Investigating the relationship between resting-state EEG microstates and executive functions: A null finding.

Recent advances in cognitive neurosciences suggest that intrinsic brain networks dynamics are associated with cognitive functioning. Despite this emerging perspective, limited research exists to validate this hypothesis. This Registered Report aimed to specifically test the relationship between intrinsic brain spatio-temporal dynamics and executive functions. Resting-state EEG microstates were used to assess brain spatio-temporal dynamics, while a comprehensive battery of nine cognitive function tasks was employed to evaluate executive functions in 140 participants. We hypothesized that microstates (class C and D) metrics would correlate with an executive functions composite score. Contrary to expectations, our hypotheses were not supported by the data. We however observed a small, non-significant trend with a negative correlation between microstate D occurrences and executive functions scores (r = -.18, 95% CI [-.33, -.01]) which however did not meet the adjusted threshold for significance. In light of the inconclusive or minor effect sizes observed, the assertion that intrinsic brain networks dynamics - as measured by resting-state EEG microstate metrics - are a reliable signature of executive functioning remains unsupported.

Cocktail party training induces increased speech intelligibility and decreased cortical activity in bilateral inferior frontal gyri. A functional near-infrared study.

The human brain networks responsible for selectively listening to a voice amid other talkers remain to be clarified. The present study aimed to investigate relationships between cortical activity and performance in a speech-in-speech task, before (Experiment I) and after training-induced improvements (Experiment II). In Experiment I, 74 participants performed a speech-in-speech task while their cortical activity was measured using a functional near infrared spectroscopy (fNIRS) device. One target talker and one masker talker were simultaneously presented at three different target-to-masker ratios (TMRs): adverse, intermediate and favorable. Behavioral results show that performance may increase monotonically with TMR in some participants and failed to decrease, or even improved, in the adverse-TMR condition for others. On the neural level, an extensive brain network including the frontal (left prefrontal cortex, right dorsolateral prefrontal cortex and bilateral inferior frontal gyri) and temporal (bilateral auditory cortex) regions was more solicited by the intermediate condition than the two others. Additionally, bilateral frontal gyri and left auditory cortex activities were found to be positively correlated with behavioral performance in the adverse-TMR condition. In Experiment II, 27 participants, whose performance was the poorest in the adverse-TMR condition of Experiment I, were trained to improve performance in that condition. Results show significant performance improvements along with decreased activity in bilateral inferior frontal gyri, the right dorsolateral prefrontal cortex, the left inferior parietal cortex and the right auditory cortex in the adverse-TMR condition after training. Arguably, lower neural activity reflects higher efficiency in processing masker inhibition after speech-in-speech training. As speech-in-noise tasks also imply frontal and temporal regions, we suggest that regardless of the type of masking (speech or noise) the complexity of the task will prompt the implication of a similar brain network. Furthermore, the initial significant cognitive recruitment will be reduced following a training leading to an economy of cognitive resources.

Performance after training in a complex cognitive task is enhanced by high-definition transcranial random noise stimulation.

Interest for neuromodulation, and transcranial random noise stimulation (tRNS) in particular, is growing. It concerns patients rehabilitation, but also healthy people who want or need to improve their cognitive and learning abilities. However, there is no consensus yet regarding the efficacy of tRNS on learning and performing a complex task. In particular, the most effective electrode montage is yet to be determined. Here, we examined the effect of two different tRNS montages on learning rate, short- and long-term performance in a video game (Space Fortress) that engages multiple cognitive abilities. Sixty-one participants were randomly assigned to one of three groups (sham vs. simple-definition tRNS vs. high-definition tRNS) in a double-blind protocol. Their performance on the Space Fortress task was monitored during a 15-day experiment with baseline (day 1), stimulation (day 2 to 4), short- (day 5) and long-term (day 15) evaluations. Our results show that the high-definition tRNS group improved more on the long term than simple-definition tRNS group, tended to learn faster and had better performance retention compared to both simple-definition tRNS and sham groups. This study is the first to report that high-definition tRNS is more effective than conventional simple-definition tRNS to enhance performance in a complex task.

Functional Connectivity Within the Fronto-Parietal Network Predicts Complex Task Performance: A fNIRS Study.

Performance in complex tasks is essential for many high risk operators. The achievement of such tasks is supported by high-level cognitive functions arguably involving functional activity and connectivity in a large ensemble of brain areas that form the fronto-parietal network. Here we aimed at determining whether the functional connectivity at rest within this network could predict performance in a complex task: the Space Fortress video game. Functional Near Infrared Spectroscopy (fNIRS) data from 32 participants were recorded during a Resting-State period, the completion of a simple version of Space Fortress (monotask) and the original version (multitask). The intrinsic functional connectivity within the fronto-parietal network (i.e., during the Resting-State) was a significant predictor of performance at Space Fortress multitask but not at its monotask version. The same pattern was observed for the functional connectivity during the task. Our overall results suggest that Resting-State functional connectivity within the fronto-parietal network could be used as an intrinsic brain marker for performance prediction of a complex task achievement, but not for simple task performance.

Global difficulty modulates the prioritization strategy in multitasking situations.

There has been a considerable amount of research to conceptualize how cognition handle multitasking situations. Despite these efforts, it is still not clear how task parameters shape attentionnal resources allocation. For instance, many research have suggested that difficulty levels could explain these conflicting observations and very few have considered other factors such as task importance. In the present study, twenty participants had to carry out two N-Back tasks simultaneously, each subtask having distinct difficulty (0,1 or 2-Back) and importance (1 or 3 points) levels. Participants's cumulative dwell time were collected to assess their attentional strategies. Results showed that depending on the global level of difficulty (combination of the two levels of difficulty), attentional resources of people were driven either by the subtask difficulty (under low-global-difficulty) or the subtask importance (under high-global-difficulty), in a non-compensatory way. We discussed these results in terms of decision-making heuristics and metacognition.

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.

Assessment of Ocular and Physiological Metrics to Discriminate Flight Phases in Real Light Aircraft.

OBJECTIVE: The purpose of the present study was to find psychophysiological proxies that are straightforward to use and could be implemented in actual flight conditions to accurately discriminate pilots' workload levels. BACKGROUND: Piloting an aircraft is a complex activity where cognitive limitations may jeopardize flight safety. There is a need to implement solutions to monitor pilots' workload level to improve flight safety. There has been recent interest in combining psychophysiological measurements. Most of these studies were conducted in flight simulators at the group level, limiting the interpretation of the results. METHODS: We conducted an experiment with 11 pilots performing two standard traffic patterns in a light aircraft. Five metrics were derived from their ocular and cardiac activities and were evaluated through three flight phases: takeoff, downwind, and landing. RESULTS: Statistical analyses showed that the saccadic rate was the most efficient metric to distinguish between the three flight phases. In addition, a classifier trained on the ocular data collected from the first run predicted the flight phase within a second run with an accuracy of 75%. No gain in the classifier accuracy has been found by combining cardiac and ocular metrics. CONCLUSIONS: Ocular-based metrics may be more suitable than cardiac ones to provide relevant information on pilots' flying activity in operational settings. APPLICATIONS: Electrocardiographic and eye-tracking devices could be implemented in future cockpits as additional flight data for accident analysis, an objective pilot's state evaluation for training, and proxies for human-machine interactions to improve flight safety.

Can an aircraft be piloted via sonification with an acceptable attentional cost? A comparison of blind and sighted pilots.

In the aeronautics field, some authors have suggested that an aircraft's attitude sonification could be used by pilots to cope with spatial disorientation situations. Such a system is currently used by blind pilots to control the attitude of their aircraft. However, given the suspected higher auditory attentional capacities of blind people, the possibility for sighted individuals to use this system remains an open question. For example, its introduction may overload the auditory channel, which may in turn alter the responsiveness of pilots to infrequent but critical auditory warnings. In this study, two groups of pilots (blind versus sighted) performed a simulated flight experiment consisting of successive aircraft maneuvers, on the sole basis of an aircraft sonification. Maneuver difficulty was varied while we assessed flight performance along with subjective and electroencephalographic (EEG) measures of workload. The results showed that both groups of participants reached target-attitudes with a good accuracy. However, more complex maneuvers increased subjective workload and impaired brain responsiveness toward unexpected auditory stimuli as demonstrated by lower N1 and P3 amplitudes. Despite that the EEG signal showed a clear reorganization of the brain in the blind participants (higher alpha power), the brain responsiveness to unexpected auditory stimuli was not significantly different between the two groups. The results suggest that an auditory display might provide useful additional information to spatially disoriented pilots with normal vision. However, its use should be restricted to critical situations and simple recovery or guidance maneuvers.

The Spatial Release of Cognitive Load in Cocktail Party Is Determined by the Relative Levels of the Talkers.

In a multi-talker situation, spatial separation between talkers reduces cognitive processing load: this is the "spatial release of cognitive load". The present study investigated the role played by the relative levels of the talkers on this spatial release of cognitive load. During the experiment, participants had to report the speech emitted by a target talker in the presence of a concurrent masker talker. The spatial separation (0° and 120° angular distance in azimuth) and the relative levels of the talkers (adverse, intermediate, and favorable target-to-masker ratio) were manipulated. The cognitive load was assessed with a prefrontal functional near-infrared spectroscopy. Data from 14 young normal-hearing listeners revealed that the target-to-masker ratio had a direct impact on the spatial release of cognitive load. Spatial separation significantly reduced the prefrontal activity only for the intermediate target-to-masker ratio and had no effect on prefrontal activity for the favorable and the adverse target-to-masker ratios. Therefore, the relative levels of the talkers might be a key point to determine the spatial release of cognitive load and more specifically the prefrontal activity induced by spatial cues in multi-talker situations.

N270 sensitivity to conflict strength and working memory: A combined ERP and sLORETA study.

The event-related potential N270 component is known to be an electrophysiological marker of the supramodal conflict processing. However little is know about the factors that may modulate its amplitude. In particular, among all studies that have investigated the N270, little or no control of the conflict strength and of the load in working memory have been done leaving a lack in the understanding of this component. We designed a spatial audiovisual conflict task with simultaneous target and cross-modal distractor to evaluate the N270 sensitivity to the conflict strength (i.e., visual target with auditory distractor or auditory target with visual distractor) and the load in working memory (goal task maintenance with frequent change in the target modality). In a first session, participants had to focus on one modality for the target position to be considered (left-hand or right-hand) while the distractor could be at the same side (compatible) or at opposite side (incompatible). In a second session, we used the same set of stimuli as in the first session with an additional distinct auditory signal that clued the participants to frequently switch between the auditory and the visual targets. We found that (1) reaction times and N270 amplitudes for conflicting situations were larger within the auditory target condition compared to the visual one, (2) the increase in target maintenance effort led to equivalent increase of both reaction times and N270 amplitudes within all conditions and (3) the right dorsolateral prefrontal cortex current density was higher for both conflicting and active maintenance of the target situations. These results provide new evidence that the N270 component is an electrophysiological marker of the supramodal conflict processing that is sensitive to the conflict strength and that conflict processing and active maintenance of the task goal are two functions of a common executive attention system.

Frequency analysis of a task-evoked pupillary response: Luminance-independent measure of mental effort.

Pupil diameter is a widely-studied cognitive load measure, which, despite its convenience for non-intrusive operator state monitoring in complex environments, is still not available for in situ measurements because of numerous methodological limitations. The most important of these limitations is the influence of pupillary light reflex. Hence, there is the need of providing a pupil-based cognitive load measure that is independent of light conditions. In this paper, we present a promising technique of pupillary signal analysis resulting in luminance-independent measure of mental effort that could be used in real-time without a priori on luminous conditions. Twenty-two participants performed a short-term memory task under different screen luminance conditions. Our results showed that the amplitude of pupillary dilation due to load on memory was luminance-dependent with higher amplitude corresponding to lower-luminance condition. Furthermore, our experimentation showed that load on memory and luminance factors express themselves differently according to frequency. Therefore, as our statistical analysis revealed, the ratio between low (0-1.6 Hz) and high frequency (1.6-4 Hz) bands (LF/HF ratio) of power spectral densities of pupillary signal is sensitive to the cognitive load but not to luminance. Our results are promising for the measurement of load on memory in ecological settings.

Real-time state estimation in a flight simulator using fNIRS.

Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot's instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot's mental state matched significantly better than chance with the pilot's real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development.

P300 event-related potential as an indicator of inattentional deafness?

An analysis of airplane accidents reveals that pilots sometimes purely fail to react to critical auditory alerts. This inability of an auditory stimulus to reach consciousness has been coined under the term of inattentional deafness. Recent data from literature tends to show that tasks involving high cognitive load consume most of the attentional capacities, leaving little or none remaining for processing any unexpected information. In addition, there is a growing body of evidence for a shared attentional capacity between vision and hearing. In this context, the abundant information in modern cockpits is likely to produce inattentional deafness. We investigated this hypothesis by combining electroencephalographic (EEG) measurements with an ecological aviation task performed under contextual variation of the cognitive load (high or low), including an alarm detection task. Two different audio tones were played: standard tones and deviant tones. Participants were instructed to ignore standard tones and to report deviant tones using a response pad. More than 31% of the deviant tones were not detected in the high load condition. Analysis of the EEG measurements showed a drastic diminution of the auditory P300 amplitude concomitant with this behavioral effect, whereas the N100 component was not affected. We suggest that these behavioral and electrophysiological results provide new insights on explaining the trend of pilots' failure to react to critical auditory information. Relevant applications concern prevention of alarms omission, mental workload measurements and enhanced warning designs.

Processing Functional Near Infrared Spectroscopy Signal with a Kalman Filter to Assess Working Memory during Simulated Flight.

Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI.

Moving Average Convergence Divergence filter preprocessing for real-time event-related peak activity onset detection : application to fNIRS signals.

Real-time solutions for noise reduction and signal processing represent a central challenge for the development of Brain Computer Interfaces (BCI). In this paper, we introduce the Moving Average Convergence Divergence (MACD) filter, a tunable digital passband filter for online noise reduction and onset detection without preliminary learning phase, used in economic markets analysis. MACD performance was tested and benchmarked with other filters using data collected with functional Near Infrared Spectoscopy (fNIRS) during a digit sequence memorization task. This filter has a good performance on filtering and real-time peak activity onset detection, compared to other techniques. Therefore, MACD could be implemented for efficient BCI design using fNIRS.

Effects of the audiovisual conflict on auditory early processes.

Auditory alarm misperception is one of the critical events that lead aircraft pilots to an erroneous flying decision. The rarity of these alarms associated with their possible unreliability may play a role in this misperception. In order to investigate this hypothesis, we manipulated both audiovisual conflict and sound rarity in a simplified landing task. Behavioral data and event related potentials (ERPs) of thirteen healthy participants were analyzed. We found that the presentation of a rare auditory signal (i.e., an alarm), incongruent with visual information, led to a smaller amplitude of the auditory N100 (i.e., less negative) compared to the condition in which both signals were congruent. Moreover, the incongruity between the visual information and the rare sound did not significantly affect reaction times, suggesting that the rare sound was neglected. We propose that the lower N100 amplitude reflects an early visual-to-auditory gating that depends on the rarity of the sound. In complex aircraft environments, this early effect might be partly responsible for auditory alarm insensitivity. Our results provide a new basis for future aeronautic studies and the development of countermeasures.