Electromagnetic data collected using electroencephalography (EEG) and magnetoencephalography (MEG) are of central importance for psychophysiological research. The scope of concepts, methods, and instruments used by EEG/MEG researchers has dramatically increased and is expected to further increase in the future. Building on existing guideline publications, the goal of the present paper is to contribute to the effective documentation and communication of such advances by providing updated guidelines for conducting and reporting EEG/MEG studies. The guidelines also include a checklist of key information recommended for inclusion in research reports on EEG/MEG measures.

https://csea.phhp.ufl.edu/Publications/Keil_CommitteeReport_2014.pdf

Committee report: Publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography

study objectives : The goal of the study was to seek physiological correlates of lucid dreaming. Lucid dreaming is a dissociated state with aspects of waking and dreaming combined in a way so as to suggest a specific alteration in brain physiology for which we now present pre liminary but intriguing evidence. We show that the unusual combination of hallucinatory dream activity and wake-like reflective awareness and agentive control experienced in lucid dreams is paralleled by significant changes in electrophysiology. design : 19-channel EEG was recorded on up to 5 nights for each participant. Lucid episodes occurred as a result of pre-sleep autosuggestion. setting : Sleep laboratory of the Neurological Clinic, Frankfurt University. Participants : Six student volunteers who had been trained to become lucid and to signal lucidity through a pattern of horizontal eye movements. Measurements and results : Results show lucid dreaming to have REMlike power in frequency bands δ and θ, and higher-than-REM activity in the γ band, the between-states-difference peaking around 40 Hz. Power in the 40 Hz band is strongest in the frontal and frontolateral region. Overall coherence levels are similar in waking and lucid dreaming and significantly higher than in REM sleep, throughout the entire frequency spectrum analyzed. Regarding specific frequency bands, waking is characterized by high coherence in α, and lucid dreaming by increased δ and θ band coherence. In lucid dreaming, coherence is largest in frontolateral and frontal areas. conclusions : Our data show that lucid dreaming constitutes a hybrid state of consciousness with definable and measurable differences from waking and from REM sleep, particularly in frontal areas.

/pdf/lucid-dreaming-a-state-of-consciousness-with-features-of-2fv9et8xc2.pdf

Lucid dreaming: a state of consciousness with features of both waking and non-lucid dreaming.

Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under- and overload conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the AA solutions without affecting the operative task. In this regard, passive Brain-Computer Interface (pBCI) systems are a good candidate to activate automation, since they are able to gather information about the covert behaviour (e.g. mental workload) of a subject by analysing its neurophysiological signals (i.e. brain activity), and without interfering with the ongoing operational activity. We proposed a pBCI system able to trigger AA solutions integrated in a realistic Air Traffic Management (ATM) research simulator developed and hosted at ENAC (Ecole Nationale de l’Aviation Civile of Toulouse, France). Twelve Air Traffic Controller (ATCO) students have been involved in the experiment and they have been asked to perform ATM scenarios with and without the support of the AA solutions. Results demonstrated the effectiveness of the proposed pBCI system, since it enabled the AA mostly during the high-demanding conditions (i.e. overload situations) inducing a reduction of the mental workload under which the ATCOs were operating. On the contrary, as desired, the AA was not activated when workload level was under the threshold, to prevent too low demanding conditions that could bring the operator’s workload level towards potentially dangerous conditions of underload.

/pdf/adaptive-automation-triggered-by-eeg-based-mental-workload-3hkepm82h5.pdf

Adaptive Automation Triggered by EEG-Based Mental Workload Index: A Passive Brain-Computer Interface Application in Realistic Air Traffic Control Environment.

Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.

/pdf/brain-computer-interface-based-adaptive-automation-to-42aopz7iwa.pdf

Brain–Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems

In the present study the frontal and parietal P300, elicited in an auditory oddball paradigm were investigated in a large sample of healthy participants (N = 1572), aged 6–87. According to the concepts of the compensation-related utilization of neural circuits hypothesis (CRUNCH) it was hypothesized that the developmental trajectories of the frontal P300 would reach a maximum in amplitude at an older age than the amplitude of the parietal P300 amplitude. In addition, the amplitude of the frontal P300 was expected to increase with aging in adulthood in contrast to a decline in amplitude of the parietal P300 amplitude. Using curve-fitting methods, a comparison was made between the developmental trajectories of the amplitudes of the frontal and parietal P300. It was found that the developmental trajectories of frontal and parietal P300 amplitudes differed significantly across the lifespan. During adulthood, the amplitude of the parietal P300 declines with age, whereas both the frontal P300 amplitude and behavioral performance remain unaffected. A lifespan trajectory of combined frontal and parietal P300 amplitudes was found to closely resemble the lifespan trajectory of behavioral performance. Our results can be understood within the concepts of CRUNCH. That is, to compensate for declining neural resources, older participants recruit additional neural resources of prefrontal origin and consequently preserve a stable behavioral performance. Though, a direct relation between amplitude of the frontal P300 and compensatory mechanisms cannot yet be claimed.

/pdf/combined-frontal-and-parietal-p300-amplitudes-indicate-1odbbn0ua0.pdf

Combined frontal and parietal P300 amplitudes indicate compensated cognitive processing across the lifespan

Virtual reality (VR) is an evolving technology being adopted by manufacturing in areas (such as operator training, and the virtual testing of new products before manufacture), where it is now becoming a widely accepted industrial tool. Of particular note are applications in off-line programming of robots. However, before this concept finds acceptance in industry, countless problems need to be resolved. Several problems are addressed within this paper, including the requirement of an acceptable interaction device, and the subject of haptic and tactile feedback. As manufacturing continually moves to become a more responsive environment, with products having shorter life cycles and batch quantities reducing in size, robot programming times become critical, and hence an area to be addressed in order to seek improved productivity. Off-line programming is one approach, where for example off-line programming within a virtual environment could reduce the required skill levels of a programmer, reduce the programming times, allow the operator a `natural' interface with which the operator would conduct the task in the real world, and reduce the boredom factor. This paper discusses the development of a new approach or method for the off-line programming of robotic devices, indicating some of the potential applications, and highlighting some of the restricting limitations that need to be overcome. The paper also includes a review of previous published work on the off-line programming of robots using VR.

S.J. Steiner

Papers

A new method for off-line robot programming: applications and limitations using a virtual environment