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

A Neuroergonomics Approach to Human Performance in Aviation

A Neuroergonomics Approach to Human Performance in Aviatio

Monitoring pilot’s cognitive fatigue with engagement features in simulated and actual flight conditions using an hybrid fNIRS-EEG passive BCI

There is growing interest for implementing tools to monitor cognitive performance in naturalistic environments. Recent technological progress has allowed the development of new generations of brain imaging systems such as dry electrodes electroencephalography (EEG) and functional near infrared spec- troscopy (fNIRS) to investigate cortical activity in a variety of human tasks out of the laboratory. These highly portable brain imaging devices offer interesting prospects to implement passive brain computer interfaces (pBCI) and neuroadaptive technology. We developed a fNIRS-EEG based pBCI to monitor cognitive fatigue using engagement related features (EEG engagement ratio and wavelet coherence fNIRS based metrics). This mental state is known to impair cognitive performance and can jeopardize flight safety. In this preliminary study, four participants were asked to perform four identical traffic patterns along with a secondary auditory task in a flight simulator and in an actual light aircraft. The two first traffic patterns were considered as the low cognitive fatigue class, whereas the two last traffic patterns were considered as the high cognitive fatigue class. As expected, the pilots missed more auditory targets in the second part than in the first part of the experiment. Classification accuracy reached 87.2% in the flight simulator condition and 87.6% in the actual flight conditions when combining the two modalities. This study demonstrates that fNIRS and EEG-based pBCIs can monitor mental states in operational and noisy environments

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Cognitive Decay And Memory Recall During Long Duration Spaceflight

This dissertation aims to advance the efficacy of Long-Duration Space Flight (LDSF) pre-flight and in-flight training programs, acknowledging existing knowledge gaps in NASA\u27s methodologies. The research\u27s objective is to optimize the cognitive workload of LDSF crew members, enhance their neurocognitive functionality, and provide more meaningful work experiences, particularly for Mars missions.The study addresses identified shortcomings in current training and learning strategies and simulation-based training systems, focusing on areas requiring quantitative measures for astronaut proficiency and training effectiveness assessment. The project centers on understanding cognitive decay and memory loss under LDSF-related stressors, seeking to establish when such cognitive decline exceeds acceptable performance levels throughout mission phases. The research acknowledges the limitations of creating a near-orbit environment due to resource constraints and the need to develop engaging tasks for test subjects. Nevertheless, it underscores the potential impact on future space mission training and other high-risk professions. The study further explores astronaut training complexities, the challenges encountered in LDSF missions, and the cognitive processes involved in such demanding environments. The research employs various cognitive and memory testing events, integrating neuroimaging techniques to understand cognition\u27s neural mechanisms and memory. It also explores Rasmussen\u27s S-R-K behaviors and Brain Network Theory’s (BNT) potential for measuring forgetting, cognition, and predicting training needs. The multidisciplinary approach of the study reinforces the importance of integrating insights from cognitive psychology, behavior analysis, and brain connectivity research. Research experiments were conducted at the University of North Dakota\u27s Integrated Lunar Mars Analog Habitat (ILMAH), gathering data from selected subjects via cognitive neuroscience tools and Electroencephalography (EEG) recordings to evaluate neurocognitive performance. The data analysis aimed to assess brain network activations during mentally demanding activities and compare EEG power spectra across various frequencies, latencies, and scalp locations. Despite facing certain challenges, including inadequacies of the current adapter boards leading to analysis failure, the study provides crucial lessons for future research endeavors. It highlights the need for swift adaptation, continual process refinement, and innovative solutions, like the redesign of adapter boards for high radio frequency noise environments, for the collection of high-quality EEG data. In conclusion, while the research did not reveal statistically significant differences between the experimental and control groups, it furnished valuable insights and underscored the need to optimize astronaut performance, well-being, and mission success. The study contributes to the ongoing evolution of training methodologies, with implications for future space exploration endeavors

Applications of Optical Brain Imaging Methods in Aviation Neuroergonomics

Pilotların, insansız hava aracı operatörlerinin, hava trafik kontrolörlerinin eğitim ve uçuş faaliyetleri sırasında bilişsel durumlarının takibini sağlayacak nesnel yöntemlerin geliştirilmesi uçuş emniyetinin sağlanması, eğitim süreçlerinin optimizasyonu ve yenilikçi insan-makine arayüzlerinin tasarımı bakımından kritik önem taşımaktadır. İşlevsel Yakın-Kızılötesi Tayfölçümü (functional near infrared spectroscopy – fNIRS) optik beyin görüntüleme teknolojisi gibi saha kullanımına uygun, portatif ve güvenilir nörofizyolojik ölçüm yöntemleri bu ihtiyaçlara yönelik bazı önemli avantajlar sunmaktadır. Bu derlemede fNIRS teknolojisinin dayandığı bilimsel temeller ve bu teknolojiyle gerçekleştirilmiş pilot/operatör bilişsel işyükü takibi, kontrol arayüzü değerlendirmesi, G-LoC/hipoksi kestirimi gibi öncü havacılık uygulamalarından örnekler sunularak fNIRS yönteminin havacılık tıbbı ve ergonomisi alanları için sunduğu imkanların özetlenmesi amaçlanmıştır.The development of objective methods that enable monitoring of the cognitive status of pilots, unmanned aerial vehicle operators, and air traffic controllers is critically important in aviation for improving flight safety, optimizing pilot/operator training and developing innovative man-machine interfaces. Functional near-infrared spectroscopy (fNIRS) optical brain imaging technology offers significant advantages for this purpose by providing portable, rugged sensors that can be employed in the field to monitor neurophysiological markers during flight operations. This article reviews studies that employ fNIRS technology for cognitive workload assessment, operator interface evaluation, and G-LoC/hypoxia prediction in aviation to document the potential of neurophysiological measurement modalities like fNIRS for aviation medicine and ergonomics

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 211, October 1980

This bibliography lists 212 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1980

Aerospace Medicine and Biology: A cumulative index to the 1982 issues

This publication is a cumulative index to the abstracts contained in the Supplements 229 through 240 of Aerospace Medicine and Biology: A continuing Bibliography. It includes three indexes: subject, personal author, and corporate source

Impact of Fatigue on Corticomuscular Coupling and EEG Microstates during Human-Robot Interaction and Physical Exercise

Human movements are controlled by the Central Nervous System. Motor dysfunction and sensory-motor deficits result in restricted use of the upper extremities in stroke patients, leading to difficulty in carrying out daily activities. Human-robot interaction (HRI) in rehabilitation can provide individualised, task oriented therapy to patients for fast recovery. The key goals of rehabilitation strategies are to enhance the functional ability and cognitive performance of stroke patients in an optimised way. Therapy can often benefit from assessing progress. Nine Hole Peg Test (NHPT) is one of the widely used tests for assessing upper extremity impairment whose only outcome measure is the time for completion of the task. Coordination between EEG and EMG signals plays a vital role in movement control. EEGEMG coherence is considered capable of measuring the control of spinal motor neurons by the cerebral cortex. It helps to understand how the brain controls muscle movement and also the effects of muscle movement on brain function hence can give more insight into fatigue. EEG microstates are recurrent scalp potential configurations that remain stable for a short period of time. The analysis of EEG microstates can help to identify the background neuronal activity at the millisecond level. Analysing EEG-EMG coherence and EEG microstates on a person performing NHPT under fatigue conditions will help us to have a better understanding of underlying neuronal activities. To explore these an experiment was conducted with 8 healthy participants while interacting with a robot-assisted NHPT. The experiment involved two trials of NHPT, then a fatiguing exercise which was then followed by two more trials of NHPT. EEG-EMG coherence was examined for pre fatigue and post fatigue trials of NHPT. EEG microstates analysis was conducted for resting state conditions, NHPT trial, and also during physical exercise. The analysis of EEG-EMG coherence showed an increase in corticomuscular coupling with fatigue. The increased EEG-EMG coherence suggests that the functional coupling between the brain and muscles becomes stronger with fatigue. Three distinct microstates were observed for the different physical states of participants. Changes were assessed by utilising microstate parameters such as occurrence, coverage, duration, and global explained variance. It was found that the coverage of some microstates is impacted by fatigue in all the experimental stages used for analysis. These results support the involvement of different neural assemblies but also highlight the potential that physical fatigue can be observed and identified by assessing changes in microstate parameters