Vsevolod Peysakhovich

Attribute-driven edge bundling for general graphs with applications in trail analysis

Edge bundling methods reduce visual clutter of dense and occluded graphs. However, existing bundling techniques either ignore edge properties such as direction and data attributes, or are otherwise computationally not scalable, which makes them unsuitable for tasks such as exploration of large trajectory datasets. We present a new framework to generate bundled graph layouts according to any numerical edge attributes such as directions, timestamps or weights. We propose a GPU-based implementation linear in number of edges, which makes our algorithm applicable to large datasets. We demonstrate our method with applications in the analysis of aircraft trajectory datasets and eye-movement traces.

Neural and psychophysiological correlates of human performance under stress and high mental workload.

In our anxiogenic and stressful world, the maintenance of an optimal cognitive performance is a constant challenge. It is particularly true in complex working environments (e.g. flight deck, air traffic control tower), where individuals have sometimes to cope with a high mental workload and stressful situations. Several models (i.e. processing efficiency theory, cognitive-energetical framework) have attempted to provide a conceptual basis on how human performance is modulated by high workload and stress/anxiety. These models predict that stress can reduce human cognitive efficiency, even in the absence of a visible impact on the task performance. Performance may be protected under stress thanks to compensatory effort, but only at the expense of a cognitive cost. Yet, the psychophysiological cost of this regulation remains unclear. We designed two experiments involving pupil diameter, cardiovascular and prefrontal oxygenation measurements. Participants performed the Toulouse N-back Task that intensively engaged both working memory and mental calculation processes under the threat (or not) of unpredictable aversive sounds. The results revealed that higher task difficulty (higher n level) degraded the performance and induced an increased tonic pupil diameter, heart rate and activity in the lateral prefrontal cortex, and a decreased phasic pupil response and heart rate variability. Importantly, the condition of stress did not impact the performance, but at the expense of a psychophysiological cost as demonstrated by lower phasic pupil response, and greater heart rate and prefrontal activity. Prefrontal cortex seems to be a central region for mitigating the influence of stress because it subserves crucial functions (e.g. inhibition, working memory) that can promote the engagement of coping strategies. Overall, findings confirmed the psychophysiological cost of both mental effort and stress. Stress likely triggered increased motivation and the recruitment of additional cognitive resources that minimize its aversive effects on task performance (effectiveness), but these compensatory efforts consumed resources that caused a loss of cognitive efficiency (ratio between performance effectiveness and mental effort).

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.

Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS

An improved understanding of how the brain allocates mental resources as a function of task difficulty is critical for enhancing human performance. Functional near infrared spectroscopy (fNIRS) is a field-deployable optical brain monitoring technology that provides a direct measure of cerebral blood flow in response to cognitive activity. We found that fNIRS was sensitive to variations in task difficulty in both real-life (flight simulator) and laboratory settings (tests measuring executive functions), showing increased concentration of oxygenated hemoglobin (HbO2) and decreased concentration of deoxygenated hemoglobin (HHb) in the prefrontal cortex as the tasks became more complex. Intensity of prefrontal activation (HbO2 concentration) was not clearly correlated to task performance. Rather, activation intensity shed insight on the level of mental effort, i.e., how hard an individual was working to accomplish a task. When combined with performance, fNIRS provided an estimate of the participants’ neural efficiency, and this efficiency was consistent across levels of difficulty of the same task. Overall, our data support the suitability of fNIRS to assess the mental effort related to human operations and represents a promising tool for the measurement of neural efficiency in other contexts such as training programs or the clinical setting.

The impact of luminance on tonic and phasic pupillary responses to sustained cognitive load

Pupillary reactions independent of light conditions have been linked to cognition for a long time. However, the light conditions can impact the cognitive pupillary reaction. Previous studies underlined the impact of luminance on pupillary reaction, but it is still unclear how luminance modulates the sustained and transient components of pupillary reaction - tonic pupil diameter and phasic pupil response. In the present study, we investigated the impact of the luminance on these two components under sustained cognitive load. Fourteen participants performed a novel working memory task combining mathematical computations with a classic n-back task. We studied both tonic pupil diameter and phasic pupil response under low (1-back) and high (2-back) working memory load and two luminance levels (gray and white). We found that the impact of working memory load on the tonic pupil diameter was modulated by the level of luminance, the increase in tonic pupil diameter with the load being larger under lower luminance. In contrast, the smaller phasic pupil response found under high load remained unaffected by luminance. These results showed that luminance impacts the cognitive pupillary reaction - tonic pupil diameter (phasic pupil response) being modulated under sustained (respectively, transient) cognitive load. These findings also support the relationship between the locus-coeruleus system, presumably functioning in two firing modes - tonic and phasic - and the pupil diameter. We suggest that the tonic pupil diameter tracks the tonic activity of the locus-coeruleus while phasic pupil response reflects its phasic activity. Besides, the designed novel cognitive paradigm allows the simultaneous manipulation of sustained and transient components of the cognitive load and is useful for dissociating the effects on the tonic pupil diameter and phasic pupil response.

Pilot Flying and Pilot Monitoring’s Aircraft State Awareness During Go-Around Execution in Aviation: A Behavioral and Eye Tracking Study

ABSTRACT Objective: Examination of the performance and visual scanning of aircrews during final approach and an unexpected go-around maneuver. Background: Accident and incident analyses have revealed that go-around procedures are often imperfectly performed because of their complexity, their high time stress, and their rarity of occurrence that avails little time for practice. We wished to examine this experimentally and establish the frequency and nature of errors in both flight-performance and visual scanning. Method: We collected flight-performance (e.g., errors in procedures, excessive flight deviations) and eye-tracking data of 12 flight crews who performed final approach and go-around flight phases in realistic full-flight transport-category simulators. Results: The pilot performance results showed that two thirds of the crews committed errors including critical trajectory deviations during go-arounds, a precursor of accidents. Eye-tracking analyses revealed that the cross-checking process was not always efficient in detecting flight-path deviations when they occurred. Ocular data also highlighted different visual strategies between the 2 crew members during the 2 flight phases. Conclusion: This study reveals that the go-around is a challenging maneuver. It demonstrates the advantages of eye tracking and suggests that it is a valuable tool for the explicit training of attention allocation during go-arounds to enhance flight safety.

High Working Memory Load Impairs Language Processing during a Simulated Piloting Task: An ERP and Pupillometry Study

Given the important amount of visual and auditory linguistic information that pilots have to process, operating an aircraft generates a high working-memory load (WML). In this context, the ability to focus attention on relevant information and to remain responsive to concurrent stimuli might be altered. Consequently, understanding the effects of WML on the processing of both linguistic targets and distractors is of particular interest in the study of pilot performance. In the present work, participants performed a simplified piloting task in which they had to follow one of three colored aircraft, according to specific written instructions (i.e., the written word for the color corresponding to the color of one of the aircraft) and to ignore either congruent or incongruent concurrent auditory distractors (i.e., a spoken name of color). The WML was manipulated with an n-back sub-task. Participants were instructed to apply the current written instruction in the low WML condition, and the 2-back written instruction in the high WML condition. Electrophysiological results revealed a major effect of WML at behavioral (i.e., decline of piloting performance), electrophysiological, and autonomic levels (i.e., greater pupil diameter). Increased WML consumed resources that could not be allocated to the processing of the linguistic stimuli, as indexed by lower P300/P600 amplitudes. Also, significantly, lower P600 responses were measured in incongruent vs. congruent trials in the low WML condition, showing a higher difficulty reorienting attention toward the written instruction, but this effect was canceled in the high WML condition. This suppression of interference in the high load condition is in line with the engagement/distraction trade-off model. We propose that P300/P600 components could be reliable indicators of WML and that they allow an estimation of its impact on the processing of linguistic stimuli.

Pupil Dilation and Eye Movements Can Reveal Upcoming Choice in Dynamic Decision-Making

In dynamic environments such as air-traffic control, emergency response and security surveillance, there are severe constraints to information processing and decision-making. Human operators must constantly monitor, assess, and integrate incoming information in order to make optimal decisions in such complex environments. In order to maximize operators’ performance, there is a need for effective technological support for dynamic decision-making. Eye tracking is one promising avenue that can provide online, non-obtrusive indices of cognitive functioning. Using a simulated maritime decision-making environment, we evaluated whether oculometry may be exploited to foretell the decision made by the operator beforehand. Our results showed that pupil dilation and fixation transitions can reveal the upcoming judgment of the human operator by about half a second before the decision. This finding can be useful to design adaptive support tools for dynamic decision-making by integrating the operator’s cognitive state.

Eliciting Sustained Mental Effort Using the Toulouse N-Back Task: Prefrontal Cortex and Pupillary Responses

In safety-critical environments such as piloting or air-traffic control, the study of mental overload is crucial to further reduce accident rates. However, researchers face the complexity of inducing an important amount of mental effort in laboratory conditions. Therefore, we designed a novel paradigm, named “Toulouse N-back Task” (TNT), combining the classical n-back task with a mathematical processing to replicate the multidimensional sustained high mental workload (MW) existing in many complex occupations. Instead of memorizing and comparing unique items, as in classical n-back task, participants have to memorize and to compare the results of mathematics operations. Twenty participants were tested with the TNT under three load factors (n = 0, 1, or 2) with functional Near-InfraRed Spectroscopy (fNIRS) and pupillary measurements. The results revealed that higher difficulty degraded the cognitive performance together with increased prefrontal oxygenation and an increase in pupil diameter. Hence, hemodynamic responses and pupil diameter were sensitive to different levels of TNT’s difficulty. This paradigm could serve as a viable alternative to the classical n-back task and enable the progressive increase of the difficulty, for example, to test “high performer” individuals.

Author Correction: Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.