Brain Processes Involved in Motor Planning Are a Dominant Factor for Inducing Event-Related Desynchronization.

Event-related desynchronization (ERD) is a relative attenuation in the spectral power of an electroencephalogram (EEG) observed over the sensorimotor area during motor execution and motor imagery. It is a well-known EEG feature and is commonly employed in brain-computer interfaces. However, its underlying neural mechanisms are not fully understood, as ERD is a single variable correlated with external events involving numerous pathways, such as motor intention, planning, and execution. In this study, we aimed to identify a dominant factor for inducing ERD. Participants were instructed to grasp their right hand with three different (10, 25, or 40%MVF: maximum voluntary force) levels under two distinct experimental conditions: a closed-loop condition involving real-time visual force feedback (VF) or an open-loop condition in a feedforward (FF) manner. In each condition, participants were instructed to repeat the grasping task a certain number of times with a timeline of Rest (10.0 s), Preparation (1.0 s), and Motor Execution (4.0 s) periods, respectively. EEG signals were recorded simultaneously with the motor task to evaluate the time-course of the event-related spectrum perturbation for each condition and dissect the modulation of EEG power. We performed statistical analysis of mu and beta-ERD under the instructed grasping force levels and the feedback conditions. In the FF condition (i.e., no force feedback), mu and beta-ERD were significantly attenuated in the contralateral motor cortex during the middle of the motor execution period, while ERD in the VF condition was maintained even during keep grasping. Only mu-ERD at the somatosensory cortex tended to be slightly stronger in high load conditions. The results suggest that the extent of ERD reflects neural activity involved in the motor planning process for changing virtual equilibrium point rather than the motor control process for recruiting motor neurons to regulate grasping force.

Enhanced Visual Feedback Using Immersive VR Affects Decision Making Regarding Hand Use With a Simulated Impaired Limb.

The long-term effects of impairment have a negative impact on the quality of life of stroke patients in terms of not using the affected limb even after some recovery (i.e., learned non-use). Immersive virtual reality (IVR) has been introduced as a new approach for the treatment of stroke rehabilitation. We propose an IVR-based therapeutic approach to incorporate positive reinforcement components in motor coordination as opposed to constraint-induced movement therapy (CIMT). This study aimed to investigate the effect of IVR-reinforced physical therapy that incorporates positive reinforcement components in motor coordination. To simulate affected upper limb function loss in patients, a wrist weight was attached to the dominant hand of participant. Participants were asked to choose their right or left hand to reach toward a randomly allocated target. The movement of the virtual image of the upper limb was reinforced by visual feedback to participants, that is, the participants perceived their motor coordination as if their upper limb was moving to a greater degree than what was occurring in everyday life. We found that the use of the simulated affected limb was increased after the visual feedback enhancement intervention, and importantly, the effect was maintained even after gradual withdrawal of the visual amplification. The results suggest that positive reinforcement within the IVR could induce an effect on decision making in hand usage.

Statistical Learning Model of the Sense of Agency.

A sense of agency (SoA) is the experience of subjective awareness regarding the control of one's actions. Humans have a natural tendency to generate prediction models of the environment and adapt their models according to changes in the environment. The SoA is associated with the degree of the adaptation of the prediction models, e.g., insufficient adaptation causes low predictability and lowers the SoA over the environment. Thus, identifying the mechanisms behind the adaptation process of a prediction model related to the SoA is essential for understanding the generative process of the SoA. In the first half of the current study, we constructed a mathematical model in which the SoA represents a likelihood value for a given observation (sensory feedback) in a prediction model of the environment and in which the prediction model is updated according to the likelihood value. From our mathematical model, we theoretically derived a testable hypothesis that the prediction model is updated according to a Bayesian rule or a stochastic gradient. In the second half of our study, we focused on the experimental examination of this hypothesis. In our experiment, human subjects were repeatedly asked to observe a moving square on a computer screen and press a button after a beep sound. The button press resulted in an abrupt jump of the moving square on the screen. Experiencing the various stochastic time intervals between the action execution (button-press) and the consequent event (square jumping) caused gradual changes in the subjects' degree of their SoA. By comparing the above theoretical hypothesis with the experimental results, we concluded that the update (adaptation) rule of the prediction model based on the SoA is better described by a Bayesian update than by a stochastic gradient descent.

Assessment and Rating of Motor Cerebellar Ataxias With the Kinect v2 Depth Sensor: Extending Our Appraisal.

Current assessment of patients with cerebellar disorders is based on conventional neurological examination that is dependent on subjective judgements. Quantitative measurement of cerebellar ataxias (CAs) is essential for assessment of evidence-based treatments and the monitoring of the progress or recovery of diseases. It may provide us a useful tool to navigate future treatments for ataxia. We developed a Kinect v2. sensor system with a novel algorithm to measure and evaluate movements for two tests of Scale for the Assessment and Rating of Ataxia (SARA): the nose-finger test and gait. For the nose-finger test, we evaluated and compared accuracy, regularities and smoothness in the movements of the index finger and the proximal limbs between cerebellar patients and control subjects. For the task of walking, we evaluated and compared stability between the two groups. The precision of the system for evaluation of movements was smaller than 2 mm. For the nose-finger test, the mildly affected patients tended to show more instability than the control subjects. For a severely affected patient, our system quantified the instability of movements of the index finger using kinematic parameters, such as fluctuations and average speed. The average speed appears to be the most sensitive parameter that contrasts between patients with CAs and control subjects. Furthermore, our system also detected the adventitious movements of more proximal body parts, such as the elbow, shoulder and head. Assessment of walking was possible only in patients with mild CAs. They demonstrated large sways and compensatory wide stances. These parameters appeared to show higher accuracy than SARA. This examiner-independent device measures movements of the points of interest of SARA more accurately than eye and further provides additional information about the ataxic movements (e.g., the adventitious movements of the elbow, shoulder and head in the nose-finger test and the wide-based walking with large oscillation in the gait task), which is out of the scope of SARA. Our new system enables more accurate scoring of SARA and further provides additional information that is not currently evaluated with SARA. Therefore, it provides an easier, more accurate and more systematic description of CAs.

Coordination of human movements resulting in motor strategies exploited by skilled players during a throwing task.

In this study, we investigated the underlying mechanisms of a motor system that affects skills and strategies of expert dart throwers. Eight experts participated in our experiment and each subject performed 42 throws. Kinematics of the shoulder, elbow, wrist, and dart were recorded by six high-speed cameras (200 Hz). The vertical error curve over time was calculated based on both hand and dart trajectories to clarify their relationship and interaction, which could attribute to their skills. Moreover, the kinematics of the dart (speed and direction) and angular kinematics of the elbow and wrist at the time of release were investigated to elucidate which parameters constitute the throwing strategies of experts. Experimental results showed that expert's throwing can be classified into two strategies, i.e., reducing timing sensitivity and reducing timing error. These strategies were derived from the spatial and temporal controls of the hand trajectory. Moreover, we confirmed that the speed of the dart and angular acceleration of the wrist joint at the time of release were highly correlated with the time-window for successful release. These results imply that the two strategies are characterized not only by a spatiotemporal relationship between the hand and dart trajectories, but also by relationships with release kinematic parameters of the proximal joint and the dart. Understanding characteristics which lead to strategies of skilled throwers would provide effective training methodology for beginners.

On-Body Sensor Positions Hierarchical Classification.

Many motion sensor-based applications have been developed in recent years because they provide useful information about daily activities and current health status of users. However, most of these applications require knowledge of sensor positions. Therefore, this research focused on the problem of detecting sensor positions. We collected standing-still and walking sensor data at various body positions from ten subjects. The offset values were removed by subtracting the sensor data of standing-still phase from the walking data for each axis of each sensor unit. Our hierarchical classification technique is based on optimizing local classifiers. Many common features are computed, and informative features are selected for specific classifications. In this approach, local classifiers such as arm-side and hand-side discriminations yielded F1-scores of 0.99 and 1.00, correspondingly. Overall, the proposed method achieved an F1-score of 0.81 and 0.84 using accelerometers and gyroscopes, respectively. Furthermore, we also discuss contributive features and parameter tuning in this analysis.

Muscle synergy analysis in dart throwing.

This study aims to analyze muscle synergies in darts throwing movement to clarify how the central nervous system (CNS) controls muscle activation to produce complicated motion. Activities of 10 different muscles on upper limb were recorded through surface electromyography (EMG) electrodes from four participants with less experience of dart throwing. Subsequently, non-negative matrix factorization (NNMF) was applied to the collected EMG signals for muscle synergy analysis. Results showed that three muscle synergies could explain sufficiently the observed EMG data, with determination coefficient r2 = 0.91 ± 0.02 across four subjects. However, it was found that there was significant difference in terms of patterns of both muscle synergies and activation coefficients between participants, which might reflect different neuromuscular control strategies in dart throwing.

Target-directed motor imagery of the lower limb enhances event-related desynchronization.

Event-related desynchronization/synchronization (ERD/S) is an electroencephalogram (EEG) feature widely used as control signals for Brain-Computer Interfaces (BCIs). Nevertheless, the underlying neural mechanisms and functions of ERD/S are largely unknown, thus investigating them is crucial to improve the reliability of ERD/S-based BCIs. This study aimed to identify Motor Imagery (MI) conditions that enhance ERD/S. We investigated following three questions: 1) whether target-directed MI affects ERD/S, 2) whether MI with sound imagery affects ERD/S, and 3) whether ERD/S has a body part dependency of MI. Nine participants took part in the experiments of four MI conditions; they were asked to imagine right foot dorsiflexion (F), right foot dorsiflexion and the sound of a bass drum when the sole touched the floor (FS), right leg extension (L), and right leg extension directed toward a soccer ball (LT). Statistical comparison revealed that there were significant differences between conditions L and LT in beta-band ERD and conditions F and L in beta-band ERS. These results suggest that mental rehearsal of target-directed lower limb movement without real sensory stimuli can enhance beta-band ERD; furthermore, MI of foot dorsiflexion induces significantly larger beta-band ERS than that of leg extension. These findings could be exploited for the training of BCIs such as powered prosthetics for disabled person and neurorehabilitation system for stroke patients.

Inclination of standing posture due to the presentation of tilted view through an immersive head-mounted display.

[Purpose] The purpose of the present study is to clarify whether tilted scenery presented through an immersive head-mounted display (HMD) causes the inclination of standing posture. [Subjects and Methods] Eleven healthy young adult males who provided informed consent participated in the experiment. An immersive HMD and a stereo camera were employed to develop a visual inclination system. The subjects maintained a standing posture twice for 5s each while wearing the visual inclination system. They performed this task under two conditions: normal view and 20° leftward tilted view. A three-dimensional motion analysis system was used to measure the subjects' postures, and two force plates were used to measure the vertical component of the floor reaction force of each leg. [Results] In the 20° leftward tilted view, the head and trunk angles in the frontal plane were similarly inclined toward the left, and the vertical component of the floor reaction force increased in the left leg, whereas it decreased in the right leg. [Conclusion] When the view in the immersive HMD was tilted, the participants' trunk side bent toward the same side as that of the view. This visual inclination system seems to be a simple intervention for changing standing posture.

Functional Connectivity Analysis of NIRS Data under Rubber Hand Illusion to Find a Biomarker of Sense of Ownership.

The self-identification, which is called sense of ownership, has been researched through methodology of rubber hand illusion (RHI) because of its simple setup. Although studies with neuroimaging technique, such as fMRI, revealed that several brain areas are associated with the sense of ownership, near-infrared spectroscopy (NIRS) has not yet been utilized. Here we introduced an automated setup to induce RHI, measured the brain activity during the RHI with NIRS, and analyzed the functional connectivity so as to understand dynamical brain relationship regarding the sense of ownership. The connectivity was evaluated by multivariate Granger causality. In this experiment, the peaks of oxy-Hb on right frontal and right motor related areas during the illusion were significantly higher compared with those during the nonillusion. Furthermore, by analyzing the NIRS recordings, we found a reliable connectivity from the frontal to the motor related areas during the illusion. This finding suggests that frontal cortex and motor related areas communicate with each other when the sense of ownership is induced. The result suggests that the sense of ownership is related to neural mechanism underlying human motor control, and it would be determining whether motor learning (i.e., neural plasticity) will occur. Thus RHI with the functional connectivity analysis will become an appropriate biomarker for neurorehabilitation.

Slow dynamics perspectives on the Embodied-Brain Systems Science.

Recent researches point out the importance of the fast-slow cognitive process and learning process of self-body. Bayesian perspectives on the cognitive system also attract research attentions. The view of fast-slow dynamical system has long attracted wide range of attentions from physics to the neurobiology. In many research fields, there is a vast well-organized and coherent behavior in the multi degrees-of-freedom. This behavior matches the mathematical fact that fast-slow system is essentially described with a few variables. In this paper, we review the mathematical basis for understanding the fast-slow dynamical systems. Additionally, we review the basis of Bayesian statistics and provide a fast-slow perspective on the Bayesian inference.

Pitchfork bifurcation in a receptor theory-based model of the serotonergic system.

Abnormalities in the serotonergic system are thought to be a potent cause of several mental diseases. Past research has shown that autoreceptors are the key component. It is thought that the autoreceptor constructs a negative feedback circuit on this system and realizes homeostatic control on its neural activity. This study is mainly organized from the above mentioned knowledge. In this paper, we construct two possible models of the serotonergic system based on receptor theory and provide some predictions for this system with each model. In the first model, we predict that the deficit of serotonin synthesis causes destabilization of the amount of autoreceptors; autoreceptors show an explosive increase if serotonin synthesis drops below a certain threshold value. In the second model, we indicate that the serotonergic system changes its stable property from a monostable one to a bistable one by certain factors. We clarify these factors and show that this changing process is named pitch-fork bifurcation. Additionally, we also suggest another notable phenomena which would appear when we consider a stochastic perturbation on the receptor expressions. Lastly, we suggest some experimental ideas towards the verification of the validity of these models.