Differential replay for reward and punishment paths predicts approach and avoidance

Planning is thought to involve neural replay, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear if, during planning, replay of a path relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied participants while they planned to either approach or avoid an uncertain environment that contained paths leading to reward and to punishment. We show significant planning-related forward sequential replay with state-to-state transitions in the range of 20 to 90 ms. Replay of rewarding paths was boosted prior to a decision to avoid, and attenuated prior to a decision to approach. Crucially, a trial-by-trial bias in replaying punishing paths predicted an irrational choice to approach when a prospective environment was more risky, an effect that was particularly marked in more anxious participants. The findings reveal a coupling between the content of forwards replay and rational choice behaviour, such that replay prioritises an online representation of potential reward.

The foundations of the working alliance in assertive community treatment teams

Background In this study, we aimed to identify and define the fundamental components of the working alliance in multidisciplinary (Flexible) Assertive Community Treatment teams with shared caseloads, in order to support their daily practice and further research. Methods After reviewing the literature, concept mapping with professionals and clients was used to define the working alliance in (F) ACT teams. The resulting concept maps formed the basis for the working alliance assessment instrument, which was pilot tested with professionals and clients through cognitive interviews with a think-aloud procedure. Results The study led to the development of a twenty five-item assessment instrument to evaluate working alliances in multidisciplinary teams (WAM) that was comprised of three subscales: bond, task/goal and team. Two different versions were developed for clients and professionals. Conclusions The WAM instrument was developed to determine the quality of the working alliance in (F) ACT teams. Future research will focus on testing its psychometric properties and predictive value.

The Effects of High School Basketball Player’s Sports Participa-tion Motivation on Achievement Goal Orientation and Achieve-ment Behaviors

Background: Although the motivation to set goals and taking steps to achieve them is essential for athletes wishing to progress to a professional level, motives for participating in sports vary depending on personal and physical characteristics. We aimed to investigate the effect of motivation to participate in sports on achievement goal orientation and achievement behavior in high-school basketball players. Methods: The study included 256 female high-school basketball players from Busan, Korea, and was conducted between September and October 2020. The questionnaires obtained data regarding motivation to participate in sports, achievement goal orientation, and achievement behavior. Structural equation modeling was used for data analysis. Results: Motivation to participate in sports exhibited a significant positive correlation with achievement goal orientation (P<0.05). Specifically, motivation related to the development of technical skills and achieving a sense of fulfillment, amusement, and health exerted a positive effect on task-goal orientation. Greater motivation related to technical skill development, attaining a sense of accomplishment, and improving health was associated with greater self-goal orientation. Additionally, achievement goal orientation exerted a significant positive effect on achievement behavior (P<0.05). Conclusion: Given the relative unpopularity of basketball in Korea, it is crucial for players to develop high achievement goal orientation and engage in real efforts to translate such motivation into action. This goal- and achievement-oriented attitude should precede motivation for participating in basketball.

Tool-Use Model to Reproduce the Goal Situations Considering Relationship Among Tools, Objects, Actions and Effects Using Multimodal Deep Neural Networks

We propose a tool-use model that enables a robot to act toward a provided goal. It is important to consider features of the four factors; tools, objects actions, and effects at the same time because they are related to each other and one factor can influence the others. The tool-use model is constructed with deep neural networks (DNNs) using multimodal sensorimotor data; image, force, and joint angle information. To allow the robot to learn tool-use, we collect training data by controlling the robot to perform various object operations using several tools with multiple actions that leads different effects. Then the tool-use model is thereby trained and learns sensorimotor coordination and acquires relationships among tools, objects, actions and effects in its latent space. We can give the robot a task goal by providing an image showing the target placement and orientation of the object. Using the goal image with the tool-use model, the robot detects the features of tools and objects, and determines how to act to reproduce the target effects automatically. Then the robot generates actions adjusting to the real time situations even though the tools and objects are unknown and more complicated than trained ones.

Motor Synergies Measurement Reveals the Relevant Role of Variability in Reward-Based Learning

Currently, it is not fully understood how motor variability is regulated to ease of motor learning processes during reward-based tasks. This study aimed to assess the potential relationship between different dimensions of motor variability (i.e., the motor variability structure and the motor synergies variability) and the learning rate in a reward-based task developed using a two-axis force sensor in a computer environment. Forty-four participants performed a pretest, a training period, a posttest, and three retests. They had to release a virtual ball to hit a target using a vertical handle attached to a dynamometer in a computer-simulated reward-based task. The participants’ throwing performance, learning ratio, force applied, variability structure (detrended fluctuation analysis, DFA), and motor synergy variability (good and bad variability ratio, GV/BV) were calculated. Participants with higher initial GV/BV displayed greater performance improvements than those with lower GV/BV. DFA did not show any relationship with the learning ratio. These results suggest that exploring a broader range of successful motor synergy combinations to achieve the task goal can facilitate further learning during reward-based tasks. The evolution of the motor variability synergies as an index of the individuals’ learning stages seems to be supported by our study.

Exploring the Dimensions of Movement-Specific Reinvestment From Personal Characteristics Perspectives

The purposes of the present study were three-fold: to examine (a) if the movement-specific reinvestment responses should be represented as two dimensional constructs, (b) whether dichotomization of the movement-specific reinvestment responses are appropriate, and (c) how the two dimensions are associated with relevant psychological concepts. To conduct a comparative examination of the MSRS structure in two Asian samples, participants were 236 Japanese university students (136 men, 100 women; Mage = 18.0, SD = 1.6) and 328 Singaporeans (167 men, 161 women; Mage = 21.8, SD = 1.8). After examining the factor structure of the movement-specific reinvestment responses for the first purpose, latent class factor analysis was conducted for both samples for the second purpose. For the third purpose, correlation analysis and mediation analysis were conducted for a part of the Singaporean sample. Through a series of latent class factor analysis, four and three classes were identified for the Japanese and Singaporean samples, respectively. For both samples, the patterns of the item-average scores for the two movement-specific reinvestment dimensions were parallel among the classes. Conscious Motor Processing was positively associated with mental toughness, intrinsic regulation, integrated regulation, mastery-approach and task goal orientations, and dispositional flow, whereas Movement Self-Consciousness was positively related with stress and mastery-avoidance goal orientation. The findings of the study supported (a) the two-dimensional representation of the movement-specific reinvestment responses, but did not fully support (b) the practice of dichotomization of the movement-specific reinvestment responses, and indicated that (c) at the trait level, Conscious Motor Processing and Movement Self-Consciousness were associated with positive and negative psychological constructs, respectively.

Evidence for a Cultural Mindset: Combining Process Data, Theory, and Simulation

Despite large literature on Cross-Cultural Competence (3C) there is a gap in understanding learning processes and mechanisms by which people arrive at successful 3C. We present a novel perspective for 3C learning and decision-making in innovative assessment contexts. We use Mindset theory (i.e., believing ability is fixed or changeable) because it is shown to be a powerful motivator for general learning and performance and in cross-cultural contexts. We propose the notion of cultural mindsets – beliefs, affect, and cognition that govern how people adapt, learn, and update cultural information. To understand how cultural mindset affects learning and performance, we apply computational cognitive modeling using Markov decision process (MDP). Using logfile data from an interactive 3C task, we operationalize behavioral differences in actions and decision making based on Mindset theory, developing cognitive models of fixed and malleable cultural mindsets based on mechanisms of initial beliefs, goals, and belief updating. To explore the validity of our theory, we develop computational MDP models, generate simulated data, and examine whether performance patterns fit our expectations. We expected the malleable cultural mindset would be better at learning the cultural norms in the assessment, more persistent in cultural interactions, quit less before accomplishing the task goal, and would be more likely to modify behavior after negative feedback. We find evidence of distinct patterns of cultural learning, decision-making, and performance with more malleable cultural mindsets showing significantly greater cultural learning, persistence, and responsiveness to feedback, and more openness to exploring current cultural norms and behavior. Moreover, our model was supported in that we were able to accurately classify 83% of the simulated records from the generating model. We argue that cultural mindsets are important mechanisms involved in effectively navigating cross-cultural situations and should be considered in a variety of areas of future research including education, business, health, and military institutions.

Is there a Trade-off between Economy and Task Goal Variability in Transfemoral Amputee Gait?

Background: Energy cost minimization has been widely accepted to regulate gait. Optimization principles have been frequently used to explain how individuals adapt their gait pattern. However, there have been rare attempts to account for the role of variability in this optimization process. Motor redundancy can enable individuals to perform tasks reliably while achieving energy optimization. However, we do not know how the goal-irrelevant and goal-relevant variability is regulated.. In this study, we investigated how unilateral transfemoral amputees regulate step and stride variability based on the task to achieve energy economy. Methods: Nine individuals with unilateral transfemoral amputation walked on a treadmill at speeds of 0.6,0.8,1.0,1.2 and 1.4 m/s using their prescribed passive prostheses. We calculated the step-to-step and stride-to-stride variability and applied goal equivalent manifold (GEM) based control to decompose goal-relevant and goal-irrelevant manifold. To quantify the energy economy, the energy recovery rate (R) was calculated based on potential energy and kinetic energy. Comparisons were made between GEM variabilities and commonly used standard deviation measurements. A linear regression model was used to investigate the trade-off between R and GEM variabilities. Results: Our analysis shows greater variability along the goal-relevant manifold compared to the goal-irrelevant manifold (p<.001). Moreover, our analysis shows lower energy recovery rate for amputee gait compared to nonamputee gait (at least 20% less at faster walking speed). We found a negative relationship between energy recovery rate and goal-irrelevant variability. Compared to the standard deviation measurements, the variability decomposed using GEM reflected the preferred walking speed and the limitation of the passive prosthetic device.Conclusion: Individuals with amputation cleverly leverage task redundancy, regulating step and stride variability to the goal equivalent manifold (GEM). This result suggests that task redundancy enables unilateral amputees to benefit from motor variability in terms of energy economy. The differences observed between prosthetic step and intact step support the development of prosthetic leg capable of enhancing positive work during the double support phase and of powered prosthesis controllers that allow for variability along the task space while minimizing variability that interferes with the task goal. This study provides a different perspective on amputee gait analysis and challenge the field to think differently about the role of variability.

Functional Architecture of Executive Control and Associated Event-Related Potentials

Medial frontal cortex enables executive control by monitoring relevant information and using it to adapt behavior. In macaques performing a saccade countermanding (stop-signal) task, we recorded EEG over and neural spiking across all layers of the supplementary eye field (SEF). We report the laminar organization of concurrently activated neurons monitoring the conflict between incompatible responses and the timing of events serving goal maintenance and executive control. We also show their relation to coincident event-related potentials (ERP). Neurons signaling response conflict were largely broad-spiking found across all layers. Neurons signaling the interval until specific task events were largely broad-spiking neurons concentrated in L3 and L5. Neurons predicting the duration of control and sustaining the task goal until the release of operant control were a mix of narrow- and broad-spiking neurons confined to L2/3. We complement these results with the first report of a monkey homologue of the N2/P3 ERP complex associated with response inhibition. N2 polarization varied with error likelihood and P3 polarization varied with the duration of expected control. The amplitude of the N2 and P3 were predicted by the spike rate of different classes of neurons located in L2/3 but not L5/6. These findings reveal important, new features of the cortical microcircuitry supporting executive control and producing associated ERP.

Online modification of goal-directed control in human reaching movements

Humans are able to perform very sophisticated reaching movements in a myriad of contexts based on flexible control strategies influenced by the task goal and environmental constraints such as obstacles. However, it remains unknown whether these control strategies can be adjusted online. The objective of this study was to determine whether the factors which determine control strategies during planning also modify the execution of an ongoing movement following sudden changes in task demand. More precisely, we investigated whether, and at which latency, feedback responses to perturbation loads followed the change in the structure of the goal target or environment. We changed the target width (square or rectangle) to alter the task redundancy, or the presence of obstacles to induce different constraints on the reach path, and assessed based on surface EMG recordings when the change in visual display altered the feedback response to mechanical perturbations. Task-related EMG responses were detected within 150 ms of a change in target shape. Considering visuomotor delays of ~ 100 ms, these results suggest that it takes 50 ms to change control policy within a trial. An additional 30 ms delay was observed when the change in context involved sudden appearance or disappearance of obstacles. Overall, our results demonstrate that the control policy within a reaching movement is not static: contextual factors which influence movement planning also influence movement execution at surprisingly short latencies. Moreover, the additional 30 ms associated with obstacles suggest that these two types of changes may be mediated via distinct processes.