Task Goals Research Articles

Task-relevant visual feedback uncertainty attenuates visuomotor adaptation.

Motor adaptation is attenuated when sensory feedback about the movement is uncertain. Although this was initially shown for small visual errors, attenuation seems not to hold when visual errors are larger and the contributions of implicit adaptation are isolated with the error-clamp method, which makes visual feedback task-irrelevant. Here we ask whether adaptation to a similarly large perturbation is attenuated when task-relevant visual feedback is uncertain. In a first experiment, we tested participants on a 30° movement-contingent visuomotor rotation under both low (cursor) and high (cloud of moving dots) visual feedback uncertainty. In line with optimal integration, we found that the early increase in adaptation and final extent of adaptation were reduced with high feedback uncertainty. In a second experiment, we included several blocks of no-feedback trials during the perturbation block to quantify the contribution of implicit adaptation. Results showed that implicit adaptation was smaller with high compared to low feedback uncertainty throughout the perturbation block. The estimated contribution of explicit adaptation was overall small, particularly for high feedback uncertainty. Our results demonstrate an influence of task-relevant visual feedback, and the resulting target errors, on implicit adaptation. We show that our motor system is sensitive to the feedback it receives even for larger error sizes and accordingly adjusts its learning properties when our ability to achieve the task goal is affected.NEW & NOTEWORTHY Motor adaptation is linked to the estimation of our actions. Whereas uncertainty of task-irrelevant visual feedback appears not to influence implicit adaptation for errors beyond a certain size, here we tested whether this is still the case for task-relevant feedback. We show that implicit adaptation is attenuated when task-relevant visual feedback is uncertain, suggesting a dependency on the assessment of not just sensory prediction errors but also target errors.

Blockchain-driven decentralized identity management: An interdisciplinary review and research agenda

The rise of blockchain technology has sparked interest in decentralized identity management (DIdM). However, DIdM's interdisciplinary nature has led to a fragmented understanding. We propose a “Task Structure-Technological Properties-Fit” framework to clarify the application of DIdM across tasks and contexts. We conducted a comprehensive review of 149 DIdM papers to define task structure (task goals and stakeholder values), task goals (identity value creation and value maintenance), stakeholders (users, service providers, identity issuers, regulators, and infrastructure builders), and DIdM properties (interoperability and self-sovereignty). We explored how these elements could align and then highlight research gaps and present a DIdM research agenda.

Value-Based Subgoal Discovery and Path Planning for Reaching Long-Horizon Goals.

Learning to reach long-horizon goals in spatial traversal tasks is a significant challenge for autonomous agents. Recent subgoal graph-based planning methods address this challenge by decomposing a goal into a sequence of shorter-horizon subgoals. These methods, however, use arbitrary heuristics for sampling or discovering subgoals, which may not conform to the cumulative reward distribution. Moreover, they are prone to learning erroneous connections (edges) between subgoals, especially those lying across obstacles. To address these issues, this article proposes a novel subgoal graph-based planning method called learning subgoal graph using value-based subgoal discovery and automatic pruning (LSGVP). The proposed method uses a subgoal discovery heuristic that is based on a cumulative reward (value) measure and yields sparse subgoals, including those lying on the higher cumulative reward paths. Moreover, LSGVP guides the agent to automatically prune the learned subgoal graph to remove the erroneous edges. The combination of these novel features helps the LSGVP agent to achieve higher cumulative positive rewards than other subgoal sampling or discovery heuristics, as well as higher goal-reaching success rates than other state-of-the-art subgoal graph-based planning methods.

The influence of reward and loss outcomes after free- and forced-tasks on voluntary task choice

In four experiments, we investigated the impact of outcomes and processing mode (free versus forced) on subsequent voluntary task-switching behavior. Participants freely chose between two tasks or were forced to perform one, and the feedback they received randomly varied after correct performance (reward or no-reward; loss or no-loss). In general, we reasoned that the most recently applied task goal is usually the most valued one, leading people to prefer task repetitions over switches. However, the task values might be additionally biased by previous outcomes and the previous processing mode. Indeed, negatively reinforcing tasks with no-reward or losses generally resulted in more subsequent switches. Additionally, participants demonstrated a stronger attachment to free- compared to forced-tasks, as indicated by more switches when the previous task was forced, suggesting that people generally value free over forced-choice task goals. Moreover, the reward manipulation had a greater influence on switching behavior following free- compared to forced-tasks in Exp. 1 and Exp. 3, suggesting a stronger emphasis on evaluating rewarding outcomes associated with free-task choices. However, this inflationary effect on task choice seemed to be limited to reward and situations where task choice and performance more strongly overlap. Specifically, there was no evidence that switching behavior was differentially influenced after free-and forced-task as a function of losses (Exp. 2) or reward when task choice and task performance were separated (Exp. 4). Overall, the results provide new insights into how the valuation of task goals based on choice freedom and outcome feedback can influence voluntary task choices.

Successful retrieval is its own reward.

The ability to successfully remember past events is critical to our daily lives, yet the neural mechanisms underlying the motivation to retrieve is unclear. Although reward-system activity and feedback-related signals have been observed during memory retrieval, whether this signal reflects intrinsic reward or goal-attainment is unknown. Adjudicating between these two alternatives is crucial for understanding how individuals are motivated to engage in retrieval and how retrieval supports later remembering. To test these two accounts, we conducted between-subjects recognition memory tasks on human participants undergoing scalp electroencephalography and varied test-phase goals (recognize old vs. detect new items). We used an independently validated feedback classifier to measure positive feedback evidence. We find positive feedback following successful retrieval regardless of task goals. Together, these results suggest that successful retrieval is intrinsically rewarding. Such a feedback signal may promote future retrieval attempts as well as bolster later memory for the successfully retrieved events.

Distribution of control during bimanual movement and stabilization

In two-handed actions like baseball batting, the brain can allocate the control to each arm in an infinite number of ways. According to hemispheric specialization theory, the dominant hemisphere is adept at ballistic control, while the non-dominant hemisphere is specialized at postural stabilization, so the brain should divide the control between the arms according to their respective specialization. Here, we tested this prediction by examining how the brain shares the control between the dominant and non-dominant arms during bimanual reaching and postural stabilization. Participants reached with both hands, which were tied together by a stiff virtual spring, to a target surrounded by an unstable repulsive force field. If the brain exploits each hemisphere’s specialization, then the dominant arm should be responsible for acceleration early in the movement, and the non-dominant arm will be the prime actor at the end when holding steady against the force field. The power grasp force, which signifies the postural stability of each arm, peaked at movement termination but was equally large in both arms. Furthermore, the brain predominantly used the arm that could use the stronger flexor muscles to mainly accelerate the movement. These results point to the brain flexibly allocating the control to each arm according to the task goal without adhering to a strict specialization scheme.

Distributed safe formation tracking control of multiquadcopter systems using barrier Lyapunov function.

Coordinating the movements of a robotic fleet using consensus-based techniques is an important problem in achieving the desired goal of a specific task. Although most available techniques developed for consensus-based control ignore the collision of robots in the transient phase, they are either computationally expensive or cannot be applied in environments with dynamic obstacles. Therefore, we propose a new distributed collision-free formation tracking control scheme for multiquadcopter systems by exploiting the properties of the barrier Lyapunov function (BLF). Accordingly, the problem is formulated in a backstepping setting, and a distributed control law that guarantees collision-free formation tracking of the quads is derived. In other words, the problems of both tracking and interagent collision avoidance with a predefined accuracy are formulated using the proposed BLF for position subsystems, and the controllers are designed through augmentation of a quadratic Lyapunov function. Owing to the underactuated nature of the quadcopter system, virtual control inputs are considered for the translational (x and y axes) subsystems that are then used to generate the desired values for the roll and pitch angles for the attitude control subsystem. This provides a hierarchical controller structure for each quadcopter. The attitude controller is designed for each quadcopter locally by taking into account a predetermined error limit by another BLF. Finally, simulation results from the MATLAB-Simulink environment are provided to show the accuracy of the proposed method. A numerical comparison with an optimization-based technique is also provided to prove the superiority of the proposed method in terms of the computational cost, steady-state error, and response time.

Limb-related sensory prediction errors and task-related performance errors facilitate human sensorimotor learning through separate mechanisms.

The unpredictable nature of our world can introduce a variety of errors in our actions, including sensory prediction errors (SPEs) and task performance errors (TPEs). SPEs arise when our existing internal models of limb-environment properties and interactions become miscalibrated due to changes in the environment, while TPEs occur when environmental perturbations hinder achievement of task goals. The precise mechanisms employed by the sensorimotor system to learn from such limb- and task-related errors and improve future performance are not comprehensively understood. To gain insight into these mechanisms, we performed a series of learning experiments wherein the location and size of a reach target were varied, the visual feedback of the motion was perturbed in different ways, and instructions were carefully manipulated. Our findings indicate that the mechanisms employed to compensate SPEs and TPEs are dissociable. Specifically, our results fail to support theories that suggest that TPEs trigger implicit refinement of reach plans or that their occurrence automatically modulates SPE-mediated learning. Rather, TPEs drive improved action selection, that is, the selection of verbally sensitive, volitional strategies that reduce future errors. Moreover, we find that exposure to SPEs is necessary and sufficient to trigger implicit recalibration. When SPE-mediated implicit learning and TPE-driven improved action selection combine, performance gains are larger. However, when actions are always successful and strategies are not employed, refinement in behavior is smaller. Flexibly weighting strategic action selection and implicit recalibration could thus be a way of controlling how much, and how quickly, we learn from errors.

“We all contributed to tell stories to the best of our abilities”: collaborative digital storytelling to promote students’ positive interdependence in an online course of Italian as a foreign language

Positive interdependence is defined as a mutual relationship between people who are driven to achieve the same task goals- Considered as the foundation of collaborative language learning, it can surface in group activities of digital content creation. Digital storytelling may enhance skills of positive interdependence as it enables digital narratives to be told through mixed media (Robin, 2016). However, prolonged exposure to technology might cause distraction, motivation loss, and fatigue among language students, hampering the establishment of positive interdependence. To encourage interdependent interactions in digital learning environments, this study presents the results of educational activities conducted using the ThingLink and StoryMaps platforms by learners of Italian as a foreign language during an online language course. The results stemming from online questionnaires, transcript analyses, and focus group interviews highlight how students’ positive interdependence can be boosted by telling stories through immersive technologies.

EQUILIBRIUM IN TECHNICAL WRITING: HARMONIZING OBJECTIVITY WITH ADVOCACY

The task of editing is strenuous, and the most challenging one is to reach the target goals within the time limitation. Equilibrium is the stage of finding a balance between two opposite things. In this research piece, the standpoint of an editor will be analyzed from the perspective of objectivity and advocacy. The fact cannot be denied that editors (many of them) spend an extensive time only to rectify the issues related to lexicon. However, painfully true, many of them overlook the rhythm of balancing act, and only for that lethargic activity, they face a challenging situation to reach the laudable phase. The goal of this research task is to help the future editors and the technical writers to connect the eclectic issues related to the balancing act.

Top-Down Task Goals Induce the Retrieval State.

Engaging the retrieval state (Tulving, 1983) impacts processing and behavior (Long and Kuhl, 2019, 2021; Smith et al., 2022), but the extent to which top-down factors-explicit instructions and goals-versus bottom-up factors-stimulus properties such as repetition and similarity-jointly or independently induce the retrieval state is unclear. Identifying the impact of bottom-up and top-down factors on retrieval state engagement is critical for understanding how control of task-relevant versus task-irrelevant brain states influence cognition. We conducted between-subjects recognition memory tasks on male and female human participants in which we varied test phase goals. We recorded scalp electroencephalography and used an independently validated mnemonic state classifier (Long, 2023) to measure retrieval state engagement as a function of top-down task goals (recognize old vs detect new items) and bottom-up stimulus repetition (hits vs correct rejections (CRs)). We find that whereas the retrieval state is engaged for hits regardless of top-down goals, the retrieval state is only engaged during CRs when the top-down goal is to recognize old items. Furthermore, retrieval state engagement is greater for low compared to high confidence hits when the task goal is to recognize old items. Together, these results suggest that top-down demands to recognize old items induce the retrieval state independent from bottom-up factors, potentially reflecting the recruitment of internal attention to enable access of a stored representation.

Dissimilarities of the demi-plié movement trajectory in its different roles in classical ballet

ABSTRACT Demi-plié is a coordinated dance movement involving knees bent while keeping hips turned out and heels grounded. It consists of descending and ascending phases, the latter often preparing for the next move. Task goals may influence its trajectory. Ten classical dancers (eight females, two males), aged 20–45 years old performed demi-plié itself and prior to pirouette en dehors, relevé, sauté, and sissonne fermée de côté. Lower limb and hip trajectory data were collected through a motion capture system. Time-series data were aligned across all conditions using a dynamic time warping algorithm. The Euclidean distance measured the hip trajectory between each ballet movement, providing a continuous dissimilarity function over time. Descriptive analysis focused on each participant’s maximum dissimilarity values across conditions. Results showed maximum hip trajectory differences of 40% for demi-plié before sauté, 30% before sissonne, 20% before relevé, and 10% before pirouette. Dissimilarities began in the descending phase of the demi-plié. ANOVAs for repeated measures and Bonferroni’s post-hoc showed that the standard deviation of dissimilarity had the largest effect size for the demi-plié – demi-plié before sauté, and the smallest for the demi-plié – demi-plié before pirouette. Demi-plié prior to jumps demands plyometric forces and has open-loop motor planning, requiring acceleration, whereas demi-plié is closed-loop, relying on proprioceptive updating.

Dexterous manipulation: differential sensitivity of manipulation and grasp forces to task requirements.

How humans coordinate digit forces to perform dexterous manipulation is not well understood. This gap is due to the use of tasks devoid of dexterity requirements and/or the use of analytical techniques that cannot isolate the roles that digit forces play in preventing object slip and controlling object position and orientation (pose). In our recent work, we used a dexterous manipulation task and decomposed digit forces into FG, the internal force that prevents object slip, and FM, the force responsible for object pose control. Unlike FG, FM was modulated from object lift onset to hold, suggesting their different sensitivity to sensory feedback acquired during object lift. However, the extent to which FG and FM can be controlled independently remains to be determined. Importantly, how FG and FM change as a function of object property is mathematically indeterminate and therefore requires active modulation. To address this gap, we systematically changed either object mass or external torque. The FM normal component responsible for object orientation control was modulated to changes in object torque but not mass. In contrast, FG was distinctly modulated to changes in object mass and torque. These findings point to a differential sensitivity of FG and FM to task requirements and provide novel insights into the neural control of dexterous manipulation. Importantly, our results indicate that the proposed digit force decomposition has the potential to capture important differences in how sensory inputs are processed and integrated to simultaneously ensure grasp stability and dexterous object pose control.NEW & NOTEWORTHY Successful dexterous object manipulation requires simultaneous prevention of object slip and object pose control. How these two task goals are attained can be investigated by decomposing digit forces into grasp and manipulation forces, respectively. We found that these forces were characterized by differential sensitivity to changes in object properties (mass and torque). This finding suggests the involvement of distinct sensorimotor mechanisms that, combined, simultaneously ensure grasp stability and dexterous control of object pose.

Multiple Goals Theory and Communication Quality Analysis for Fellows Communication Training.

End-of-life communication skills are vital to high-quality critical care. Patients and families often report deficiencies in end-of-life communication by providers. However, formalized training is difficult to implement and study on a large scale. Furthermore, curricula are often designed with early-stage clinical trainees in mind and are not tailored to advanced clinician learners. The goal of this pilot study was to explore educational and practical implications of using Multiple Goals Theory (MGT), Communication Quality Analysis (CQA), and communication logs as a three-pronged, reflective communication curriculum for advanced trainees. We describe design and qualitative evaluation of a novel, pilot, longitudinal curricular intervention for pulmonary and critical care fellows and program directors at a tertiary academic medical center. The 2-year longitudinal communication curriculum incorporates 1) a theoretical framework from communication science (MGT), with 2) a novel training modality of analyzing audio-recorded intensive care unit family meetings (CQA), and 3) written communication logs after an intensive care unit family meeting. The sample included 13 pulmonary and critical care medicine fellows and two program directors. Qualitative thematic analysis was conducted on seven fellow interviews and on 23 communication logs completed. Four themes emerged from interviews: 1) fellows incorporated the skills into real-life practice and found the curriculum useful and valuable; 2) a key takeaway from MGT was the deemphasis of task goals; 3) CQA was an engaging opportunity for self-reflection and learning; and 4) written communication logs were perceived as helpful in theory but too burdensome in practice. Findings from analyses of the communication logs included that most fellows' writing was brief and without substantial reflection. Many scholars have argued that communication theory can impact practice, but few have recognized the potential of theory and methods, such as MGT and CQA, as educational tools. Our findings demonstrate that MGT is a feasible and useful theoretical framework for improving communication skills among advanced trainees, and CQA fosters meaningful self-reflection about practice. Communication logs were not feasible or useful training tools in this context, but CQA workshops helped fulfill the goals of narrative reflection. Next steps are to implement this curriculum in more programs and measure changes in behavior acquisition and clinical care.

Cultural influences on internship development value and job pursuit intention: An exploratory comparison of student experiences in France and the United States

Internships are increasingly becoming an essential facet of a student's portfolio because of demonstrated linkages with employability and career opportunities. While undergraduate internships have expanded globally, most studies have examined the relationship between internship characteristics and student outcomes within a single country. In this cross-cultural study, we examine the generalizability of existing findings using survey data from 210 university students in France and the United States (U.S.). Results showed that in both countries the internship characteristics of supervisor support and mentoring, autonomy, and task goal clarity positively relate to student perceptions of the developmental value of their internship and job pursuit intention with the intern-host. However, the nature of these relationships varies, with U.S. students benefiting more from greater autonomy, while French students benefit more from increased supervisor mentoring. Contrary to expectations, increased task goal clarity led to poorer outcomes for French students. We discuss the implications of our findings for students and higher education institutions, intern-host organizations, and future cross-cultural research on internships.

IMC-PnG: Maximizing runtime performance and timing guarantee for imprecise mixed-criticality real-time scheduling

Mixed-Criticality (MC) systems have successfully overcome the limitation of traditional real-time systems based on pessimistic Worst-Case Execution Times (WCETs), by using different WCETs depending on different criticalities. One of the important yet unsolved problems of current MC systems is to achieve two goals (G1 and G2) for low-criticality tasks without compromising timing guarantees for high-criticality tasks: (G1) providing a certain (degraded) level of timing guarantees for all low-criticality tasks; (G2) while maximizing the fully-serviced (non-degraded) execution of low-criticality tasks. To address the problem, we propose IMC-PnG, an MC scheduling framework, which employs two salient features: a task-level virtual-deadline assignment under the imprecise computing model with efficient resource utilization (supporting G1), and an online scheduling algorithm that dynamically changes criticality levels of individual tasks at runtime (supporting G2). In simulation results with random workloads, we showed that IMC-PnG has up to 12.10% higher schedulability and up to 42.10% higher runtime performance (measured by the fully-serviced ratio of low-criticality tasks) than the existing approaches.

"Three-Wide Education" in the Field of College Moral Education Model and its Operating Mechanism

The fundamental of my country's education reform lies in the people of Lindu. "Three-wide education" is based on the task goals proposed by colleges and universities. It has important guiding significance for the exploration of the moral education model of colleges and universities. The basic connotation of the moral education model of colleges and universities is very rich under the field of "Sanquan Education". It adheres to the focus of education as the focus of the work, all members participate in the joint force, the whole process is effectively connected, and the linkage is comprehensive. Based on this, this article deeply interprets this connotation, combined with the outstanding realistic dilemma faced by the current moral education model of colleges and universities, trying to improve the moral education model of colleges and universities in multiple aspects to give full play to the role of moral education in colleges and universities, solve some long -term restriction of high -quality development of college education, Bottleneck problem.

Visual-Motor Coordination While Drifting Through the Corner of an Ice-Racing Track: A Case Study of an Expert and a Novice Driver

This case study investigated the visual-motor coordination of an expert and a novice driver during high-speed cornering on an ice-racing track. The frozen track imposes unique task constraints on drivers due to the loss of traction. We Examined the coordination structure employed by the drivers to stabilize task goals in such an uncertain environment. The eye tracker system collected data on eye movements, head rotation, and steering wheel rotation. Coherent patterns of eye-head-steering were evaluated through Mutual Information with a time delay. The results showed that both drivers were forced to deal with unstable, shaky steering under the task constraints of losing traction. The novice driver employed a control strategy that suppressed both head and steering wheel movements. The expert driver exhibited rhythmic head rotation, which may have a functional role in dealing with disturbances by generating stable movement patterns. This study highlights human flexibility and adaptability in response to challenging and uncertain environments. The perception-action system of the expert driver actively generated movements, forming a functional and complementary coordination.

Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System

Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute’s Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuromodulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.

Inferring control objectives in a virtual balancing task in humans and monkeys

Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal’s control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject’s control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.