BACKGROUND: Residents in nursing homes are prone to cognitive decline affecting memory, visuospatial cognition, and executive functions. Cognitive decline can lead to dementia, necessitating prioritized intervention. METHODS: The current study aimed to investigate whether an intervention using a digital game was effective for preserving and improving the cognitive function of residents in nursing homes. An intervention study was conducted using a single-case AB design with multiple baselines. The participants in the study were five older adults aged 65 and over who do not play digital games regularly. The study ran for 15 weeks, including a baseline (phase A) and an intervention phase (phase B). Phase A had five baselines (5 to 9 weeks) with random participant assignment. In phase B, participants engaged in a digital game (Space Invaders) individually. Cognitive function was assessed as the outcome, measured using the Brain Assessment (performed on a tablet through the Internet) at 16 measurement points. Four of five participants (two female and two male) were included in the analysis, using visual inspection and Bayesian statistics with multi-level modeling. RESULTS: Visual inspection of the graphs revealed cognitive function score improvements after the intervention for most layers in terms of memory of numbers, memory of words, mental rotation test (visuospatial ability), and total scores in the Brain Assessment. These effects were also significant in the analysis by multi-level modeling. CONCLUSIONS: The results suggest that the use of digital games may be effective for preserving and improving cognitive function among residents of nursing home. TRIAL REGISTRATION: This study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000048677; public title: Effect of a Digital Game Intervention for Cognitive Functions in Older People; registration date: August 30, 2022).
Cognition , Cognitive Dysfunction , Nursing Homes , Video Games , Humans , Male , Female , Video Games/psychology , Aged , Aged, 80 and over , Cognition/physiology , Cognitive Dysfunction/therapy , Cognitive Dysfunction/psychology , Single-Case Studies as Topic , Homes for the Aged
Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hunting strategy requiring large brains that involve high-level cognition. However, recent findings that collaborative hunting has also been documented in smaller-brained vertebrates have placed this previous belief under strain. Here, using computational multi-agent simulations based on deep reinforcement learning, we demonstrate that decisions underlying collaborative hunts do not necessarily rely on sophisticated cognitive processes. We found that apparently elaborate coordination can be achieved through a relatively simple decision process of mapping between states and actions related to distance-dependent internal representations formed by prior experience. Furthermore, we confirmed that this decision rule of predators is robust against unknown prey controlled by humans. Our computational ecological results emphasize that collaborative hunting can emerge in various intra- and inter-specific interactions in nature, and provide insights into the evolution of sociality.
From wolves to ants, many animals are known to be able to hunt as a team. This strategy may yield several advantages: going after bigger preys together, for example, can often result in individuals spending less energy and accessing larger food portions than when hunting alone. However, it remains unclear whether this behavior relies on complex cognitive processes, such as the ability for an animal to represent and anticipate the actions of its teammates. It is often thought that 'collaborative hunting' may require such skills, as this form of group hunting involves animals taking on distinct, tightly coordinated roles as opposed to simply engaging in the same actions simultaneously. To better understand whether high-level cognitive skills are required for collaborative hunting, Tsutsui et al. used a type of artificial intelligence known as deep reinforcement learning. This allowed them to develop a computational model in which a small number of 'agents' had the opportunity to 'learn' whether and how to work together to catch a 'prey' under various conditions. To do so, the agents were only equipped with the ability to link distinct stimuli together, such as an event and a reward; this is similar to associative learning, a cognitive process which is widespread amongst animal species. The model showed that the challenge of capturing the prey when hunting alone, and the reward of sharing food after a successful hunt drove the agents to learn how to work together, with previous experiences shaping decisions made during subsequent hunts. Importantly, the predators started to exhibit the ability to take on distinct, complementary roles reminiscent of those observed during collaborative hunting, such as one agent chasing the prey while another ambushes it. Overall, the work by Tsutsui et al. challenges the traditional view that only organisms equipped with high-level cognitive processes can show refined collaborative approaches to hunting, opening the possibility that these behaviors may be more widespread than originally thought including between animals of different species.
Deep Learning , Predatory Behavior , Reinforcement, Psychology , Animals , Cooperative Behavior , Humans , Computer Simulation , Decision Making
OBJECTIVE: To investigate whether muscle quality is related to cognitive function in older adults living in the community. METHODS: The participants were 40 community-dwelling older adults without a diagnosis of dementia (mean age, 78.85 ± 6.40 years; 31 women). The dependent variable was the score on the mild cognitive impairment (MCI) index of the Japanese version of the Neurobehavioral Cognitive Status Examination Five (range: 0-6; higher scores indicate MCI or possible dementia). RESULTS: Multiple regression with Bayesian statistics was performed for analysis of muscle quality, as indicated by echo intensity (EI), with skeletal muscle mass index, gait speed, physical activity level, age, and sex as covariates. EI was significantly associated with the MCI index (expected a posterior = 0.04 [95% Bayesian confidence interval: 0.01, 0.07], t = 2.47, ß = 0.41, p = 0.019). CONCLUSIONS: The results suggest that EI may be related to the cognitive function of older adults living in the community. Future studies should examine whether focusing on EI can help prevent cognitive decline among older adults..
Contrast resolution is an important index for evaluating the signal detectability of computed tomographic (CT) images. Recently, various noise reduction algorithms, such as iterative reconstruction (IR) and deep learning reconstruction (DLR), have been proposed to reduce the image noise in CT images. However, these algorithms cause changes in the image noise texture and blurred image signals in CT images. Furthermore, the contrast-to-noise ratio (CNR) cannot be accurately evaluated in CT images reconstructed using noise reduction methods. Therefore, in this study, we devised a new method, namely, "effective CNR analysis," for evaluating the contrast resolution of CT images. We verified whether the proposed algorithm could evaluate the effective contrast resolution based on the signal detectability of CT images. The findings showed that the effective CNR values obtained using the proposed method correlated well with the subjective visual impressions of CT images. To investigate whether signal detectability was appropriately evaluated using effective CNR analysis, the conventional CNR analysis method was compared with the proposed method. The CNRs of the IR and DLR images calculated using conventional CNR analysis were 13.2 and 10.7, respectively. By contrast, those calculated using the effective CNR analysis were estimated to be 0.7 and 1.1, respectively. Considering that the signal visibility of DLR images was superior to that of IR images, our proposed effective CNR analysis was shown to be appropriate for evaluating the contrast resolution of CT images.
Evaluation of intervention in a multiagent system, for example, when humans should intervene in autonomous driving systems and when a player should pass to teammates for a good shot, is challenging in various engineering and scientific fields. Estimating the individual treatment effect (ITE) using counterfactual long-term prediction is practical to evaluate such interventions. However, most of the conventional frameworks did not consider the time-varying complex structure of multiagent relationships and covariate counterfactual prediction. This may lead to erroneous assessments of ITE and difficulty in interpretation. Here, we propose an interpretable, counterfactual recurrent network in multiagent systems to estimate the effect of the intervention. Our model leverages graph variational recurrent neural networks (GVRNNs) and theory-based computation with domain knowledge for the ITE estimation framework based on long-term prediction of multiagent covariates and outcomes, which can confirm the circumstances under which the intervention is effective. On simulated models of an automated vehicle and biological agents with time-varying confounders, we show that our methods achieved lower estimation errors in counterfactual covariates and the most effective treatment timing than the baselines. Furthermore, using real basketball data, our methods performed realistic counterfactual predictions and evaluated the counterfactual passes in shot scenarios.
This cross-sectional study aimed to determine the association between phase angle (PhA) and physical activity intensity in community-dwelling older Japanese adults. The intensity and time of physical activity for predicting high PhA were also examined. This study involved 67 community-dwelling older adults (mean age: 78.3 ± 5.5; female: 83.6%). We measured the physical activity and body composition of the participants. Physical activity was measured using a triaxial accelerometer, and light-intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA) hours per day were calculated from the results. Body composition was measured using Inbody S10, and the PhA was calculated from the measurements of the right side of the body. Bayesian statistical modeling revealed an association between PhA and MVPA (ß = 0.256; p = 0.022; 95% Bayesian confidence interval [CI] = 0.001, 0.012), but not LPA (ß = -0.113; p = 0.341; 95% Bayesian CI = -0.002, 0.001), even after adjustment for confounders. The cutoff value of MVPA predicting high PhA, calculated by the receiver operator characteristic curve, was 19.7 min/d (sensitivity = 0.906; specificity = 0.429). These results can be used to develop strategies to increase PhA in older adults and suggest that MVPA is important in this population.
AIMS: Regular self-weighing is effective in weight management and may help to mitigate the risk of underweight among older adults. We examined which factors of oral function are associated with a risk for underweight among community-dwelling older adults and whether regular self-weighing can mitigate that risk. METHODS: This was a cohort study. Self-administered questionnaires were mailed to 7665 older adults in March 2019 (response rate 74.3%) and 7591 in March 2020 (response rate 74.7%). Among those who responded to both surveys, 3594 older adults who were not underweight in March 2019 were included (follow-up rate: 59.2%). We examined the association between dysphagia, poor masticatory function, and dry mouth and the development of underweight, and whether regular self-weighing reduced the risk for underweight. RESULTS: The average age ± standard deviation of participants was 71.1 ± 3.4 years. There was a significant association between swallowing difficulty and the occurrence of underweight (odds ratio = 1.65, p = .012). However, this relationship did not differ significantly with regular self-weighing (p = .477). CONCLUSIONS: These study findings suggest that to prevent underweight among community-dwelling older adults, it is important to focus on those with poor swallowing function.
OBJECTIVES: The aim of this study was to investigate the stronger correlate of appetite-family or friend networks-in community-dwelling older adults, given that undernutrition can impair physical function, increase mortality, and be influenced by social networks. METHODS: A cross-sectional study was conducted in Kasugai City, Aichi Prefecture, and Nara City, Nara Prefecture, Japan, between August 2019 and March 2023. The analysis included 119 participants (women: 79%, mean age: 76.5 ± 5.6 y). A multiple regression analysis was performed, using the scores from the Japanese version of the Simplified Nutritional Appetite Questionnaire (SNAQ-J) as the dependent variable and family network and friend network as the independent variables. The analysis included social participation, living alone status, sex, age, body mass index, skeletal muscle mass index, grip strength, walking speed, and the Japanese version of the 15 Geriatric Depression Scale score as covariates to examine their relationship with appetite. RESULTS: The mean value of the SNAQ-J score of the participants was 15.4 ± 1.2. Seven participants (6%) had a loss of appetite. Family network was significantly associated with appetite (B = 0.121, ß = 0.266, P <0.05; 95% condidence interval [CI], 0.030-0.212). In the single regression analysis, the friend network was significantly associated with the total score of the SNAQ-J (B = 0.115, P <0.001; 95% CI, 0.052-0.177); however, this association was not observed in the multiple regression analysis (B = 0.002, ß = 0.006, P = 0.954; 95% CI, -0.074-0.078). CONCLUSION: Appetite was associated with family networks. Among social networks, focusing on family networks may help prevent the loss of appetite in older adults in Japan.
Appetite , Malnutrition , Humans , Female , Aged , Aged, 80 and over , Appetite/physiology , Cross-Sectional Studies , Independent Living , Friends
Extracting the rules of real-world multi-agent behaviors is a current challenge in various scientific and engineering fields. Biological agents independently have limited observation and mechanical constraints; however, most of the conventional data-driven models ignore such assumptions, resulting in lack of biological plausibility and model interpretability for behavioral analyses. Here we propose sequential generative models with partial observation and mechanical constraints in a decentralized manner, which can model agents' cognition and body dynamics, and predict biologically plausible behaviors. We formulate this as a decentralized multi-agent imitation-learning problem, leveraging binary partial observation and decentralized policy models based on hierarchical variational recurrent neural networks with physical and biomechanical penalties. Using real-world basketball and soccer datasets, we show the effectiveness of our method in terms of the constraint violations, long-term trajectory prediction, and partial observation. Our approach can be used as a multi-agent simulator to generate realistic trajectories using real-world data.
Learning , Neural Networks, Computer , Cognition
ABSTRACT: The persistence of inflammatory and neuropathic pain is poorly understood. We investigated a novel therapeutic paradigm by targeting gene networks that sustain or reverse persistent pain states. Our prior observations found that Sp1-like transcription factors drive the expression of TRPV1, a pain receptor, that is blocked in vitro by mithramycin A (MTM), an inhibitor of Sp1-like factors. Here, we investigate the ability of MTM to reverse in vivo models of inflammatory and chemotherapy-induced peripheral neuropathy (CIPN) pain and explore MTM's underlying mechanisms. Mithramycin reversed inflammatory heat hyperalgesia induced by complete Freund adjuvant and cisplatin-induced heat and mechanical hypersensitivity. In addition, MTM reversed both short-term and long-term (1 month) oxaliplatin-induced mechanical and cold hypersensitivity, without the rescue of intraepidermal nerve fiber loss. Mithramycin reversed oxaliplatin-induced cold hypersensitivity and oxaliplatin-induced TRPM8 overexpression in dorsal root ganglion (DRG). Evidence across multiple transcriptomic profiling approaches suggest that MTM reverses inflammatory and neuropathic pain through broad transcriptional and alternative splicing regulatory actions. Mithramycin-dependent changes in gene expression following oxaliplatin treatment were largely opposite to and rarely overlapped with changes in gene expression induced by oxaliplatin alone. Notably, RNAseq analysis revealed MTM rescue of oxaliplatin-induced dysregulation of mitochondrial electron transport chain genes that correlated with in vivo reversal of excess reactive oxygen species in DRG neurons. This finding suggests that the mechanism(s) driving persistent pain states such as CIPN are not fixed but are sustained by ongoing modifiable transcription-dependent processes.
Antineoplastic Agents , Neuralgia , Humans , Plicamycin/adverse effects , Oxaliplatin/toxicity , Antineoplastic Agents/therapeutic use , Antineoplastic Agents/adverse effects , Neuralgia/chemically induced , Neuralgia/drug therapy , Neuralgia/metabolism , Hyperalgesia/chemically induced , Hyperalgesia/drug therapy , Hyperalgesia/metabolism , Ganglia, Spinal/metabolism
In this study, we analyzed golfers' swing movement to extract differences in proficiency and individual characteristics using two-dimensional video data from a single camera. We conducted an experiment with 27 golfers who had a wide range of skill levels, using a 7-iron; we acquired video data with a camera on the sagittal plane. For data extraction, we used pose estimation (using HRNet) and object detection (using DeepLabCut) methods to extract human-joint and club-head data. We examined the relationship between proficiency and individual characteristics vis-à-vis forward tilt angle and club trajectory. The results showed that the stability and reproducibility of the forward tilt angle are characteristics of proficiency. Highly skilled golfers showed low variability and high reproducibility between trials in forward tilt angle. However, we found that club trajectory may not be a characteristic of proficiency but rather an individual characteristic. Club trajectory was divided roughly into clockwise rotation and counterclockwise rotation. Thus, the analysis based on video data from a single markerless camera enabled the extraction of the differences in proficiency and individual characteristics of golf swing. This suggests the usefulness of our system for simply evaluating golf swings and applying it to motor learning and coaching situations.
The study explored cross-sectional associations between loneliness and occupational dysfunction in community-dwelling older adults. Seventy-four older adults (12 men and 62 women; mean age 73.9 ± 8.3 years) completed a questionnaire survey that included the Japanese version of the UCLA Loneliness Scale Version 3 and the Classification and Assessment of Occupational Dysfunction (CAOD). Bayesian statistical modeling was used for a more stable estimation given the small sample. For model selection, we assumed a univariate analysis model of the CAOD (Model 1); a multivariate analysis model, including confounding factors in Model 1 (Model 2); and a multivariate analysis model, including random effects in Model 2 (Model 3). The best model was selected by comparing the widely applicable information criterion (WAIC) and the widely applicable Bayesian information criterion (WBIC) for each model. Bayesian statistics with the dependent variable as "loneliness" showed that the best model used "occupational dysfunction" as the independent variable and included confounding factors and random effects (WAIC = 474.5 and WBIC = 213.1). The best model identified an association between occupational dysfunction and loneliness (odds ratio [OR] = 2.363; 95% Bayesian confidence interval [CI] = 1.105-5.259). This study highlights the role of occupational dysfunction in addition to the risks and related factors reported to date when dealing with loneliness. Therapists could help older adults cope with loneliness by supporting their social participation and improving their occupational dysfunction.
Independent Living , Occupational Therapy , Male , Humans , Female , Aged , Aged, 80 and over , Cross-Sectional Studies , Bayes Theorem , Allied Health Personnel
This study aims to clarify why the aiming method in golf putting in risky situations differs based on skill level. This study set up a difficult challenge (steep slopes and fast ball rolling greens), which required even professional golfers to change their aim. A total of 12 tour professionals and 12 intermediate amateurs were asked to perform a steep-slope task with no visual feedback of outcomes (no FB) followed by a task with visual feedback (with FB). The aim of the task was for the ball to enter the hole in one shot. Additionally, the participants were told that if the ball did not enter the hole, it was to at least stop as close to it as possible. The participant's aim (as an angle) and the kinematics of the putter head and ball were measured. The results indicated that professionals' highest ball trajectory points were significantly higher than that of amateurs, especially with FB. Additionally, professionals had higher ball-launch angles (the direction of the ball when the line connecting the ball and the center of the hole is 0 degrees) and lower peak putter head velocities than amateurs. Furthermore, the aim angle, indicating the golfer's decision-making, was higher for professionals under both conditions. However, even with FB, the amateurs' aim angles were lower and the difference between trials was smaller than that of professionals. Therefore, this study confirmed that the professionals made more drastic changes to their aim to find low-risk routes than the amateurs and that the amateurs' ability to adjust their aim was lower than that of professionals. The results suggest that the reason for the amateurs' inability to find low-risk routes lies in their decision-making. The professionals found better routes; however, there were individual differences in their routes.
Nonthermal velocity distributions with much greater tails than a Maxwellian have been observed for radical atoms in plasmas for a long time. Historically, such velocity distributions have been modeled by a two-temperature Maxwell distribution. In this paper, I propose a model based on collisional energy cascade, which has been studied in the field of granular materials. In the collisional energy cascade, a particle ensemble undergoes energy input at the high-energy region, entropy production by elastic collisions among particles, and energy dissipation. For radical atoms, energy input may be caused by the Franck-Condon energy of molecular dissociation or charge-exchange collision with hot ions, and the input energy is eventually dissipated by collisions with the walls. I show that the steady-state velocity distribution in the collisional energy cascade is approximated by the generalized Mittag-Leffler distribution, which is a one-parameter extension of the Maxwell distribution. This parameter indicates the degree of the nonthermality and is related to the relative importance of energy dissipation over entropy production. This model is compared with a direct molecular dynamics simulation for simplified gaseous systems with energy input, as well as some experimentally observed velocity distributions of light radicals in plasmas.
While forecasting football match results has long been a popular topic, a practical model for football participants, such as coaches and players, has not been considered in great detail. In this study, we propose a generalized and interpretable machine learning model framework that only requires coaches' decisions and player quality features for forecasting. By further allowing the model to embed historical match statistics, features that consist of significant information, during the training process the model was practical and achieved both high performance and interpretability. Using five years of data (over 1,700 matches) from the English Premier League, our results show that our model was able to achieve high performance with an F1-score of 0.47, compared to the baseline betting odds prediction, which had an F1-score of 0.39. Moreover, our framework allows football teams to adapt for tactical decision-making, strength and weakness identification, formation and player selection, and transfer target validation. The framework in this study would have proven the feasibility of building a practical match result forecast framework and may serve to inspire future studies.
Athletic Performance , Gambling , Soccer , Humans , Forecasting
BACKGROUND: Olanexidine glucuronide (Olanedine®), an antiseptic solution may cause skin dermatitis around one week after disinfection. Although removal after the procedure is recommended to avoid skin dermatitis, whether it is effective for preventing skin dermatitis has not been documented in detail in the literature. CASE PRESENTATION: We encountered two cases of delayed-onset contact dermatitis by Olanedine®. In both cases, the patient's back was disinfected with Olanedine® and was covered with a surgical drape for epidural catheterization. After catheterization and removal of the surgical drape, the insertion site of the catheter was covered with a film dressing, then the epidural catheter was taped to the back. On the third postoperative day, the epidural catheter was removed. On the seventh postoperative day, the patients reported pruritus on the back, where an erythematous papule rash was observed. However, it was not observed at the site covered by the tape to secure the epidural catheter or by the tape of the surgical drape. Symptoms were relieved with oral or topical steroids by the time of discharge. CONCLUSION: Wiping off the remaining Olanedine® even a few days after disinfection may be helpful not only for reducing symptoms but also for preventing the development of contact dermatitis.
Physical attractiveness is a key factor in social communication, and through this communication process, we attractively brand and express ourselves. Thus, this study investigated the biomechanical strategies used by women to express gait attractiveness. Our aim was to extend the current literature by examining this aspect of dynamic motion from the perspective of expressed, rather than perceived attractiveness. In this regard, we obtained motion capture data from 17 women, including seven professional fashion models. The participants walked on a treadmill under two conditions: 1) a normal condition in which they were instructed to walk as casually as possible; and 2) an attractive-conscious condition where they were asked to walk as attractively as possible. Then, we used whole-body kinematic data to represent motion energy at each joint, flexibility of the upper body, and the up-down/forward-backward silhouettes of the limbs, and compared these parameters between the two conditions by using statistical parametric mapping. During the attractive-conscious condition, the non-model women increased the energy of the hip and thoracolumbar joints, which emphasized the motions of their bosoms and buttocks. They also increased their upper body flexibility (possibly reflecting fertility) and continued to face front and downward. Conversely, although the fashion models partially shared the same strategy with the non-models (e.g., hip energy, upper body flexibility, and head bending downward), the strategy of the former was prominent in the stretching of the knee during the push-off phase and pulling the upper arm back, allowing them to showcase their youth and emphasize their chests. In addition, the fashion models used a wider variety of strategies to express their gait attractiveness. The findings indicate that the biomechanical strategy used to express gait attractiveness in women involves showcasing femininity, fertility, and youth. Our results not only deepen the understanding of human movement for self-expression through gait attractiveness, but they also help us comprehend self-branding behavior in human social life.
Bacillus subtilis natto is used in the production of natto, a traditional fermented soy food, and has beneficial immunomodulatory effects in humans. Single-stranded RNA (ssRNA) viruses, including influenza and coronavirus, often cause global pandemics. We proposed a human cell culture model mimicking ssRNA viral infection and investigated the ability of B. subtilis natto to induce antiviral effects in the model. The gene expressions were analyzed using quantitative real-time reverse transcription PCR. M1-phenotype macrophages derived from THP-1 cells strongly express the Toll-like receptor 8 (76.2-hold), CD80 (64.2-hold), and CCR7 (45.7-hold) mRNA compared to M0 macrophages. One µg/mL of resiquimod (RSQ)-stimulation induced the expression of IRF3 (1.9-hold), CXCL10 (14.5-hold), IFNß1 (3.5-hold), ISG20 (4.4-hold), and MxA (1.7-hold) mRNA in the M1-phenotype macrophages. Based on these results, the RSQ-stimulated M1-phenotype macrophages were used as a cell culture model mimicking ssRNA viral infection. Moreover, the B. subtilis natto XF36 strain induced the expression of genes associated with antiviral activities (IFNß1, IFNλ1, ISG20, and RNase L) and anti-inflammatory activities (IL-10) in the cell culture model. Thus, it is suggested that the XF36 suppresses viral infections and excessive inflammation by inducing the expression of genes involved in antiviral and anti-inflammatory activities.
We investigate the long-range behavior of the induced Casimir interaction between two spinless heavy impurities, or polarons, in superfluid cold atomic gases. With the help of effective field theory (EFT) of a Galilean invariant superfluid, we show that the induced impurity-impurity potential at long distance universally shows a relativistic van der Waals-like attraction (â¼1/r^{7}) resulting from the exchange of two superfluid phonons. We also clarify finite temperature effects from the same two-phonon exchange process. The temperature T introduces the additional length scale c_{s}/T with the speed of sound c_{s}. Leading corrections at finite temperature scale as T^{6}/r for distances râªc_{s}/T smaller than the thermal length. For larger distances the potential shows a nonrelativistic van der Waals behavior (â¼T/r^{6}) instead of the relativistic one. Our EFT formulation applies not only to weakly coupled Bose or Fermi superfluids but also to those composed of strongly correlated unitary fermions with a weakly coupled impurity. The sound velocity controls the magnitude of the van der Waals potential, which we evaluate for the fermionic superfluid in the BCS-BEC crossover.
Humans often share roles and aim to achieve a group goal based on sociality, which is the tendency to spontaneously involve oneself with others. Cognitive science, psychology, and neuroscience studies suggest that in such planned coordination, adjusting one's own actions based on other roles is crucial for high task performance. However, the mechanisms of complex and dynamically planned coordination, such as non-verbal group behavior with three or more members, remain to be fully investigated. This study introduced a coordinated drawing task in a triad, quantitatively analyzed non-verbal group behavior based on sharing heterogeneous roles, and investigated an important role. Participant triads engaged in the task repeatedly by operating reels to change thread tensions and moving a pen connected to the three threads to draw an equilateral triangle. Then, the three roles (pulling, relaxing, and adjusting) had to be shared. The pulling and relaxing roles served to move the pen as if an operator pulled it closer to the hand and to support the pen's movement, respectively. However, these roles alone could not draw a side considering the task specification. The adjusting role needed to change the tension flexibly and maintain an overall balance. In the experiment, we measured the pen positions and tensions, and established statistical models to fit the analyzed data. The results estimated that the action in the adjusting role was related to the improved performance of faster drawing on a side. This role may moderately intervene in the actions by the other roles and fine-tune without disturbing the pen's smooth movement while avoiding great pen deviation. Our findings may suggest the crucial role as a facilitator that handles resiliently in non-verbal coordinated behavior of a triad, and contribute to our understanding of social interactions.
