Measurements by biphasic changes of the alpha band amplitude as indicators of arousal level

Unravelling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks

Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators' performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just "when" but also "what" to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments.

Event-Related Alpha-Band Power Changes During Self-reflection and Working Memory Tasks in Healthy Individuals

Dysfunctional attentional control is observed in patients with mental disorders. However, there is no established neurophysiological method to assess attention in such patients. We showed a discrepancy in alpha-band power in the tasks that evoked internal and external attention event-related alpha-band power changes in healthy subjects during self-reflection (SR) and working memory (WM) tasks in a preliminary study. In this study, we aimed at elucidating event-related alpha-band power changes in healthy subjects during the tasks, addressing the shortcomings of the previous study. Sixteen healthy volunteers were examined for the event-related power (ERpow) change during the tasks. The results demonstrated the discrepancy of alpha-band ERpow at 8, 10, and 12 Hz in the parieto-occipital area between the WM and SR tasks for a period between a target stimulus and a command stimulus, where a participant switched to internal attention from external attention according to the SR task and remained at external attention according to the WM task. The results suggest that alpha-band ERpow in this area is associated with the direction of attention in response to cognitive stimuli, indicating that the findings of ERpow during the two tasks would potentially aid in the clarification of the pathophysiology of the dysfunctional change in attention in patients with psychiatric disorders.

The effects of different fatigue levels on brain-behavior relationships in driving

BACKGROUND

In the past decade, fatigue has been regarded as one of the main factors impairing task performance and increasing behavioral lapses during driving, even leading to fatal car crashes. Although previous studies have explored the impact of acute fatigue through electroencephalography (EEG) signals, it is still unclear how different fatigue levels affect brain-behavior relationships.

METHODS

A longitudinal study was performed to investigate the brain dynamics and behavioral changes in individuals under different fatigue levels by a sustained attention task. This study used questionnaires in combination with actigraphy, a noninvasive means of monitoring human physiological activity cycles, to conduct longitudinal assessment and tracking of the objective and subjective fatigue levels of recruited participants. In this study, degrees of effectiveness score (fatigue rating) are divided into three levels (normal, reduced, and high risk) by the SAFTE fatigue model.

RESULTS

Results showed that those objective and subjective indicators were negatively correlated to behavioral performance. In addition, increased response times were accompanied by increased alpha and theta power in most brain regions, especially the posterior regions. In particular, the theta and alpha power dramatically increased in the high-fatigue (high-risk) group. Additionally, the alpha power of the occipital regions showed an inverted U-shaped change.

CONCLUSION

Our results help to explain the inconsistent findings among existing studies, which considered the effects of only acute fatigue on driving performance while ignoring different levels of resident fatigue, and potentially lead to practical and precise biomathematical models to better predict the performance of human operators.

Domain-general Stroop Performance and Hemispheric Asymmetries: A Resting-state EEG Study

The ability to suppress irrelevant information while executing a task, also known as interference resistance ability, is a function of pFC that is critical for successful goal-directed human behavior. In the study of interference resistance and, more generally, executive functions, two key questions are still open: Does pFC contribute to cognitive control abilities through lateralized but domain-general mechanisms or through hemispheric specialization of domain-specific processes? And what are the underlying causes of interindividual differences in executive control performance? To shed light on these issues, here we employed an interindividual difference approach to investigate whether participants' hemispheric asymmetry in resting-state electrophysiological brain dynamics may reflect their variability in domain-general interference resistance. We recorded participants' resting-state electroencephalographic activity and performed spectral power analyses on the estimated cortical source activity. To measure participants' lateralized brain dynamics at rest, we computed the right–left hemispheric asymmetry score for the β/α power ratio. To measure their domain-general interference resistance ability, verbal and spatial Stroop tasks were used. Robust correlations followed by intersection analyses showed that participants with stronger resting-state-related left-lateralized activity in different pFC regions, namely the mid-posterior superior frontal gyrus, middle and posterior middle frontal gyrus, and inferior frontal junction, were more able to inhibit irrelevant information in both domains. The present results confirm and extend previous findings showing that neurophysiological difference factors may explain interindividual differences in executive functioning. They also provide support for the hypothesis of a left pFC hemispheric specialization for domain-independent phasic cognitive control processes mediating Stroop performance.

Assessing and conceptualizing frontal EEG asymmetry: An updated primer on recording, processing, analyzing, and interpreting frontal alpha asymmetry

Frontal electroencephalographic (EEG) alpha asymmetry is widely researched in studies of emotion, motivation, and psychopathology, yet it is a metric that has been quantified and analyzed using diverse procedures, and diversity in procedures muddles cross-study interpretation. The aim of this article is to provide an updated tutorial for EEG alpha asymmetry recording, processing, analysis, and interpretation, with an eye towards improving consistency of results across studies. First, a brief background in alpha asymmetry findings is provided. Then, some guidelines for recording, processing, and analyzing alpha asymmetry are presented with an emphasis on the creation of asymmetry scores, referencing choices, and artifact removal. Processing steps are explained in detail, and references to MATLAB-based toolboxes that are helpful for creating and investigating alpha asymmetry are noted. Then, conceptual challenges and interpretative issues are reviewed, including a discussion of alpha asymmetry as a mediator/moderator of emotion and psychopathology. Finally, the effects of two automated component-based artifact correction algorithms-MARA and ADJUST-on frontal alpha asymmetry are evaluated.

Mind over chatter: plastic up-regulation of the fMRI salience network directly after EEG neurofeedback

Neurofeedback (NFB) involves a brain-computer interface that allows users to learn to voluntarily control their cortical oscillations, reflected in the electroencephalogram (EEG). Although NFB is being pioneered as a noninvasive tool for treating brain disorders, there is insufficient evidence on the mechanism of its impact on brain function. Furthermore, the dominant rhythm of the human brain is the alpha oscillation (8-12 Hz), yet its behavioral significance remains multifaceted and largely correlative. In this study with 34 healthy participants, we examined whether during the performance of an attentional task, the functional connectivity of distinct fMRI networks would be plastically altered after a 30-min session of voluntary reduction of alpha rhythm (n=17) versus a sham-feedback condition (n=17). We reveal that compared to sham-feedback, NFB induced an increase of connectivity within regions of the salience network involved in intrinsic alertness (dorsal anterior cingulate), which was detectable 30 min after termination of training. The increase in salience network (default-mode network) connectivity was negatively (positively) correlated with changes in 'on task' mind-wandering as well as resting state alpha rhythm. Crucially, we observed a causal dependence between alpha rhythm synchronization during NFB and its subsequent change at resting state, not exhibited by the SHAM group. Our findings provide neurobehavioral evidence for the brain's exquisite functional plasticity, and for a temporally direct impact of NFB on a key cognitive control network, suggesting a promising basis for its use to treat cognitive disorders under physiological conditions.

EEG alpha phase shifts during transition from wakefulness to drowsiness

Phases of alpha oscillations recorded by EEG were typically studied in the context of event or task related experiments, rarely during spontaneous alpha activity and in different brain states. During wake-to-drowsy transition they change unevenly, depending on the brain region. To explore their dynamics, we recorded ten adult healthy individuals in these two states. Alpha waves were treated as stable frequency and variable amplitude signals with one carrier frequency (CF). A method for calculating their CF phase shifts (CFPS) and CF phase potentials (CFPP) was developed and verified on surrogate signals as more accurate than phase shifts of Fourier components. Probability density estimate (PDE) of CFPS, CFPP and CF phase locking showed that frontal and fronto-temporal areas of the cortex underwent more extensive changes than posterior regions. The greatest differences were found between pairs of channels involving F7, F8, F3 and F4 (PDE of CFPS); F7, F8, T3 and T4 (CFPP); F7, F8, F3, F4, C3, C4 and T3 (decrease in CF phase locking). A topographic distribution of channels with above the average phase locking in the wake state revealed two separate regions occupying anterior and posterior brain areas (with intra regional and inter hemispheric connections). These regions merged and became mutually phase locked longitudinally in the drowsy state. Changes occurring primarily in the frontal and fronto-temporal regions correlated with an early decrease of alertness. Areas of increased phase locking might be correlated with topography of synchronous neuronal assemblies conceptualized within neural correlates of consciousness.

This is the rhythm of your eyes: the phase of ongoing electroencephalogram oscillations modulates saccadic reaction time

Motor reaction times in humans are highly variable from one trial to the next, even for simple and automatic tasks, such as shifting your gaze to a suddenly appearing target. Although classic models of reaction time generation consider this variability to reflect intrinsic noise, some portion of it could also be attributed to ongoing neuronal processes. For example, variations of alpha rhythm frequency (8-12 Hz) across individuals, or alpha amplitude across trials, have been related previously to manual reaction time variability. Here we investigate the trial-by-trial influence of oscillatory phase, a dynamic marker of ongoing activity, on saccadic reaction time in three paradigms of increasing cognitive demand (simple reaction time, choice reaction time, and visual discrimination tasks). The phase of ongoing prestimulus activity in the high alpha/low beta range (11-17 Hz) at frontocentral locations was strongly associated with saccadic response latencies. This relation, present in all three paradigms, peaked for phases recorded ∼50 ms before fixation point offset and 250 ms before target onset. Reaction times in the most demanding discrimination task fell into two distinct modes reflecting a fast but inaccurate strategy or a slow and efficient one. The phase effect was markedly stronger in the group of subjects using the faster strategy. We conclude that periodic fluctuations of electrical activity attributable to neuronal oscillations can modulate the efficiency of the oculomotor system on a rapid timescale; however, this relation may be obscured when cognitive load also adds a significant contribution to response time variability.

Improving classification rates for use in fatigue countermeasure devices using brain activity

Fatigue can be defined as a state that involves psychological and physical tiredness with a range of symptoms such as tired eyes, yawning and increased blink rate. It has major implications for work place and road safety as well as a negative symptom of many acute and chronic illnesses. As such there has been considerable research dedicated to systems or algorithms that can be used to detect and monitor the onset of fatigue. This paper examines using electroencephalography (EEG) signals to classify fatigue and alert states as a function of subjective self-report, driving performance and physiological symptoms. The results show that EEG classification network for fatigue improved from 75% to 80% when these factors are applied, especially when the data is grouped by subjective self-report of fatigue with classification accuracy improving to 84.5%.

Where the BOLD signal goes when alpha EEG leaves

Previous studies using simultaneous EEG and fMRI recordings have yielded discrepant results regarding the topography of brain activity in relation to spontaneous power fluctuations in the alpha band of the EEG during eyes-closed rest. Here, we explore several possible explanations for this discrepancy by re-analyzing in detail our previously reported data. Using single subject analyses as a starting point, we found that alpha power decreases are associated with fMRI signal increases that mostly follow two distinct patterns: either 'visual' areas in the occipital lobe or 'attentional' areas in the frontal and parietal lobe. On examination of the EEG spectra corresponding to these two fMRI patterns, we found greater relative theta power in sessions yielding the 'visual' fMRI pattern during alpha desynchronization and greater relative beta power in sessions yielding the 'attentional' fMRI pattern. The few sessions that fell into neither pattern featured the overall lowest theta and highest beta power. We conclude that the pattern of brain activation observed during spontaneous power reduction in the alpha band depends on the general level of brain activity as indexed over a broader spectral range in the EEG. Finally, we relate these findings to the concepts of 'resting state' and 'default mode' and discuss how - as for sleep - EEG-based criteria might be used for staging brain activity during wakefulness.

Modulation of induced gamma band activity in the human EEG by attention and visual information processing

Here we present a series of four studies aimed to investigate the link between induced gamma band activity in the human EEG and visual information processing. We demonstrated and validated the modulation of spectral gamma band power by spatial selective visual attention. When subjects attended to a certain stimulus, spectral power was increased as compared to when the same stimulus was ignored. In addition, we showed a shift in spectral gamma band power increase to the contralateral hemisphere when subjects shifted their attention to one visual hemifield. The following study investigated induced gamma band activity and the perception of a Gestalt. Ambiguous rotating figures were used to operationalize the law of good figure (gute Gestalt). We found increased gamma band power at posterior electrode sites when subjects perceived an object. In the last experiment we demonstrated a differential hemispheric gamma band activation when subjects were confronted with emotional pictures. Results of the present experiments in combination with other studies presented in this volume are supportive for the notion that induced gamma band activity in the human EEG is closely related to visual information processing and attentional perceptual mechanisms.

A controlled daytime challenge of motor performance and vigilance in sleep bruxers

Many etiological factors have been suggested for sleep bruxism. Among these, elevated mental and physical alertness has been proposed to characterize sleep bruxers. The present study tests the hypothesis that, during the day-time, sleep bruxers are more vigilant and more prone to react to a motor command than are control subjects. Seven sleep bruxers, diagnosed polysomnographically according to validated research criteria, were matched for age and gender to seven control subjects. A simple reaction time task was selected to assess daytime vigilance and motor responsiveness. The following physiological measures were recorded: reaction time, error rate, electroencephalography, electrocardiography, electromyography, and video detection of body movements. Analysis of these variables showed no differences between groups. During the test, bruxers and controls showed a parallel decrease in EEG vigilance and heart rate over time. Frequency of orofacial and body movements was the same in both groups, and no clenching activity was observed during the experimental test. Subjects' visual analog scale ratings revealed that both controls and bruxers were more competitive after the test than before, and bruxers were slightly more anxious than controls before and after the test. Together, the results indicate that sleep bruxers are neither more vigilant nor more prone to react to a motor command during the daytime than are control subjects.

EEG differences and cognitive style

Individuals differences in information processing related to cognitive style were investigated by EEG recording during cognitive tasks. Fifteen adults received the Cognitive Styles Analysis which assessed their positions on two dimensions: the wholist-analytic and the verbal-imagery. The EEG from midline, paramedial and lateral electrode clusters was recorded, while subjects viewed words presented at different rates. A button was pressed when a word was in a target conceptual category. Off-line analysis produced spectral powers for delta, theta, alpha, beta 1, beta 2 and gamma bands. For the midline, the wholists had higher output than analytics in theta and alpha, but lower in gamma. In the paramedial cluster, verbalisers had greater right power than imagers for all bands except alpha. Further, the overall power was greater on the right for imagers than verbalisers frontally, and the converse occipitally. In the lateral grouping, the wholist-verbalisers had greater overall power left antero-temporally than other sub-groups.

EEG and cardiac activation during periodic leg movements in sleep: support for a hierarchy of arousal responses

OBJECTIVE

To investigate other physiologic changes that occur with periodic leg movements during sleep (PLMS) that might be considered to be more sensitive indices of sleep fragmentation.

BACKGROUND

Although PLMS are associated with recurrent microarousals (MA), the frequency of PLMS with MA does not correlate with objective daytime sleepiness. It is postulated that the lack of correlation results from the low sensitivity of the standard criteria used to score MA.

METHODS

Ten drug-free patients with a polygraphic and clinical diagnosis of restless legs syndrome (RLS) and PLMS were examined. The EEG correlates of PLMS were analyzed by visual scoring and spectral analysis during PLMS that ended in a visible microarousal (PLMS with MA) or not (PLMS without MA). The R-R interval in the EKG signal was also examined.

RESULTS

A total of 34% of PLMS were associated with MA lasting >3 seconds, and 3% of PLMS were associated with MA lasting <3 seconds. Although PLMS with MA were associated with an increase in alpha activity, for PLMS without MA a significant increase in delta and theta activity was present. Both types of PLMS induced a shortening of the R-R interval; this was particularly more marked for PLMS with MA.

CONCLUSIONS

First, visual scoring of MA that include a duration of less than 3 seconds has little effect on the detection of PLMS with MA. Second, EEG activation and tachycardia are present during both types of PLMS. Third, a hierarchy in the arousal response is present-going from autonomic activation to bursts of delta activity to alpha activity to a full awakening.