Neural signature of inattentional deafness

The effect of working memory load on inattentional deafness during aeronautical decision-making

Operating an aircraft requires pilots to handle a significant amount of multi-modal information, which creates a high working memory load. Detecting auditory alarms in this high-load scenario is crucial for aviation safety. According to cognitive control load theory, an increase in working memory load may enhance distractor interference, resulting in improved detection sensitivity for task-irrelevant stimuli. Therefore, understanding the effect of working memory load on auditory alarm detection is of particular interest in aviation safety research. The studies were designed to investigate the effect of storage load and executive function load of working memory on auditory alarm detection during aeronautical decision-making through three experiments. In Experiment 1 and 2, participants performed an aeronautical decision-making task while also detecting an auditory alarm during the retention interval of a working memory task (visual-spatial, visual-verbal and auditory-verbal). In Experiment 3, participants were required to detect an auditory alarm while performing the 2-back and 3-back aeronautical decision-making tasks. Experiment 1 found that the auditory alarm sensitivity was higher in conditions of low visual-spatial working memory storage load compare to high load conditions. Experiment 2 found that a high storage load of visual-verbal working memory reduced auditory alarm sensitivity but auditory-verbal working memory load did not. Experiment 3 found that, unlike storage load, auditory alarm sensitivity was stronger under high executive function load relative to low executive function load. These findings show that working memory storage load and executive function load have different effects on auditory alarm sensitivity. The relationship between executive function and auditory alarm sensitivity supports cognitive control load theory, while the impact of the storage function on auditory alarm sensitivity does not adhere to this theory.

Simultaneous fMRI and tDCS for Enhancing Training of Flight Tasks

There is a gap in our understanding of how best to apply transcranial direct-current stimulation (tDCS) to enhance learning in complex, realistic, and multifocus tasks such as aviation. Our goal is to assess the effects of tDCS and feedback training on task performance, brain activity, and connectivity using functional magnetic resonance imaging (fMRI). Experienced glider pilots were recruited to perform a one-day, three-run flight-simulator task involving varying difficulty conditions and a secondary auditory task, mimicking real flight requirements. The stimulation group (versus sham) received 1.5 mA high-definition HD-tDCS to the right dorsolateral prefrontal cortex (DLPFC) for 30 min during the training. Whole-brain fMRI was collected before, during, and after stimulation. Active stimulation improved piloting performance both during and post-training, particularly in novice pilots. The fMRI revealed a number of tDCS-induced effects on brain activation, including an increase in the left cerebellum and bilateral basal ganglia for the most difficult conditions, an increase in DLPFC activation and connectivity to the cerebellum during stimulation, and an inhibition in the secondary task-related auditory cortex and Broca's area. Here, we show that stimulation increases activity and connectivity in flight-related brain areas, particularly in novices, and increases the brain's ability to focus on flying and ignore distractors. These findings can guide applied neurostimulation in real pilot training to enhance skill acquisition and can be applied widely in other complex perceptual-motor real-world tasks.

The role of brain-localized gamma and alpha oscillations in inattentional deafness: implications for understanding human attention

Introduction

The processes involved in how the attention system selectively focuses on perceptual and motor aspects related to a specific task, while suppressing features of other tasks and/or objects in the environment, are of considerable interest for cognitive neuroscience. The goal of this experiment was to investigate neural processes involved in selective attention and performance under multi-task situations. Several studies have suggested that attention-related gamma-band activity facilitates processing in task-specific modalities, while alpha-band activity inhibits processing in non-task-related modalities. However, investigations into the phenomenon of inattentional deafness/blindness (inability to observe stimuli in non-dominant task when primary task is demanding) have yet to observe gamma-band activity.

Methods

This EEG experiment utilizes an engaging whole-body perceptual motor task while carrying out a secondary auditory detection task to investigate neural correlates of inattentional deafness in natural immersive high workload conditions. Differences between hits and misses on the auditory detection task in the gamma (30-50 Hz) and alpha frequency (8-12 Hz) range were carried out at the cortical source level using LORETA.

Results

Participant auditory task performance correlated with an increase in gamma-band activity for hits over misses pre- and post-stimulus in left auditory processing regions. Alpha-band activity was greater for misses relative to hits in right auditory processing regions pre- and post-stimulus onset. These results are consistent with the facilitatory/inhibitory role of gamma/alpha-band activity for neural processing. Additional gamma- and alpha-band activity was found in frontal and parietal brain regions which are thought to reflect various attentional monitoring, selection, and switching processes.

Discussion

The results of this study help to elucidate the role of gamma and alpha frequency bands in frontal and modality-specific regions involved with selective attention in multi-task immersive situations.

Prediction of severity of aviation landing accidents using support vector machine models

The purpose of this study was to apply support vector machine (SVM) models to predict the severity of aircraft damage and the severity of personal injury during an aircraft approach and landing accident and to evaluate and rank the importance of 14 accident factors across 39 sub-categorical factors. Three new factors were introduced using the theory of inattentional blindness: The presence of visual area surface penetrations for a runway, the Federal Aviation Administration's (FAA) visual area surface penetration policy timeframe, and the type of runway approach lighting. The study comprised 1,297 aircraft approach and landing accidents at airports within the United States with at least one instrument approach procedure. Support vector machine models were developed in using the linear, polynomial, radial basis function (RBF), and sigmoid kernels for the severity of aircraft damage and additional SVM models were developed for the severity of personal injury. The SVM models using the RBF kernel produced the best machine learning models with a 96% accuracy for predicting the severity of aircraft damage (0.94 precision, 0.95 recall, and 0.95 F1-score) and a 98% accuracy for predicting the severity of personal injury (0.99 precision, 0.98 recall, and 0.99 F1-score). The top predictors across both models were the pilot's total flight hours, time of the accident, pilot's age, crosswind component, landing runway number, single-engine land certificate, and any obstacle penetration. This study demonstrates the benefit of SVM modeling using the RBF kernel for accident prediction and for datasets with categorical factors.

Classification of Electrophysiological Signatures With Explainable Artificial Intelligence: The Case of Alarm Detection in Flight Simulator

Relevant sounds such as alarms are sometimes involuntarily ignored, a phenomenon called inattentional deafness. This phenomenon occurs under specific conditions including high workload (i.e., multitasking) and/or cognitive fatigue. In the context of aviation, such an error can have drastic consequences on flight safety. This study uses an oddball paradigm in which participants had to detect rare sounds in an ecological context of simulated flight. Cognitive fatigue and cognitive load were manipulated to trigger inattentional deafness, and brain activity was recorded via electroencephalography (EEG). Our results showed that alarm omission and alarm detection can be classified based on time-frequency analysis of brain activity. We reached a maximum accuracy of 76.4% when the algorithm was trained on all participants and a maximum of 90.5%, on one participant, when the algorithm was trained individually. This method can benefit from explainable artificial intelligence to develop efficient and understandable passive brain-computer interfaces, improve flight safety by detecting such attentional failures in real time, and give appropriate feedback to pilots, according to our ambitious goal, providing them with reliable and rich human/machine interactions.

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.

High expectancy influences the role of cognitive load in inattentional deafness during landing decision-making

Neglecting a critical auditory alarm is a major obstacle to maintaining a safe environment, especially in aviation. Earlier studies have indicated that tasks with a higher perceptual or cognitive load in the visual modality influence the processing of auditory stimuli. It is unclear, however, whether other factors, such as memory failure, active neglect, or expectancy influence the effect of cognitive load on auditory alarm detection sensitivity during aeronautical decision-making. In this study, we investigated this issue in three laboratory experiments using the technique of signal detection analysis, in which participants were asked to make a landing decision based on indicators of the instrument landing system while also trying to detect an audible alarm. We found that the sensitivity of auditory alarm detection was reduced under conditions of high cognitive load and that this effect persisted even when the auditory detection response occurred first (before the landing decision response) and when the probability of an auditory alarm was 40%. However, the sensitivity of auditory detection was not influenced by cognitive load under high expectancy conditions (60% probability of alarm presentation). Furthermore, the value of the response bias was reduced under high cognitive load conditions when the probability of an auditory alarm was low (20%). With an increase in the level of expectancy (40% and 60% probability of alarm presentation), it was found that cognitive load did not influence the response bias. These findings indicate that visual cognitive load affects the sensitivity to an auditory alarm only at a low expectancy level (20% and 40% probability of alarm presentation). The effect of cognitive load on the sensitivity to an auditory alarm was not due to memory failure or active neglect and the response bias was more sensitive to the expectancy factor.

Benchmarking cEEGrid and Solid Gel-Based Electrodes to Classify Inattentional Deafness in a Flight Simulator

Transfer from experiments in the laboratory to real-life tasks is challenging due notably to the inability to reproduce the complexity of multitasking dynamic everyday life situations in a standardized lab condition and to the bulkiness and invasiveness of recording systems preventing participants from moving freely and disturbing the environment. In this study, we used a motion flight simulator to induce inattentional deafness to auditory alarms, a cognitive difficulty arising in complex environments. In addition, we assessed the possibility of two low-density EEG systems a solid gel-based electrode Enobio (Neuroelectrics, Barcelona, Spain) and a gel-based cEEGrid (TMSi, Oldenzaal, Netherlands) to record and classify brain activity associated with inattentional deafness (misses vs. hits to odd sounds) with a small pool of expert participants. In addition to inducing inattentional deafness (missing auditory alarms) at much higher rates than with usual lab tasks (34.7% compared to the usual 5%), we observed typical inattentional deafness-related activity in the time domain but also in the frequency and time-frequency domains with both systems. Finally, a classifier based on Riemannian Geometry principles allowed us to obtain more than 70% of single-trial classification accuracy for both mobile EEG, and up to 71.5% for the cEEGrid (TMSi, Oldenzaal, Netherlands). These results open promising avenues toward detecting cognitive failures in real-life situations, such as real flight.

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.

Cerebellum, Basal Ganglia, and Cortex Mediate Performance of an Aerial Pursuit Task

The affordance competition hypothesis is an ethologically inspired theory from cognitive neuroscience that provides an integrative neural account of continuous, real-time behavior, and will likely become increasingly relevant to the growing field of neuroergonomics. In the spirit of neuroergonomics in aviation, we designed a three-dimensional, first-person, continuous, and real-time fMRI task during which human subjects maneuvered a simulated airplane in pursuit of a target airplane along constantly changing headings. We introduce a pseudo-event-related, parametric fMRI analysis approach to begin testing the affordance competition hypothesis in neuroergonomic contexts, and attempt to identify regions of the brain that exhibit a linear metabolic relationship with the continuous variables of task performance and distance-from-target. In line with the affordance competition hypothesis, our results implicate the cooperation of the cerebellum, basal ganglia, and cortex in such a task, with greater involvement of the basal ganglia during good performance, and greater involvement of cortex and cerebellum during poor performance and when distance-from-target closes. We briefly review the somatic marker and dysmetria of thought hypotheses, in addition to the affordance competition hypothesis, to speculate on the intricacies of the cooperation of these brain regions in a task such as ours. In doing so, we demonstrate how the affordance competition hypothesis and other cognitive neuroscience theories are ready for testing in continuous, real-time tasks such as ours, and in other neuroergonomic settings more generally.

Altered Default Mode Network Dynamics in Civil Aviation Pilots

Background

Airlines occupy an increasingly important place in the economy of many countries. Because air disasters may cause substantial losses, comprehensive surveys of the psychophysiological mechanism of flying are needed; however, relatively few studies have focused on pilots. The default mode network (DMN) is an important intrinsic connectivity network involved in a range of functions related to flying. This study aimed to examine functional properties of the DMN in pilots.

Method

Resting-state functional magnetic resonance imaging data from 26 pilots and 24 controls were collected. Independent component analysis, a data-driven approach, was combined with functional connectivity analysis to investigate functional properties of the DMN in pilots.

Results

The pilot group exhibited increased functional integration in the precuneus/posterior cingulate cortex (PCC) and left middle occipital gyrus. Subsequent functional connectivity analysis identified enhanced functional connection between the precuneus/PCC and medial superior frontal gyrus.

Conclusion

The pilot group exhibited increased functional connections within the DMN. These findings highlight the importance of the DMN in the neurophysiological mechanism of flying.

Monitoring Pilot's Mental Workload Using ERPs and Spectral Power with a Six-Dry-Electrode EEG System in Real Flight Conditions

Recent technological progress has allowed the development of low-cost and highly portable brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the laboratory. This technology opens promising perspectives to monitor the "brain at work" in complex real-life situations such as while operating aircraft. However, there is a need to benchmark these sensors in real operational conditions. We therefore designed a scenario in which twenty-two pilots equipped with a six-dry-electrode EEG system had to perform one low load and one high load traffic pattern along with a passive auditory oddball. In the low load condition, the participants were monitoring the flight handled by a flight instructor, whereas they were flying the aircraft in the high load condition. At the group level, statistical analyses disclosed higher P300 amplitude for the auditory target (Pz, P4 and Oz electrodes) along with higher alpha band power (Pz electrode), and higher theta band power (Oz electrode) in the low load condition as compared to the high load one. Single trial classification accuracy using both event-related potentials and event-related frequency features at the same time did not exceed chance level to discriminate the two load conditions. However, when considering only the frequency features computed over the continuous signal, classification accuracy reached around 70% on average. This study demonstrates the potential of dry-EEG to monitor cognition in a highly ecological and noisy environment, but also reveals that hardware improvement is still needed before it can be used for everyday flight operations.

Inattentional deafness to auditory alarms: Inter-individual differences, electrophysiological signature and single trial classification

Inattentional deafness can have deleterious consequences in complex real-life situations (e.g. healthcare, aviation) leading to miss critical auditory signals. Such failure of auditory attention is thought to rely on top-down biasing mechanisms at the central executive level. A complementary approach to account for this phenomenon is to consider the existence of visual dominance over hearing that could be implemented via direct visual-to-auditory pathways. To investigate this phenomenon, thirteen aircraft pilots, equipped with a 32-channel EEG system, faced a low and high workload scenarii along with an auditory oddball task in a motion flight simulator. Prior to the flying task, the pilots were screened to assess their working memory span and visual dominance susceptibility. The behavioral results disclosed that the volunteers missed 57.7% of the auditory alarms in the difficult condition. Among all evaluated capabilities, only the visual dominance index was predictive of the miss rate in the difficult scenario. These findings provide behavioral evidences that other early cross-modal competitive process than top down modulation process could account for inattentional deafness. The electrophysiological analyses showed that the miss over the hit alarms led to a significant amplitude reduction of early perceptual (N100) and late attentional (P3a and P3b) event-related potentials components. Eventually, we implemented an EEG-based processing pipeline to perform single-trial classification of inattentional deafness. The results indicate that this processing chain could be used in an ecological setting as it led to 72.2% mean accuracy to discriminate missed from hit auditory alarms.

Disruption in neural phase synchrony is related to identification of inattentional deafness in real-world setting

Individuals often have reduced ability to hear alarms in real world situations (e.g., anesthesia monitoring, flying airplanes) when attention is focused on another task, sometimes with devastating consequences. This phenomenon is called inattentional deafness and usually occurs under critical high workload conditions. It is difficult to simulate the critical nature of these tasks in the laboratory. In this study, dry electroencephalography is used to investigate inattentional deafness in real flight while piloting an airplane. The pilots participating in the experiment responded to audio alarms while experiencing critical high workload situations. It was found that missed relative to detected alarms were marked by reduced stimulus evoked phase synchrony in theta and alpha frequencies (6-14 Hz) from 120 to 230 ms poststimulus onset. Correlation of alarm detection performance with intertrial coherence measures of neural phase synchrony showed different frequency and time ranges for detected and missed alarms. These results are consistent with selective attentional processes actively disrupting oscillatory coherence in sensory networks not involved with the primary task (piloting in this case) under critical high load conditions. This hypothesis is corroborated by analyses of flight parameters showing greater maneuvering associated with difficult phases of flight occurring during missed alarms. Our results suggest modulation of neural oscillation is a general mechanism of attention utilizing enhancement of phase synchrony to sharpen alarm perception during successful divided attention, and disruption of phase synchrony in brain networks when attentional demands of the primary task are great, such as in the case of inattentional deafness.