Out of the Loop, in Your Bubble: Mind Wandering Is Independent From Automation Reliability, but Influences Task Engagement

Are Mindfulness and Mind-Wandering Opposite Constructs? It Depends on How Mindfulness is Conceptualised

This study investigated if trait mindfulness and its components, mindful attention, acceptance, and non-judging correlate negatively with self-reported and indirect markers of mind-wandering. The 552 participants of the study completed an anonymous online questionnaire consisting of trait mindfulness and mind-wandering scales. They also completed the computer-based Sustained Attention to Response Task (SART), an objective measure of mind-wandering. The total mindfulness score and acceptance and non-judging subscale scores were strongly negatively correlated with both self-reported trait mind-wandering (TMW) and SART indices of mind-wandering. In contrast, attention was significantly positively correlated with both. These findings suggest that trait mindfulness conceptualised as a multi-component construct, but not a uni-component one, is probably an opposing construct to trait mind-wandering. Furthermore, mindfulness and its components, acceptance and non-judging, are associated with a reduction in the more common form of SART errors. However, only the acceptance component made a unique contribution to the variance in TMW and SART performance. Therefore, it is advisable for researchers to specify whether they investigated mindfulness as a uni-component or multi-component construct. Furthermore, it would be beneficial if future research investigates the relationship of mindfulness and its components with mind-wandering further by also incorporating a measure of state mindfulness.

Degraded States of Engagement in Air Traffic Control

Safety studies have identified attention as a recurring cause of incidents and accidents in air traffic control. However, little is known of the precise attentional states that lead to degraded ATC performance. Therefore, we surveyed 150 French en route air traffic controllers on the causes of and impacts on perceived cooperation, safety, and performance of seven degraded attentional states from the literature: task-related and task-unrelated mind wandering, mental overload, inattentional deafness and blindness, attentional entropy, and perseveration. Our findings indicated that task-related and task-unrelated mind wandering were the most prevalent but had the least impact on perceived safety. Conversely, inattentional blindness and attentional entropy were less reported but were considered a significant safety concern, while inattentional deafness affected cooperation. Most states were experienced in workload levels consistent with the literature. However, no other factor such as shift work was identified as a cause of these states. Overall, these findings suggest that “attention” is not a specific enough subject for ATC, as attentional issues can occur in various conditions and have different impacts. As far as safety is concerned, inattentional blindness should be the prime target for further research. Neuroergonomics in particular could help develop dynamic countermeasures to mitigate its impact.

Mind Wandering Influences EEG Signal in Complex Multimodal Environments

The phenomenon of mind wandering (MW), as a family of experiences related to internally directed cognition, heavily influences vigilance evolution. In particular, humans in teleoperations monitoring partially automated fleet before assuming manual control whenever necessary may see their attention drift due to internal sources; as such, it could play an important role in the emergence of out-of-the-loop (OOTL) situations and associated performance problems. To follow, quantify, and mitigate this phenomenon, electroencephalogram (EEG) systems already demonstrated robust results. As MW creates an attentional decoupling, both ERPs and brain oscillations are impacted. However, the factors influencing these markers in complex environments are still not fully understood. In this paper, we specifically addressed the possibility of gradual emergence of attentional decoupling and the differences created by the sensory modality used to convey targets. Eighteen participants were asked to (1) supervise an automated drone performing an obstacle avoidance task (visual task) and (2) respond to infrequent beeps as fast as possible (auditory task). We measured event-related potentials and alpha waves through EEG. We also added a 40-Hz amplitude modulated brown noise to evoke steady-state auditory response (ASSR). Reported MW episodes were categorized between task-related and task-unrelated episodes. We found that N1 ERP component elicited by beeps had lower amplitude during task-unrelated MW, whereas P3 component had higher amplitude during task-related MW, compared with other attentional states. Focusing on parieto-occipital regions, alpha-wave activity was higher during task-unrelated MW compared with others. These results support the decoupling hypothesis for task-unrelated MW but not task-related MW, highlighting possible variations in the "depth" of decoupling depending on MW episodes. Finally, we found no influence of attentional states on ASSR amplitude. We discuss possible reasons explaining why. Results underline both the ability of EEG to track and study MW in laboratory tasks mimicking ecological environments, as well as the complex influence of perceptual decoupling on operators' behavior and, in particular, EEG measures.

How Can Physiological Computing Benefit Human-Robot Interaction?

As systems grow more automatized, the human operator is all too often overlooked. Although human-robot interaction (HRI) can be quite demanding in terms of cognitive resources, the mental states (MS) of the operators are not yet taken into account by existing systems. As humans are no providential agents, this lack can lead to hazardous situations. The growing number of neurophysiology and machine learning tools now allows for efficient operators’ MS monitoring. Sending feedback on MS in a closed-loop solution is therefore at hand. Involving a consistent automated planning technique to handle such a process could be a significant asset. This perspective article was meant to provide the reader with a synthesis of the significant literature with a view to implementing systems that adapt to the operator’s MS to improve human-robot operations’ safety and performance. First of all, the need for this approach is detailed regarding remote operation, an example of HRI. Then, several MS identified as crucial for this type of HRI are defined, along with relevant electrophysiological markers. A focus is made on prime degraded MS linked to time-on-task and task demands, as well as collateral MS linked to system outputs (i.e., feedback and alarms). Lastly, the principle of symbiotic HRI is detailed and one solution is proposed to include the operator state vector into the system using a mixed-initiative decisional framework to drive such an interaction.

A Neuroergonomics Approach to Mental Workload, Engagement and Human Performance

The assessment and prediction of cognitive performance is a key issue for any discipline concerned with human operators in the context of safety-critical behavior. Most of the research has focused on the measurement of mental workload but this construct remains difficult to operationalize despite decades of research on the topic. Recent advances in Neuroergonomics have expanded our understanding of neurocognitive processes across different operational domains. We provide a framework to disentangle those neural mechanisms that underpin the relationship between task demand, arousal, mental workload and human performance. This approach advocates targeting those specific mental states that precede a reduction of performance efficacy. A number of undesirable neurocognitive states (mind wandering, effort withdrawal, perseveration, inattentional phenomena) are identified and mapped within a two-dimensional conceptual space encompassing task engagement and arousal. We argue that monitoring the prefrontal cortex and its deactivation can index a generic shift from a nominal operational state to an impaired one where performance is likely to degrade. Neurophysiological, physiological and behavioral markers that specifically account for these states are identified. We then propose a typology of neuroadaptive countermeasures to mitigate these undesirable mental states.

Cortical modulation of pupillary function: systematic review

BACKGROUND

The pupillary light reflex is the main mechanism that regulates the pupillary diameter; it is controlled by the autonomic system and mediated by subcortical pathways. In addition, cognitive and emotional processes influence pupillary function due to input from cortical innervation, but the exact circuits remain poorly understood. We performed a systematic review to evaluate the mechanisms behind pupillary changes associated with cognitive efforts and processing of emotions and to investigate the cerebral areas involved in cortical modulation of the pupillary light reflex.

METHODOLOGY

We searched multiple databases until November 2018 for studies on cortical modulation of pupillary function in humans and non-human primates. Of 8,809 papers screened, 258 studies were included.

RESULTS

Most investigators focused on pupillary dilatation and/or constriction as an index of cognitive and emotional processing, evaluating how changes in pupillary diameter reflect levels of attention and arousal. Only few tried to correlate specific cerebral areas to pupillary changes, using either cortical activation models (employing micro-stimulation of cortical structures in non-human primates) or cortical lesion models (e.g., investigating patients with stroke and damage to salient cortical and/or subcortical areas). Results suggest the involvement of several cortical regions, including the insular cortex (Brodmann areas 13 and 16), the frontal eye field (Brodmann area 8) and the prefrontal cortex (Brodmann areas 11 and 25), and of subcortical structures such as the locus coeruleus and the superior colliculus.

CONCLUSIONS

Pupillary dilatation occurs with many kinds of mental or emotional processes, following sympathetic activation or parasympathetic inhibition. Conversely, pupillary constriction may occur with anticipation of a bright stimulus (even in its absence) and relies on a parasympathetic activation. All these reactions are controlled by subcortical and cortical structures that are directly or indirectly connected to the brainstem pupillary innervation system.