Functional connectivity via the dorsolateral prefrontal cortex in the late phase of rest periods predicts offline learning.

The relationship between offline learning gains and functional connectivity (FC) has been investigated in several studies. They have focused on average motor task performance and resting-state FC across subjects. Generally, individual differences are seen in both offline learning gain and neurophysiological profiles in resting-state FC. However, few studies have focused on the relationship between individual differences in offline learning gain and temporal characteristics of resting-state FC. The present study aimed to clarify this relationship between the two profiles. Thirty-four healthy right-handed participants performed a force-controlled motor task. Electroencephalography was performed during the 15-minute wakeful rest period between tasks. The results revealed a significant correlation between offline learning gain and FC between the contralateral dorsolateral prefrontal cortex (DLPFC) and contralateral primary motor cortex (M1), and ipsilateral primary somatosensory cortex (S1) during late phase of the rest interval. These results are consistent with the findings of previous studies showing the FC between M1, which is necessary for awake offline learning, and DLPFC, which is related to motor control. Additionally, sensory feedback related to force control may be caused by the interaction between contralateral DLPFC and ipsilateral S1. Our study shed light on the temporal profiles of resting-state FC associated with individual differences in offline learning.

Analysis of Contact Force and Shape Change on Grasping a Square Object Using an Actual Fin Ray Soft Gripper.

The Fin Ray-type soft gripper (FRSG) is a typical soft gripper structure and applies the deformation characteristics of the Fin Ray structure. This structure functions to stabilize the grasping of an object by passive deformation due to external forces. To analyze the performance of detailed force without compromising the actual FRSG characteristics, it is effective to incorporate multiple force sensors into the grasping object without installing them inside the Fin Ray structure. Since the grasping characteristics of the FRSG are greatly affected by the arrangement of the crossbeams, it is also important to understand the correspondence between the forces and the geometry. In addition, the grasping characteristics of an angular object have not been verified in actual equipment. Therefore, in this study, a contact force measurement device with 16 force sensors built into the grasping object and a structural deformation measurement device using camera images were used to analyze the correspondence between force and structural deformation on an actual FRSG. In the experiment, we analyzed the influence of the crossbeam arrangement on the grasping force and the grasping conditions of the square (0°) and rectangular (45°) shapes, and state that an ideal grasp in a square-shaped (45°) grasp is possible if each crossbeam in the FRSG is arranged at a different angle.

Object Grasp Control of a 3D Robot Arm by Combining EOG Gaze Estimation and Camera-Based Object Recognition.

The purpose of this paper is to quickly and stably achieve grasping objects with a 3D robot arm controlled by electrooculography (EOG) signals. A EOG signal is a biological signal generated when the eyeballs move, leading to gaze estimation. In conventional research, gaze estimation has been used to control a 3D robot arm for welfare purposes. However, it is known that the EOG signal loses some of the eye movement information when it travels through the skin, resulting in errors in EOG gaze estimation. Thus, EOG gaze estimation is difficult to point out the object accurately, and the object may not be appropriately grasped. Therefore, developing a methodology to compensate, for the lost information and increase spatial accuracy is important. This paper aims to realize highly accurate object grasping with a robot arm by combining EMG gaze estimation and the object recognition of camera image processing. The system consists of a robot arm, top and side cameras, a display showing the camera images, and an EOG measurement analyzer. The user manipulates the robot arm through the camera images, which can be switched, and the EOG gaze estimation can specify the object. In the beginning, the user gazes at the screen's center position and then moves their eyes to gaze at the object to be grasped. After that, the proposed system recognizes the object in the camera image via image processing and grasps it using the object centroid. The object selection is based on the object centroid closest to the estimated gaze position within a certain distance (threshold), thus enabling highly accurate object grasping. The observed size of the object on the screen can differ depending on the camera installation and the screen display state. Therefore, it is crucial to set the distance threshold from the object centroid for object selection. The first experiment is conducted to clarify the distance error of the EOG gaze estimation in the proposed system configuration. As a result, it is confirmed that the range of the distance error is 1.8-3.0 cm. The second experiment is conducted to evaluate the performance of the object grasping by setting two thresholds from the first experimental results: the medium distance error value of 2 cm and the maximum distance error value of 3 cm. As a result, it is found that the grasping speed of the 3 cm threshold is 27% faster than that of the 2 cm threshold due to more stable object selection.

Involvement of the Rostromedial Prefrontal Cortex in Human-Robot Interaction: fNIRS Evidence From a Robot-Assisted Motor Task.

Assistive exoskeleton robots are being widely applied in neurorehabilitation to improve upper-limb motor and somatosensory functions. During robot-assisted exercises, the central nervous system appears to highly attend to external information-processing (IP) to efficiently interact with robotic assistance. However, the neural mechanisms underlying this process remain unclear. The rostromedial prefrontal cortex (rmPFC) may be the core of the executive resource allocation that generates biases in the allocation of processing resources toward an external IP according to current behavioral demands. Here, we used functional near-infrared spectroscopy to investigate the cortical activation associated with executive resource allocation during a robot-assisted motor task. During data acquisition, participants performed a right-arm motor task using elbow flexion-extension movements in three different loading conditions: robotic assistive loading (ROB), resistive loading (RES), and non-loading (NON). Participants were asked to strive for kinematic consistency in their movements. A one-way repeated measures analysis of variance and general linear model-based methods were employed to examine task-related activity. We demonstrated that hemodynamic responses in the ventral and dorsal rmPFC were higher during ROB than during NON. Moreover, greater hemodynamic responses in the ventral rmPFC were observed during ROB than during RES. Increased activation in ventral and dorsal rmPFC subregions may be involved in the executive resource allocation that prioritizes external IP during human-robot interactions. In conclusion, these findings provide novel insights regarding the involvement of executive control during a robot-assisted motor task.

Intranuclear mesoscale viscoelastic changes during osteoblastic differentiation of human mesenchymal stem cells.

Cell nuclei behave as viscoelastic materials. Dynamic regulation of the viscoelastic properties of nuclei in living cells is crucial for diverse biological and biophysical processes, specifically for intranuclear mesoscale viscoelasticity, through modulation of the efficiency of force propagation to the nucleoplasm and gene expression patterns. However, how the intranuclear mesoscale viscoelasticity of stem cells changes with differentiation is unclear and so is its biological significance. Here, we quantified the changes in intranuclear mesoscale viscoelasticity during osteoblastic differentiation of human mesenchymal stem cells. This analysis revealed that the intranuclear region is a viscoelastic solid, probably with a higher efficiency of force transmission that results in high sensitivity to mechanical signals in the early stages of osteoblastic differentiation. The intranuclear region was noted to alter to a viscoelastic liquid with a lower efficiency, which is responsible for the robustness of gene expression toward terminal differentiation. Additionally, evaluation of changes in the mesoscale viscoelasticity due to chromatin decondensation and correlation between the mesoscale viscoelasticity and local DNA density suggested that size of gap and flexibility of chromatin meshwork structures, which are modulated depending on chromatin condensation state, determine mesoscale viscoelasticity, with various rates of contribution in different differentiation stages. Given that chromatin within the nucleus condenses into heterochromatin as stem cells adopt a specific lineage by restricting transcription, viscoelasticity is perhaps a key factor in cooperative regulation of the nuclear mechanosensitivity and gene expression pattern for stem cell differentiation.

Modulation of sensorimotor cortical oscillations in athletes with yips.

The yips, an involuntary movement impediment that affects performance in skilled athletes, is commonly described as a form of task-specific focal dystonia or as a disorder lying on a continuum with focal dystonia at one end (neurological) and chocking under pressure at the other (psychological). However, its etiology has been remained to be elucidated. In order to understand sensorimotor cortical activity associated with this movement disorder, we examined electroencephalographic oscillations over the bilateral sensorimotor areas during a precision force task in athletes with yips, and compared them with age-, sex-, and years of experience-matched controls. Alpha-band event-related desynchronization (ERD), that occurs during movement execution, was greater in athlete with yips as compared to controls when increasing force output to match a target but not when adjusting the force at around the target. Event-related synchronization that occurs after movement termination was also greater in athletes with yips. There was no significant difference in task performance between groups. The enhanced ERD is suggested to be attributed to dysfunction of inhibitory system or increased allocation of attention to the body part used during the task. Our findings indicate that sensorimotor cortical oscillatory response is increased during movement initiation in athletes with yips.

Region-specific brain area reductions and increased cholecystokinin positive neurons in diabetic OLETF rats: implication for anxiety-like behavior.

Metabolic disorders can induce psychiatric comorbidities. Both brain and neuronal composition imbalances reportedly induce an anxiety-like phenotype. We hypothesized that alterations of localized brain areas and cholecystokinin (CCK) and parvalbumin (PV) expression could induce anxiety-like behavior in type 2 diabetic Otsuka Long-Evans Tokushima fatty (OLETF) rats. Twenty-week-old OLETF and non-diabetic Long-Evans Tokushima Otsuka (LETO) rats were used. The areas of corticolimbic regions were smaller in OLETF rats. The densities of CCK positive neurons in the lateral and basolateral amygdala, hippocampal cornu ammonis area 2, and prelimbic cortex were higher in OLETF rats. The densities of PV positive neurons were comparable between OLETF and LETO rats. Locomotion in the center zone in the open field test was lower in OLETF rats. These results suggest that imbalances of specific brain region areas and neuronal compositions in emotion-related areas increase the prevalence of anxiety-like behaviors in OLETF rats.

Role of beta-band resting-state functional connectivity as a predictor of motor learning ability.

It has been suggested that resting-state functional connectivity (rs-FC) between the primary motor area (M1) region of the brain and other brain regions may be a predictor of motor learning, although this suggestion is still controversial. In the work reported here, we investigated the relationship between M1 seed-based rs-FC and motor learning. Fifty-three healthy volunteers undertook random button-press and sequential motor learning tasks. Five-minute resting-state data acquisition was performed between the two tasks. Oscillatory neural activities during the random task and the rest period were measured using magnetoencephalography. M1 seed-based rs-FC was calculated for the alpha and beta bands using amplitude envelope correlation, in which the seed location was defined as an M1 position with peak event-related desynchronization value. The relationship between rs-FC and the performance of motor learning was examined using whole brain correlation analysis. The results showed that beta-band resting-state cross-network connectivity between the sensorimotor network and the core network, particularly the theory of mind network, affected the performance of subsequent motor learning tasks. Good learners could be distinguished from poor learners by the strength of rs-FC between the M1 and the left superior temporal gyrus, a part of the theory of mind network. These results suggest that cross-network connectivity between the sensorimotor network and the theory of mind network can be used as a predictor of motor learning performance.

Off-line effects of alpha-frequency transcranial alternating current stimulation on a visuomotor learning task.

INTRODUCTION: It has been suggested that transcranial alternating current stimulation (tACS) at both alpha and beta frequencies promotes motor function as well as motor learning. However, limited information exists on the aftereffects of tACS on motor learning and neurophysiological profiles such as entrainment and neural plasticity in parallel. Therefore, in the present study, we examined the effect of tACS on motor learning and neurophysiological profiles using an off-line tACS condition. METHODS: Thirty-three healthy participants were randomly assigned to 10 Hz, 20 Hz, or the sham group. Participants performed visuomotor learning tasks consisting of a baseline task (preadaptation task) and training task (adaptation task) to reach a target with a lever-type controller. Electroencephalography was recorded from eight locations during the learning tasks. tACS was performed between the preadaptation task and adaptation task over the left primary motor cortex for 10 min at 1 mA. RESULTS: As a result, 10 Hz tACS was shown to be effective for initial angular error correction in the visuomotor learning tasks. However, there were no significant differences in neural oscillatory activities among the three groups. CONCLUSION: These results suggest that initial motor learning can be facilitated even when 10 Hz tACS is applied under off-line conditions. However, neurophysiological aftereffects were recently demonstrated to be induced by tACS at individual alpha frequencies rather than fixed alpha tACS, which suggests that the neurophysiological aftereffects by fixed frequency stimulation in the present study may have been insufficient to generate changes in oscillatory neural activity.

24-Gaze-Point Calibration Method for Improving the Precision of AC-EOG Gaze Estimation.

This paper sought to improve the precision of the Alternating Current Electro-Occulo-Graphy (AC-EOG) gaze estimation method. The method consisted of two core techniques: To estimate eyeball movement from EOG signals and to convert signals from the eyeball movement to the gaze position. In conventional research, the estimations are computed with two EOG signals corresponding to vertical and horizontal movements. The conversion is based on the affine transformation and those parameters are computed with 24-point gazing data at the calibration. However, the transformation is not applied to all the 24-point gazing data, but to four spatially separated data (Quadrant method), and each result has different characteristics. Thus, we proposed the conversion method for 24-point gazing data at the same time: To assume an imaginary center (i.e., 25th point) on gaze coordinates with 24-point gazing data and apply an affine transformation to 24-point gazing data. Then, we conducted a comparative investigation between the conventional method and the proposed method. From the results, the average eye angle error for the cross-shaped electrode attachment is x = 2.27 ° ± 0.46 ° and y = 1.83 ° ± 0.34 ° . In contrast, for the plus-shaped electrode attachment, the average eye angle error is is x = 0.94 ° ± 0.19 ° and y = 1.48 ° ± 0.27 ° . We concluded that the proposed method offers a simpler and more precise EOG gaze estimation than the conventional method.

Effect of individual food preferences on oscillatory brain activity.

OBJECTIVES: During the anticipatory stage of swallowing, sensory stimuli related to food play an important role in the behavioral and neurophysiological aspects of swallowing. However, few studies have focused on the relationship between food preferences and oscillatory brain activity during the anticipatory stage of swallowing. Therefore, to clarify the effect of individual food preferences on oscillatory brain activity, we investigated the relationship between food preferences and oscillatory brain activity during the observation of food images. METHODS: Here we examined this relationship using visual food stimuli and electroencephalography (EEG). Nineteen healthy participants were presented 150 images of food in a random order and asked to rate their subjective preference for that food on a 4-point scale ranging from 1 (don't want to eat) to 4 (want to eat). Oscillation analysis was performed using a Hilbert transformation for bandpass-filtered EEG signals. RESULTS: The results showed that the oscillatory beta band power on C3 significantly decreased in response to favorite foods compared to disliked food. CONCLUSION: This result suggests that food preferences may impact oscillatory brain activity related to swallowing during the anticipatory stage of swallowing. This finding may lead to the development of new swallowing rehabilitation techniques for patients with dysphagia by applying food preferences to modulate oscillatory brain activity.

Modulation of Motor Learning Capacity by Transcranial Alternating Current Stimulation.

Motor function can be modulated by transcranial alternating current stimulation (tACS) in alpha, beta, and high-gamma frequencies. However, few studies have investigated tACS-induced behavioral changes in combination with endogenous oscillatory neural activity in detail. Herein, we investigated the effect of tACS on motor learning capacity and endogenous oscillatory neural activity. Fifty-two healthy volunteers were randomly assigned to four stimulation groups (10 Hz, 20 Hz, 70 Hz, or sham) and performed a visually cued button press motor learning task before and after tACS, which was delivered at the left primary motor area. Oscillatory neural activities during the motor learning task were measured using magnetoencephalography (MEG). Following tACS, the capacity for motor learning was significantly increased for 70 Hz tACS compared to sham stimulation. Oscillation analysis revealed a significant increase in beta-band power after 70-Hz tACS but not in the other stimulation groups. Our finding that capacity for motor learning and endogenous oscillatory beta activity were modulated in parallel after 70-Hz tACS suggests that 70-Hz tACS may increase the motor learning capacity by cross-modulating beta oscillatory activity. Because high gamma and beta oscillatory activity have been shown to reflect the activity of excitatory and inhibitory interneuron, our results may derive from the modulation of excitatory and inhibitory interneurons in M1 by 70-Hz tACS.

A Fully Implantable Wireless ECoG 128-Channel Recording Device for Human Brain-Machine Interfaces: W-HERBS.

Brain-machine interfaces (BMIs) are promising devices that can be used as neuroprostheses by severely disabled individuals. Brain surface electroencephalograms (electrocorticograms, ECoGs) can provide input signals that can then be decoded to enable communication with others and to control intelligent prostheses and home electronics. However, conventional systems use wired ECoG recordings. Therefore, the development of wireless systems for clinical ECoG BMIs is a major goal in the field. We developed a fully implantable ECoG signal recording device for human ECoG BMI, i.e., a wireless human ECoG-based real-time BMI system (W-HERBS). In this system, three-dimensional (3D) high-density subdural multiple electrodes are fitted to the brain surface and ECoG measurement units record 128-channel (ch) ECoG signals at a sampling rate of 1 kHz. The units transfer data to the data and power management unit implanted subcutaneously in the abdomen through a subcutaneous stretchable spiral cable. The data and power management unit then communicates with a workstation outside the body and wirelessly receives 400 mW of power from an external wireless transmitter. The workstation records and analyzes the received data in the frequency domain and controls external devices based on analyses. We investigated the performance of the proposed system. We were able to use W-HERBS to detect sine waves with a 4.8-µV amplitude and a 60-200-Hz bandwidth from the ECoG BMIs. W-HERBS is the first fully implantable ECoG-based BMI system with more than 100 ch. It is capable of recording 128-ch subdural ECoG signals with sufficient input-referred noise (3 µVrms) and with an acceptable time delay (250 ms). The system contributes to the clinical application of high-performance BMIs and to experimental brain research.

Subthalamic nucleus detects unnatural android movement.

An android, i.e., a realistic humanoid robot with human-like capabilities, may induce an uncanny feeling in human observers. The uncanny feeling about an android has two main causes: its appearance and movement. The uncanny feeling about an android increases when its appearance is almost human-like but its movement is not fully natural or comparable to human movement. Even if an android has human-like flexible joints, its slightly jerky movements cause a human observer to detect subtle unnaturalness in them. However, the neural mechanism underlying the detection of unnatural movements remains unclear. We conducted an fMRI experiment to compare the observation of an android and the observation of a human on which the android is modelled, and we found differences in the activation pattern of the brain regions that are responsible for the production of smooth and natural movement. More specifically, we found that the visual observation of the android, compared with that of the human model, caused greater activation in the subthalamic nucleus (STN). When the android's slightly jerky movements are visually observed, the STN detects their subtle unnaturalness. This finding suggests that the detection of unnatural movements is attributed to an error signal resulting from a mismatch between a visual input and an internal model for smooth movement.

Gravity Compensation and Feedback of Ground Reaction Forces for Biped Balance Control.

This paper considers the balance control of a biped robot under a constant external force or on a sloped ground. We have proposed a control method with feedback of the ground reaction forces and have realized adaptive posture changes that ensure the stability of the robot. However, fast responses have not been obtained because effective control is achieved by an integral feedback that accompanies a time delay necessary for error accumulation. To improve this response, here, we introduce gravity compensation in a feedforward manner. The stationary state and its stability are analyzed based on dynamic equations, and the robustness as well as the response is evaluated using computer simulations. Finally, the adaptive behaviors of the robot are confirmed by standing experiments on the slope.

Common neural correlates of real and imagined movements contributing to the performance of brain-machine interfaces.

The relationship between M1 activity representing motor information in real and imagined movements have not been investigated with high spatiotemporal resolution using non-invasive measurements. We examined the similarities and differences in M1 activity during real and imagined movements. Ten subjects performed or imagined three types of right upper limb movements. To infer the movement type, we used 40 virtual channels in the M1 contralateral to the movement side (cM1) using a beamforming approach. For both real and imagined movements, cM1 activities increased around response onset, after which their intensities were significantly different. Similarly, although decoding accuracies surpassed the chance level in both real and imagined movements, these were significantly different after the onset. Single virtual channel-based analysis showed that decoding accuracy significantly increased around the hand and arm areas during real and imagined movements and that these are spatially correlated. The temporal correlation of decoding accuracy significantly increased around the hand and arm areas, except for the period immediately after response onset. Our results suggest that cM1 is involved in similar neural activities related to the representation of motor information during real and imagined movements, except for presence or absence of sensory-motor integration induced by sensory feedback.

Patient-specific cortical electrodes for sulcal and gyral implantation.

PURPOSE: Noninvasive localization of certain brain functions may be mapped on a millimetre level. However, the interelectrode spacing of common clinical brain surface electrodes still remains around 10 mm. Here, we present details on development of electrodes for attaining higher quality electrocorticographic signals for use in functional brain mapping and brain-machine interface (BMI) technologies. METHODS: We used platinum-plate-electrodes of 1-mm diameter to produce sheet electrodes after the creation of individualized molds using a 3-D printer and a press system that sandwiched the electrodes between personalized silicone sheets. RESULTS: We created arrays to fit the surface curvature of the brain and inside the central sulcus, with interelectrode distances of 2.5 mm (a density of 16 times previous standard types). Rat experiments undertaken indicated no long term toxicity. We were also able to custom design, rapidly manufacture, safely implant, and confirm the efficacy of personalized electrodes, including the capability to attain meaningful high-gamma-band information in an amyotrophic lateral sclerosis patient. CONCLUSION: We developed cortical sheet electrodes with a high-spatial resolution, tailor-made to match an individual's brain. SIGNIFICANCE: This sheet electrode may contribute to the higher performance of BMI's.

Alpha band functional connectivity correlates with the performance of brain-machine interfaces to decode real and imagined movements.

Brain signals recorded from the primary motor cortex (M1) are known to serve a significant role in coding the information brain-machine interfaces (BMIs) need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to the performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beam forming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.

Patient-specific contour-fitting sheet electrodes for electrocorticographic brain machine interfaces.

Non-invasive localization of certain brain functions may be mapped on a millimeter level. However, the inter-electrode spacing of common clinical brain surface electrodes still remains around 10 mm, and some electrodes fail to measure cortical activity due to unconformable plain electrode sheets. Here, we present details on development of implantable electrodes for attaining higher quality electrocorticographic signals for use in functional brain mapping and brain-machine interfaces. We produced personalized sheet electrodes after the creation of individualized molds using a 3D-printer. We created arrays to fit the surface curvature of the brain and inside the central sulcus, with inter-electrode distances of 2.5 mm. Rat experiments undertaken indicated no long term toxicity. We were also able to custom design, rapidly manufacture, safely implant and confirm the efficacy of personalized electrodes, including the capability to attain meaningful high gamma-band information in an amyotrophic lateral sclerosis patient. This sheet electrode may contribute to the higher performance of BMI's.

Super multi-channel recording systems with UWB wireless transmitter for BMI.

In order to realize a low-invasive and high accuracy Brain-Machine Interface (BMI) system for clinical applications, a super multi-channel recording system was developed in which 4096 channels of Electrocorticogram (ECoG) signal can be amplified and transmitted to outside the body by using an Ultra Wide Band (UWB) wireless system. Also, a high density, flexible electrode array made by using a Parylene-C substrate was developed that is composed of units of 32-ch recording arrays. We have succeeded in an evaluation test of UWB wireless transmitting using a body phantom system.