in the decision-making hierarchy to less technical personnel (Staheli et al., 2016; Jøsok et al., 2017; Knox et al., 2018). Suggestions for improving communication between SOC teams have been proposed, such as establishing shared mental models for communication and transactive memories about the expertise and knowledge of team members (Steinke et al., 2015; Hámornik and Krasznay, 2018). This is considered especially critical during cyber threat situations where time pressure is high, and one-way communication is required where all critical information is communicated at once. Our findings may indicate that OLB-related metacognitive processes may help facilitate and proliferate a better understanding of the knowledge and competencies of individuals on the team, and that this is related to establishing better team-level CSA.

Our sample consisted of cyber cadets that know and are used to interact with each other. Nevertheless, our findings may also have relevance for the challenges that arise when information has to be communicated between people that have different priorities spanning the cyber-physical and strategic-tactical dimensions of cyber operations (Jøsok et al., 2016, 2017). Suggested approaches for developing shared mental models for SOC team communication mainly focus on establishing what information should be communicated ahead of time, or understanding the procedures related to performing the tasks of different members of the team (Steinke et al., 2015; Hámornik and Krasznay, 2018). Due to different stakeholders having different communication needs (Ahrend et al., 2016; Jøsok et al., 2016), it is hard to define any set protocol for what to communicate, and it is generally understood that approaches must be adapted to the needs of SOC teams and their clients (Ask et al., 2021a). This is especially the case for communication between technical and non-technical personnel in situations where communication must be adapted according to changing situational dynamics (Jøsok et al., 2017; Ask et al., 2021a). Thus, developing good process-based models for dynamic communication that can be implemented in cyber defense training and education is urgently needed (Knox et al., 2018; Ask et al., 2021a). This is where the findings in the present study may be relevant. Due to the cognitive load associated with the cybersecurity working environment, models for communication must be feasible to apply in high-stress situations to be sustainable. Applying metacognitive processes in a three-step fashion as outlined in the OLB model may also provide opportunities for regulating stress prior to communication. This may result in an increased capacity for processing the information that is communicated, or remembering what should be communicated. Thus, while having a strategic plan for what to communicate during a cyber threat situation is considered crucial for communication to be efficient (Steinke et al., 2015; Hámornik and Krasznay, 2018), approaches such as the OLB model (Knox et al., 2018) that are designed for situational adaptation may serve as a neuroergonomic complement to facilitate strategic communication.

The present findings may shed light on results from other studies on cyber defense teams indicating that experts impose less communication demands on their teams than novices (Buchler et al., 2016; Lugo et al., 2017a). This may suggest that experts have a better metacognitive understanding of team competence and more efficient (shared) mental models for communication than novices. If expert team communication efficiency reflects a higher rate of adoption of neuroergonomic strategies in response to working under stress, then even unconscious strategy adoption may result in a higher number of shared, albeit implicit mental models for team communication. Overlap of implicit mental models may depend on the degree of strategy convergence that is enforced by environmental pressure. Learning cognitive skills is associated with reduced activity in brain areas responsible for the skill, which is considered a marker for increased processing efficiency (Fleur et al., 2021). However, having an accurate mental model of the competencies of team members may serve as an anchor for cognitive effort one considers necessary for performing well during a cyber threat situation. An example may be finding a compromise between social loafing and effort where the highest level of cognitive output can be sustained for the longest period of time. Previous research has indicated that level 3 situational awareness is more taxing on working memory than preceding levels (Gutzwiller and Clegg, 2013). Cognitive strategies that serve to balance personal knowledge acquisition with cognitive offloading without compromising team performance may compete with strategies for maximizing expertise and being the one to solve any given problem. At intermediate levels of environmental stress, any one strategy, or a flexible combination of the two, maybe equally sustainable. Under increasing loads, however, strategies should converge on those optimizing for balancing cognitive offloading with sustained effort, which may favor metacognitive team processes over individual processes. Strategy convergence may, however, depend on how salient tasks are, and the interests and priorities of the individual (Wickens et al., 2015).

It has been suggested that individual and team-based metacognitions depend on different processes (Shea et al., 2014). Interestingly, while being associated with the accuracy of prospective performance judgments, vagal tone was not associated with prospective judgments of confidence in individual or team performance, but was negatively associated with retrospective confidence judgments of team success. In turn, retrospective judgments of performance were negatively associated with the accuracy of prospective metacognitive judgments of team performance, but not individual performance. Retrospective judgments are associated with activity in the parahippocampal structures and the inferior frontal gyrus (Vaccaro and Fleming, 2018), but are typically assessed at the individual level in neurocognitive studies and not in a team setting. While fast acting connections between the DLPFC and hippocampal structures have been established (Friedman and Robbins, 2022), recent studies show that tracking dynamic social behavior is dependent on interactions between the DLPFC and dorsomedial PFC (McDonald et al., 2020).

This article argues that the processes outlined by the OLB model rely on the coordinated and flexible transition between FPN- and DMN-related information processing, which is a cognitive control process (Nee and D’Esposito, 2016; Nee, 2021; Friedman and Robbins, 2022). Vagal tone measured at rest is associated with connectivity between the DMN and FPN (Chand et al., 2020). The transition between cognitive processes can either be subject to self-regulated metacognitive control (Shimamura, 2008) or stimulus-driven as a result of stress and emotional influence (Baek and Falk, 2018; Poth, 2021). A recent study found that the FPN was involved in metacognitive judgments along with DMN structures, where activity in both the DLPFC and MPFC was negatively associated with confidence judgments (Morales et al., 2018). Emotions are processed differently by DMN and FPN structures (Golkar et al., 2012; Terasawa et al., 2013; Fujimoto et al., 2021; Nejati et al., 2021), while stress disrupts connectivity between the FPN and DMN along with its association with vagal tone (Chand et al., 2020). Previous studies on cyber cadets identified several emotional and self-regulatory processes that may have differing effects on teamwork and communication (Lugo et al., 2016, 2017b, 2021; Knox et al., 2017; Jøsok et al., 2019; Ask et al., 2021b). As the DLPFC is involved in mood processing (Golkar et al., 2012; Nejati et al., 2021), we hypothesized that individuals with higher vagal tone had different self-reported mood ratings than individuals with lower vagal tone (H₂). In line with our second hypothesis, we found that vagal tone was negatively associated with mood. This finding was also replicated in our subgroup analysis where individuals with higher vagal tone had lower self-reported mood than individuals with lower vagal tone.

The valence-arousal plots showing daily mood and arousal for individuals with high and low vagal tone indicated that individuals with high vagal tone had more neutral moods on day 3 of the exercise, while individuals with low vagal tone had more positive moods. In a previous study, we found that variations in daily affect were associated with experienced team workloads among cyber cadets participating in a cyber defense exercise (Ask et al., 2021b). While the significance of such findings may be unclear with respect to exercise outcomes (Lund, 2022), the findings in the present study may serve to further elucidate their relevance beyond suggesting that individual characteristics influence team dynamics. While stress and urgency may disturb analytic cognitive processes (Poth, 2021), positive moods, as opposed to neutral moods may also result in transitioning from analytical processing to stimulus-oriented processing (Baek and Falk, 2018), for example as a result of optimism bias and mood congruent processing, lack of suspicion, or overconfidence (Vishwanath et al., 2018; Canham et al., 2022; Sütterlin et al., 2022). In practice, this may result in reduced situational understanding, as indicated in our study by positive moods being a significant negative predictor of both individual and team-level prospective metacognitive judgments of performance, as well as being a positive predictor of retrospective judgments of team success. Retrospective judgments of team success were as noted negatively associated with the accuracy of team-level metacognitive judgments. These findings also mirror other studies where overconfidence has been associated with worse threat detection abilities among IT and cybersecurity personnel (Butavicius et al., 2016; Jampen et al., 2020; Sütterlin et al., 2022).

In the present study, having high metacognitive accuracy could be either due to accurately judging performance as bad or as good. Thus, it was technically possible that individuals with high metacognitive accuracy could perform equal to- or even worse on CSA estimations than individuals with low metacognitive accuracy as long as they were more correct in their performance estimations. Because good cyber defense decision-making is based on having accurate CSA (Barford et al., 2009), and metacognitive accuracy is necessary for correct SA (Endsley, 2020), we also tested the hypothesis that individuals with higher metacognitive accuracy would have more correct CSA ratings than individuals with lower metacognitive accuracy (H₃). We found that individuals with higher metacognitive accuracy also had more correct CSA ratings at both the individual and team-level. This supports our hypothesis and the findings of Endsley (2020). No measurement of team dynamics other than retrospective judgments of performance was associated with accurately judging team performance and team-level CSA ratings. This stresses the importance of training metacognitive skills to ensure that SOC teams are able to generate and share accurate CSA. In other words, team based training in absence of metacognitive training may not efficiently provide all the skills necessary for ensuring SOC team performance. This should arguably occur during education rather than relying on individual SOC teams to ensure that new recruits learn metacognitive skills. However, this may challenge traditional educational and organizational practices (Jøsok et al., 2017; Knox et al., 2018) as reflected in the plethora of challenges SOC teams face (Agyepong et al., 2019; Ask et al., 2021a). Originally developed as a pedagogical tool, the OLB model (Knox et al., 2018) may serve as a flexible and cost-effective approach to metacognitive training that is easy to implement across learning situations and institutions.

To the best of our knowledge, this is the first study providing neuroergonomic insights into the relationship between communication in teams and metacognitive CSA accuracy in a cybersecurity setting. While we aimed to provide neuroergonomic support for the OLB model, the present findings could also be used to argue for the importance of psychophysiological measurements in recruitment, training, and performance monitoring. Previous research found associations between vagal tone and performance among tactical personnel in non-cybersecurity settings (including military; Tomes et al., 2020). The present study is the first to show that vagal tone may also serve as an indicator of performance in a cybersecurity setting. To the extent that vagal tone reflects the ability for self-regulation (e.g., Segerstrom and Nes, 2007; Reynard et al., 2011), our findings are an addition to a growing body of literature showing relationships between self-regulation and movements in the Hybrid Space (Knox et al., 2017, 2019; Jøsok et al., 2019). Finally, the present findings also provide support for the scarce literature on relationships between vagal tone and metacognitive accuracy (Meessen et al., 2018).

Prefrontally modulated vagal tone, an indicator of activity in brain structures relevant for coordinating the cognitive processes underlying OLB model execution, is associated with metacognitive cyber situational awareness and imposing lower communication demands on the team. Based on the assumption that individuals working in high-stress-, high-cognitive load-environments will choose neuroergonomic cognitive strategies to reach task goals, the present findings suggest that the OLB model is neuroergonomic in such environments. Individuals with higher vagal tone had more neutral moods which could be necessary for allocating more attentional resources to analytical processing. Furthermore, individuals with higher CSA had higher metacognitive accuracy compared to individuals with lower CSA supporting previous studies suggesting that metacognitive accuracy is necessary for achieving situational awareness. The present study highlights the potential of using neurophysiological measurements as performance indicators. Future studies are needed to explicitly address the effect of using the OLB model as the basis for a metacognitive intervention to improve communication and team performance, as well as replicating the findings of the present study.

The datasets presented in this article are not readily available because access to raw and processed data is restricted in accordance with agreement between the researchers and the Norwegian Defense University College, Cyber Academy (NDCA). Requests to access the datasets should be directed to corresponding author.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study. The present study conformed to institutional guidelines and was eligible for automatic approval by the Norwegian Social Science Data Services’ (NSD) ethical guidelines for experimental studies. Participation was voluntary and all participants were informed about the aims of the study, the methods applied, that they could withdraw from participation at any time and without any consequences, and that if they did so all the data that was gathered from them would be deleted. After volunteering to participate in the study, participants were asked to provide informed consent on the first page of an online form where baseline data was collected. Participants were asked to generate and remember a unique participant ID that they would use during data collection for the duration of the study.

TA: study design and methods, data collection, analysis, writing of original draft, review and editing. BK: study design, writing of original draft, review and editing. RL and SS: study design and methods, review and editing. IH: exercise organization, scoring of CSA questionnaires for analysis, writing of original draft. All authors contributed to the article and approved the submitted version.