EMG-based Simultaneous Estimations of Joint Angle and Torque during Hand Interactions with Environments.

It is necessary to control contact force through modulation of joint stiffness in addition to the position of our limb when manipulating an object. This is achieved by contracting the agonist muscles in an appropriate magnitude, as well as, balancing it with contraction of the antagonist muscles. Here we develop a decoding technique that estimates both the position and torque of a joint of the limb in interaction with an environment based on activities of the agonist-antagonistic muscle pairs using electromyography in real time. The long short-term memory (LSTM) network that is capable of learning time series of a longtime span with varying time lags is employed as the core processor of the proposed technique. We tested both the unidirectional LSTM network and bidirectional LSTM network. A validation was conducted on the wrist joint moving along a given trajectory under resistance generated by a robot. The decoding approach provided an agreement of greater than 93% in kinetics (i.e. torque) estimation and an agreement of greater than 83% in kinematics (i.e. angle) estimation, between the actual and estimated variables, during interactions with an environment. We found no significant differences in performance between the unidirectional LSTM and bidirectional LSTM as the learning device of the proposed decoding method.

Changes in Mental Workload and Motor Performance Throughout Multiple Practice Sessions Under Various Levels of Task Difficulty.

The allocation of mental workload is critical to maintain cognitive-motor performance under various demands. While mental workload has been investigated during performance, limited efforts have examined it during cognitive-motor learning, while none have concurrently manipulated task difficulty. It is reasonable to surmise that the difficulty level at which a skill is practiced would impact the rate of skill acquisition and also the rate at which mental workload is reduced during learning (relatively slowed for challenging compared to easier tasks). This study aimed to monitor mental workload by assessing cortical dynamics during a task practiced under two difficulty levels over four days while perceived task demand, performance, and electroencephalography (EEG) were collected. As expected, self-reported mental workload was reduced, greater working memory engagement via EEG theta synchrony was observed, and reduced cortical activation, as indexed by progressive EEG alpha synchrony was detected during practice. Task difficulty was positively related to the magnitude of alpha desynchrony and accompanied by elevations in the theta-alpha ratio. Counter to expectation, the absence of an interaction between task difficulty and practice days for both theta and alpha power indicates that the refinement of mental processes throughout learning occurred at a comparable rate for both levels of difficulty. Thus, the assessment of brain dynamics was sensitive to the rate of change of cognitive workload with practice, but not to the degree of difficulty. Future work should consider a broader range of task demands and additional measures of brain processes to further assess this phenomenon.

Combined assessment of attentional reserve and cognitive-motor effort under various levels of challenge with a dry EEG system.

A novel ERP approach was proposed to index variations in mental workload, particularly in attentional reserve, which is complementary to EEG spectral content thought to reflect mental effort. To our knowledge, no study has assessed mental effort and attentional reserve simultaneously in EEG gel-based and, importantly, dry systems, which are particularly well suited for real-world settings. Therefore, by systematically considering ERP, EEG spectral, and importantly the combination of both, this study examined if a small set of dry EEG electrodes could detect changes in both spectral and ERP metrics to assess the mental workload under various challenges with a similar fidelity to their gel-based counterparts in a laboratory setting. By employing both EEG gel-based and dry systems, the ERP and spectral markers were computed while participants executed a visuomotor task under three levels of challenge. For both EEG systems, more challenging levels of difficulty were associated with concomitant changes in ERP amplitude, and spectral power reflected a reduction of the attentional reserve and an increase in cognitive-motor effort, respectively. Those variations in attentional reserve and cognitive-motor effort collectively indexed mental workload with nearly identical fidelity for both gel-based and dry EEG systems. These findings promise to assess the mental workload in situations where the use of dry EEG systems could be advantageously employed to examine human cognitive-motor performance.

Empirical evidence for the relationship between cognitive workload and attentional reserve.

While the concepts of cognitive workload and attentional reserve have been thought to have an inverse relationship for some time, such a relationship has never been empirically tested. This was the purpose of the present study. Aspects of the electroencephalogram were used to assess both cognitive workload and attentional reserve. Specifically, spectral measures of cortical activation were used to assess cognitive workload, while amplitudes of the event-related potential from the presentation of unattended "novel" sounds were used to assess attentional reserve. The relationship between these two families of measures was assessed using canonical correlation. Twenty-seven participants performed a flight simulator task under three levels of challenge. Verification of manipulation was performed using self-report measures of task demand, objective task performance, and heart rate variability using electrocardiography. Results revealed a strong, negative relationship between the spectral measures of cortical activation, believed to be representative of cognitive workload, and ERP amplitudes, believed to be representative of attentional reserve. This finding provides support for the theoretical and intuitive notion that cognitive workload and attentional reserve are inversely related. The practical implications of this result include improved state classification using advanced machine learning techniques, enhanced personnel selection/recruitment/placement, and augmented learning/training.

Expert-novice differences in SMR activity during dart throwing.

Previous evidence suggests that augmented sensorimotor rhythm (SMR) activity is related to the superior regulation of processing cognitive-motor information in motor performance. However, no published studies have examined the relationship between SMR and performance in precision sports; thus, this study examined the relationship between SMR activity and the level of skilled performance in tasks requiring high levels of attention (e.g., dart throwing). We hypothesized that skilled performance would be associated with higher SMR activity. Fourteen dart-throwing experts and eleven novices were recruited. Participants were requested to perform 60 dart throws while EEG was recorded. The 2(Group: Expert, Novice)×2(Time window: -2000 ms to -1000 ms, -1000 ms to 0 ms) ANOVA showed that the dart-throwing experts maintained a relatively higher SMR power than the novices before dart release. These results suggest that SMR might reflect the adaptive regulation of cognitive-motor processing during the preparatory period.

Brain biomarkers based assessment of cognitive workload in pilots under various task demands.

Cognitive workload is an important element of cognitive-motor performance such as that exhibited during the piloting of an aircraft. Namely, an increase in task demands on the pilot can elevate cognitive information processing and, thus, the risk of human error. As such, there is a need to develop methods that reliably assess mental workload in pilots within operational settings. The present study contributes to this research goal by identifying physiological and brain biomarkers of cognitive workload and attentional reserve during a simulated aircraft piloting task under three progressive levels of challenge. A newly developed experimental method was employed by which electroencephalography (EEG) was acquired via a dry (i.e., gel-free sensors) system using few scalp sites. Self-reported responses to surveys and piloting performance indicators were analyzed. The findings revealed that as the challenge (task demands) increased, the perceived mental load increased, attentional reserve was attenuated, and task performance decreased. Such an increase in task demands was also reflected by changes in heart rate variability (HRV), as well as in the amplitude of the P300 component of event-related potentials to auditory probes, and in the spectral power of specific EEG frequency bands. This work provides a first step towards a long-term goal to develop a composite system of biomarkers for real-time cognitive workload assessment and state assessment of pilots in operational settings.

The influence of social evaluation on cerebral cortical activity and motor performance: a study of "Real-Life" competition.

Motor performance in a social evaluative environment was examined in participants (N = 19) who completed a pistol shooting task under both performance-alone (PA) and competitive (C) conditions. Electroencephalographic (EEG), autonomic, and psychoendocrine activity were recorded in addition to kinematic measures of the aiming behavior. State anxiety, heart rate, and cortisol were modestly elevated during C and accompanied by relative desynchrony of high-alpha power, increased cortico-cortical communication between motor and non-motor regions, and degradation of the fluency of aiming trajectory, but maintenance of performance outcome (i.e., score). The findings reveal that performance in a complex social-evaluative environment characterized by competition results in elevated cortical activity beyond that essentially required for motor performance that translated as less efficient motor behavior.

Stress, emotion regulation and cognitive performance: the predictive contributions of trait and state relative frontal EEG alpha asymmetry.

The relationship between trait and state measures of frontal lobe EEG alpha-band asymmetry in regard to indexing the approach-withdrawal dimension of emotion is unclear. The comparative predictive power of these constructs to explain emotion regulation and cognitive performance was examined under varying degrees of emotional challenge. The Capability Model posits the neural underpinnings of the relative difference in electrical activity between the left and right frontal lobes as a situational mechanism possibly indexing prefrontal-amygdalar interactions and psychological state. EEG, skin conductance, heart rate and acoustic startle amplitude were collected during a working memory task under three increasing levels of stress (final level was threat of shock). During threat of shock participants with higher state asymmetry exhibited greater emotion regulation compared to those with lower scores as indexed by significant attenuation of eyeblink startle magnitudes. The trait measure of frontal EEG asymmetry failed to account for significant variability in emotion regulation. Results implicate state-specific relative left frontal lobe activity as having an adaptive role in the regulation of emotion during cognitive challenge, but only under conditions of sufficient stress.

Cerebral cortical dynamics and the quality of motor behavior during social evaluative challenge.

To determine the influence of arousal on cerebral cortical dynamics and motor behavior, 58 channels of EEG were recorded in 13 college-age men (n=6) and women during an aiming task performed alone and in a social evaluation condition. Moderate arousal, as measured by heart rate, skin conductance, and self-reported mood, was induced during the social evaluation. In accord with the Yerkes-Dodson Hypothesis, which posits optimal performance during moderate arousal, improved performance (i.e., quality of the aiming trajectories) was observed. During social evaluation, changes in electroencephalogram dynamics included decreased coherence between the motor planning (Fz) and right temporal region (T4), increased coherence in the sensorimotor networks subserving the task, and increased local processing (gamma, 30-44 Hz) in the temporal regions. The results imply that moderate arousal promotes specific alterations in cortical dynamics that facilitate motor performance.

Visuomotor expertise and dimensional complexity of cerebral cortical activity.

PURPOSE: This study employed the correlation dimension (D2) to examine whether visuomotor expertise was inversely related to the complexity of cerebral cortical activity. METHOD: Expert rifle shooters (N = 15) and novices (N = 21) completed 40 shots in the standing position during which the electroencephalogram (EEG) was recorded at 10 sites (F3, F4, C3, C4, T3, T4, P3, P4, O1, and O2) during a 5-s aiming period prior to trigger pull. D2 was derived for each trial and averaged across shots. A 2 x 2 x 5 (group x cerebral hemisphere x region) ANOVA was employed to contrast D2, while correlation analyses were used to determine the relationship between D2 and target shooting accuracy as well as variability of shot placement. RESULTS: As predicted, experts exhibited lower D2 (5.02 +/- 0.16 vs 5.49 +/- 0.13, respectively) and greater accuracy of shot placement ((339.8 +/- 44.7 vs 90.7 +/- 38.9 points out of 400 possible, respectively). Experts also exhibited an inverse relationship between D2 and shooting accuracy, while, in contrast, novices revealed a positive relationship. DISCUSSION: The results suggest that refinement and efficiency of cerebral cortical activity facilitates visuomotor performance. Lower complexity may be associated with less neuromotor "noise" in the brain, thus reducing interference with intended action.