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Abstract Hand choice is an unconscious decision frequently made in daily life. The electroencephalogram before target presentation correlates with hand choice for the target where hand choice probability reaches equilibrium. However, whether neurophysiological interventions before target presentation influence hand choice remains unknown. Therefore, this study determined whether instantaneous somatosensory electrical stimulation administered to the unilateral wrist at 0, 300, or 600 ms before the target presentation facilitates or inhibits stimulated hand choice for targets around the hand selection equilibrium point. A single electrical stimulation comprised five trains of 1 ms electrical pulses, with a 20 ms inter-pulse interval. The stimulus intensity was set at 80% of the motor threshold. This study included 14 right-handed healthy adults (five females and nine males; mean age, 25.1 ± 4.64 years). Unilateral wrist stimulation significantly increased the probability of choosing the stimulated hand and led to a faster reaction time than bilateral wrist stimulation and no-stimulation conditions. The results suggest that prior somatosensory stimulation significantly affects the hand-choice process, effectively promoting the selection of the stimulated hand. These findings highlight the potential application of this stimulation method in stroke rehabilitation to facilitate the use of the paretic hand.

Objective: To clarify the time-course of longitudinal changes in the independence level of subtasks composing bed–wheelchair transfer among patients with stroke. Design: Single-institution prospective cohort study. Patients: A total of 137 consecutive post-stroke patients using wheelchair on admission to the subacute rehabilitation wards. Methods: The independence degree in each of the 25 transfer-related subtasks was assessed using the Bed–Wheelchair Transfer Tasks Assessment Form on a three-level scale every two weeks, from admission to the endpoint (either discharge or when achieving independent transfer). Patients were classified based on admission and endpoint assessment form scores using two-step cluster analysis. Results: Patients were classified into three clusters. The first cluster included 50 patients who exhibited a greater independence level in all subtasks on admission (52.0–100% of patients performed each subtask independently) and at the endpoint (64.0–100%). The second included 30 patients who showed less independence on admission (0–27.8%) but achieved greater independence levels at the endpoint (44.4–97.2%). The third included 51 patients whose independence level remained low in many subtasks from admission (0–5.8%) until the endpoint (0–29.4%). Conclusion: The independence level and its changing process during transfer were categorized into three time-courses, each requiring different intervention strategies.

Abstract The strategies for social interaction between strangers differ from those between acquaintances, whereas the differences in neural basis of social interaction have not been fully elucidated. In this study, we examined the geometrical properties of interpersonal neural networks in pairs of strangers and acquaintances during antiphase joint tapping. Dual electroencephalogram (EEG) of 29 channels per participant was measured from 14 strangers and 13 acquaintance pairs.Intra-brain synchronizations were calculated using the weighted phase lag index (wPLI) for intra-brain electrode combinations, and inter-brain synchronizations were calculated using the phase locking value (PLV) for inter-brain electrode combinations in the theta, alpha, and beta frequency bands. For each participant pair, electrode combinations with larger wPLI/PLV than their surrogates were defined as the edges of the neural networks. We calculated global efficiency, local efficiency, and modularity derived from graph theory for the combined intra- and inter-brain networks of each pair. In the theta band networks, stranger pairs showed larger local efficiency than acquaintance pairs, indicating that the two brains of stranger pairs were more densely connected. Hence, weak social ties require extensive social interactions and result in high efficiency of information transfer between neighbors in neural network.

IntroductionThe conventional method of placing transcranial direct current stimulation (tDCS) electrodes is just above the target brain area. However, this strategy for electrode placement often fails to improve motor function and modulate cortical excitability. We investigated the effects of optimized electrode placement to induce maximum electrical fields in the leg regions of both M1 and SMA, estimated by electric field simulations in the T1and T2-weighted MRI-based anatomical models, on motor performance and cortical excitability in healthy individuals.MethodsA total of 36 healthy volunteers participated in this randomized, triple-blind, sham-controlled experiment. They were stratified by sex and were randomly assigned to one of three groups according to the stimulation paradigm, including tDCS with (1) anodal and cathodal electrodes positioned over FCz and POz, respectively, (A-P tDCS), (2) anodal and cathodal electrodes positioned over POz and FCz, respectively, (P-A tDCS), and (3) sham tDCS. The sit-to-stand training following tDCS (2 mA, 10 min) was conducted every 3 or 4 days over 3 weeks (5 sessions total).ResultsCompared to sham tDCS, A-P tDCS led to significant increases in the number of sit-to-stands after 3 weeks training, whereas P-A tDCS significantly increased knee flexor peak torques after 3 weeks training, and decreased short-interval intracortical inhibition (SICI) immediately after the first session of training and maintained it post-training.DiscussionThese results suggest that optimized electrode placement of the maximal EF estimated by electric field simulation enhances motor performance and modulates cortical excitability depending on the direction of current flow.

Abstract Evaluating reciprocal inhibition of the thigh muscles is important to investigate the neural circuits of locomotor behaviors. However, measurements of reciprocal inhibition of thigh muscles using spinal reflex, such as H‐reflex, have never been systematically established owing to methodological limitations. The present study aimed to clarify the existence of reciprocal inhibition in the thigh muscles using transcutaneous spinal cord stimulation (tSCS). Twenty able‐bodied male individuals were enrolled. We evoked spinal reflex from the biceps femoris muscle (BF) by tSCS on the lumber posterior root. We examined whether the tSCS‐evoked BF reflex was reciprocally inhibited by the following conditionings: (1) single‐pulse electrical stimulation on the femoral nerve innervating the rectus femoris muscle (RF) at various inter‐stimulus intervals in the resting condition; (2) voluntary contraction of the RF; and (3) vibration stimulus on the RF. The BF reflex was significantly inhibited when the conditioning electrical stimulation was delivered at 10 and 20 ms prior to tSCS, during voluntary contraction of the RF, and during vibration on the RF. These data suggested a piece of evidence of the existence of reciprocal inhibition from the RF to the BF muscle in humans and highlighted the utility of methods for evaluating reciprocal inhibition of the thigh muscles using tSCS.

Previous studies suggested that self-focused attention (SFA), implicated in social anxiety disorder (SAD), correlates with heightened activity in the right frontopolar area (rFPA), which is the right prefrontal cortex just behind the forehead. Transcranial static magnetic field stimulation (tSMS) is a non-invasive brain stimulation method capable of temporarily suppressing brain function beneath the magnet. We explored whether tSMS on individuals with tendencies toward SAD elicited (1) suppressing rFPA activation during the resting-state and (2) reducing SFA during a subsequent speech task. Twenty-three university students with social anxiety performed two speech tasks. Between tasks, the tSMS group received neodymium magnet stimulation while the sham group received fake magnet stimulation on the rFPA for 20 min. Resting-state rFPA activities was measured using functional near-infrared spectroscopy (fNIRS), while SFA (body sensations and observer perspective), field perspective, and detached mindfulness (DM) perspective were assessed via questionnaires during both speech tasks. The observer perspective means SFA to self-imagery from others’ viewpoint, while the field and DM perspectives mean appropriately focusing on the external environment. The results indicated that tSMS intervention decreased rFPA activity from pre- to post-intervention rest. Then, tSMS reduced SFA to bodily sensations and increased DM perspective from pre- to post-intervention speech, especially in those with high levels of social anxiety. Furthermore, tSMS enhanced the field perspective regardless of social anxiety tendency. The results suggest that tSMS may suppress overactivity in rFPA, reduce SFA to body sensation, and increase adaptive attention in highly socially anxious individuals. Our study suggests the possibility of the clinical application of tSMS for treating SAD.

BackgroundThe motivation for rehabilitation is important in encouraging stroke patients to participate in rehabilitation; however, its relationship with outcomes is not well known. In addition, changes in patient motivation during hospitalization have not been examined.AimTo examine the relationship between motivation and rehabilitation outcomes for subacute stroke patients and to investigate the changes in motivation.DesignProspective cohort study.SettingSubacute rehabilitation hospital.PopulationThe study enrolled a consecutive sample of patients (n = 201) with stroke admitted to a subacute rehabilitation ward from October 2017 to March 2019.MethodsThe functional independence measure and motivation in stroke patients for rehabilitation scale was evaluated at admission; at one, two, and three months after admission; and at discharge. The effectiveness and efficiency of the functional independence measure were calculated as rehabilitation outcomes. The effect of motivation on outcomes and the change in motivation in stroke patients for rehabilitation scale scores over time were analyzed using a linear mixed model.ResultsThe median (interquartile range) converted motivation in stroke patients for rehabilitation scale scores (converted to a range of 0–100) at admission; one, two, and three months after admission; and discharge was 86 (76–95), 83 (77–94), 81 (74–95), 81 (71–93), and 84 (75–95), respectively. The median (interquartile range) of effectiveness and efficiency of the functional independence measure from admission to discharge was 0.82 (0.68–0.91) and 0.41 (0.30–0.59), respectively. Motivation in stroke patients for rehabilitation scale scores were not significantly associated with the effectiveness and efficiency of the functional independence measure (p > 0.05). Motivation in stroke patients for rehabilitation scale scores were significantly lower at two (β = −3.1, 95% confidence interval [−5.3, −0.9], p = 0.005) and three (β = −4.4, 95% confidence interval [−7.3, −1.6], p = 0.002) months after admission than at admission.ConclusionMotivation might not directly affect rehabilitation outcomes assessed by the functional independence measure. Furthermore, many participants remained highly motivated, although their motivation decreased at one or three months after admission.Clinical rehabilitation impactAssumptions that rehabilitation is ineffective because of low motivation may not be correct. To examine the influence on outcomes, both motivation and daily activities should be considered.

Abstract Inter-brain synchronization is enhanced when individuals perform rhythmic interpersonal coordination tasks, such as playing instruments in music ensembles. Experimentally, synchronization has been shown to correlate with the performance of joint tapping tasks. However, it is unclear whether inter-brain synchronization is related to the stability of interpersonal coordination represented as the standard deviation of relative phase (SDRP). In this study, we simultaneously recorded electroencephalograms of two paired individuals during anti-phase tapping in three interactive tapping conditions: slow (reference inter-tap interval [ITI]: 0.5 s), fast (reference ITI: 0.25 s), and free (preferred ITI), and pseudo tapping where each participant tapped according to the metronome sounds without interaction. We calculated the inter-brain synchronization between pairs of six regions of interest (ROI): frontal, central, left/right temporal, parietal, and occipital regions. During the fast tapping, the inter-brain synchronization significantly increased in multiple ROI pairs including temporoparietal junction in comparison to pseudo tapping. Synchronization between the central and left-temporal regions was positively correlated with SDRP in the theta in the fast condition. These results demonstrate that inter-brain synchronization occurs when task requirements are high and increases with the instability of the coordination.

Abstract Hand choices—deciding which hand to use to reach for targets—represent continuous, daily, unconscious decisions. The posterior parietal cortex (PPC) contralateral to the selected hand is activated during a hand-choice task, and disruption of left PPC activity with a single-pulse transcranial magnetic stimulation prior to the execution of the motion suppresses the choice to use the right hand but not vice versa. These findings imply the involvement of either bilateral or left PPC in hand choice. To determine whether the effects of PPC’s activity are essential and/or symmetrical in hand choice, we increased or decreased PPC excitability in 16 healthy participants using transcranial direct current stimulation (tDCS; 10 min, 2 mA, 5 × 7 cm) and examined its online and residual effects on hand-choice probability and reaction time. After the right PPC was stimulated with an anode and the left PPC with a cathode, the probability of left-hand choice significantly increased and reaction time significantly decreased. However, no significant changes were observed with the stimulation of the right PPC with a cathode and the left PPC with an anode. These findings, thus, reveal the asymmetry of PPC-mediated regulation in hand choice.

As humans, we constantly change our movement strategies to adapt to changes in physical functions and the external environment. We have to walk very slowly in situations with a high risk of falling, such as walking on slippery ice, carrying an overflowing cup of water, or muscle weakness owing to aging or motor deficit. However, previous studies have shown that a normal gait pattern at low speeds results in reduced efficiency and stability in comparison with those at a normal speed. Another possible strategy is to change the gait pattern from normal to step-to gait, in which the other foot is aligned with the first swing foot. However, the efficiency and stability of the step-to gait pattern at low speeds have not been investigated yet. Therefore, in this study, we compared the efficiency and stability of the normal and step-to gait patterns at intermediate, low, and very low speeds. Eleven healthy participants were asked to walk with a normal gait and step-to gait on a treadmill at five different speeds (i.e., 10, 20, 30, 40, and 60 m/min), ranging from very low to normal walking speed. The efficiency parameters (percent recovery and walk ratio) and stability parameters (center of mass lateral displacement) were analyzed from the motion capture data and then compared for the two gait patterns. The results suggested that step-to gait had a more efficient gait pattern at very low speeds of 10–30 m/min, with a larger percent recovery, and was more stable at 10–60 m/min in comparison with a normal gait. However, the efficiency of the normal gait was better than that of the step-to gait pattern at 60 m/min. Therefore, step-to gait is effective in improving gait efficiency and stability when faced with situations that force us to walk slowly or hinder quick walking because of muscle weakness owing to aging or motor deficit along with a high risk of falling.

Objective This study aimed to develop the Motivation in stroke patients for rehabilitation scale (MORE scale), following the Consensus-based standards for the selection of health measurement instruments (COSMIN). Method Study participants included rehabilitation professionals working at the convalescent rehabilitation hospital and stroke patients admitted to the hospital. The original MORE scale was developed from an item pool, which was created through discussions of nine rehabilitation professionals. After the content validity of the scale was verified using the Delphi method with 61 rehabilitation professionals and 22 stroke patients, the scale’s validity and reliability were examined for 201 stroke patients. The construct validity of the scale was investigated using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and item response theory analysis. Cronbach’s alpha confirmed its internal consistency. Regarding convergent, discriminant, and criterion validity, Spearman’s rho was calculated between the MORE scale and the Apathy Scale (AS), Self-rating Depression Scale (SDS), and Visual Analogue Scale (VAS), which rates the subjective feelings of motivation. Results Using the Delphi method, 17 items were incorporated into the MORE scale. According to EFA and CFA, a one-factor model was suggested. All MORE scale items demonstrated satisfactory item response, with item slopes ranging from 0.811 to 2.142, and item difficulty parameters ranging from -3.203 to 0.522. Cronbach’s alpha was 0.948. Regarding test-retest reliability, a moderate correlation was found between scores at the beginning and one month after hospitalization (rho = 0.612. p < 0.001). The MORE scale showed significant correlation with AS (rho = -0.536, p < 0.001), SDS (rho = -0.347, p < 0.001), and VAS (rho = 0.536, p < 0.001), confirming the convergent, discriminant, and criterion validity, respectively. Conclusions The MORE scale was verified as a valid and reliable scale for evaluating stroke patients’ motivation for rehabilitation.

This research investigated the difference in aspects of gaze control between esports experts (Expert) and players with lower skills (Low Skill) while playing the real-time strategy game called StarCraft. Three versions of this game at different difficulty levels were made with the StarCraft Editor, and the gaze movements of seven Expert and nine Low Skill players were analyzed while they played the games. The gaze of Expert players covered a significantly larger area in the horizontal direction than the gaze of Low Skill players. Furthermore, the magnitude and number of saccadic eye movements were greater, and saccade velocity was faster in the Expert than in the Low Skill players. In conclusion, StarCraft experts have a specific gaze control ability that enables them to quickly and widely take visual information from all over the monitor. This could be one of the factors enabling StarCraft experts to perform better than players with lower skills when playing games that require task-switching ability.

Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of 'internal model adaptation'. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.

To characterize each cognitive function per se and to understand the brain as an aggregate of those functions, it is vital to relate dozens of these functions to each other. Knowledge about the relationships among cognitive functions is informative not only for basic neuroscientific research but also for clinical applications and developments of brain-inspired artificial intelligence. In the present study, we propose an exhaustive data mining approach to reveal relationships among cognitive functions based on functional brain mapping and network analysis. We began our analysis with 109 pseudo-activation maps (cognitive function maps; CFM) that were reconstructed from a functional magnetic resonance imaging meta-analysis database, each of which corresponds to one of 109 cognitive functions such as ‘emotion,’ ‘attention,’ ‘episodic memory,’ etc. Based on the resting-state functional connectivity between the CFMs, we mapped the cognitive functions onto a two-dimensional space where the relevant functions were located close to each other, which provided a rough picture of the brain as an aggregate of cognitive functions. Then, we conducted so-called conceptual analysis of cognitive functions using clustering of voxels in each CFM connected to the other 108 CFMs with various strengths. As a result, a CFM for each cognitive function was subdivided into several parts, each of which is strongly associated with some CFMs for a subset of the other cognitive functions, which brought in sub-concepts (i.e., sub-functions) of the cognitive function. Moreover, we conducted network analysis for the network whose nodes were parcels derived from whole-brain parcellation based on the whole-brain voxel-to-CFM resting-state functional connectivities. Since each parcel is characterized by associations with the 109 cognitive functions, network analyses using them are expected to inform about relationships between cognitive and network characteristics. Indeed, we found that informational diversities of interaction between parcels and densities of local connectivity were dependent on the kinds of associated functions. In addition, we identified the homogeneous and inhomogeneous network communities about the associated functions. Altogether, we suggested the effectiveness of our approach in which we fused the large-scale meta-analysis of functional brain mapping with the methods of network neuroscience to investigate the relationships among cognitive functions.

In a conventional view of motor control, the human brain might employ an optimization principle that leads a stereotypical motor behavior which we observe as an averaged behavioral data over subjects. In this scenario, the inter-individual motor variability is considered as an observation noise. Here, we challenged this view. We considered a motor control task where the human participants manipulated arm force by coordinating shoulder and elbow torques and investigated the muscle-tuning function that represents how the brain distributed the ideal joint torques to multiple muscles. In the experimental data, we observed large inter-individual variability in the profile of a muscle-tuning function. This contradicts with a well-established optimization theory that is based on minimization of muscle energy consumption and minimization of motor variability. We then hypothesized the inter-subject differences in the structure of the motor cortical areas might be the source of the across-subjects variability of the motor behavior. This was supported by a voxel-based morphometry analysis of magnetic resonance imaging; The inter-individual variability of the muscle tuning profile was correlated with that of the gray matter volume in the premotor cortex which is ipsilateral to the used arm (i.e., right hemisphere for the right arm). This study suggests that motor individuality may originate from inter-individual variation in the cortical structure.

Efficient human motor control is characterized by an extensive use of joint impedance modulation, which is achieved by co-contracting antagonistic muscles in a way that is beneficial to the specific task. While there is much experimental evidence available that the nervous system employs such strategies, no generally-valid computational model of impedance control derived from first principles has been proposed so far. Here we develop a new impedance control model for antagonistic limb systems which is based on a minimization of uncertainties in the internal model predictions. In contrast to previously proposed models, our framework predicts a wide range of impedance control patterns, during stationary and adaptive tasks. This indicates that many well-known impedance control phenomena naturally emerge from the first principles of a stochastic optimization process that minimizes for internal model prediction uncertainties, along with energy and accuracy demands. The insights from this computational model could be used to interpret existing experimental impedance control data from the viewpoint of optimality or could even govern the design of future experiments based on principles of internal model uncertainty.