Metacognitive control and optimal learning

The notion of optimality is often invoked informally in the literature on metacognitive control. We provide a precise formulation of the optimization problem and show that optimal time allocation strategies depend critically on certain characteristics of the learning environment, such as the extent of time pressure, and the nature of the uptake function. When the learning curve is concave, optimality requires that items at lower levels of initial competence be allocated greater time. On the other hand, with logistic learning curves, optimal allocations vary with time availability in complex and surprising ways. Hence there are conditions under which optimal strategies will be relatively easy to uncover, and others in which suboptimal time allocation might be expected. The model can therefore be used to address the question of whether and when learners should be able to exercise good metacognitive control in practice.     

On the optimal degree of fluctuations in practice for motor learning

In human movement science, it is widely accepted that random practice generally enhances complex motor-skill learning compared to repetitive practice. In two experiments, a particular variability-related concept is put to empirical test, namely the concept of differencial learning (DL), which assumes (i) that learners should not be distracted from task-space exploration by corrections, and (ii) that learning is facilitated by large inter-trial fluctuations. In both experiments, the advantage of DL over repetitive learning was not statistically significant. Moreover, learning was more pronounced when participants either received corrections in addition to DL (Exp. 1) or practiced in an order in which differences between consecutive trials were relatively small (Exp. 2). These findings suggest that the positive DL effects reported in literature cannot be attributed to the reduction of feedback or to the increase of inter-trial fluctuations. These results are discussed in the light of the structural-learning approach and the two-state model of motor learning in which structure-related learning effects are distinguished from the capability to adapt to current changes.     

Stiffness as a control variable in motor performance

In the experiments described in this article we investigated the control of stiffness of the effector system in relation to parameters of the movement. If the velocity of a movement is chosen, it appears that at the same time the stiffness of the effector system is set to a preferred value. By changing the instruction given to the subject it is possible to change the relationship between velocity and stiffness without changing the kinematic parameters of the movement.Finally, the changes of stiffness and velocity in a learning process are studied. In conformity with what might be expected on intuitive grounds, it is found that velocity increases spontaneously during learning while stiffness decreases. The results are discussed in connection with the generation of motor programmes.     

Bio-inspired cognitive model of motor learning by imitation

Learning, and even more so by imitation, is an essential Cognitive Functions because it is carried out throughout life and allows us to adapt our behaviors from other beings through observation. In this work, we propose a model, and implementation of the cognitive function of imitation motor learning (IML), based on psychological and neuroscientific evidence. According to the evidence, learning by imitation includes imitation of action and imitation of action over an object sub-processes. The imitation of action consists of the movement of the limbs. The imitation of action over an object consists of the interaction with an object within the environment. We achieve an implementation of the proposed model for IML and endow a virtual entity with it. In order to validate the proposal, we use a case study to analyze the sub-processes performance. From results, we conclude that both imitation of action and imitation of action over an object sub-processes play an essential role in getting the agent to interact with stimuli within the environment.     

Application of motor learning principles to complex surgical tasks: searching for the optimal practice schedule

Practice of complex tasks can be scheduled in several ways: as whole-task practice or as practice of the individual skills composing the task in either a blocked or a random order. The authors used those 3 schedules to study 18 participants' learning of an orthopedic surgical task. They assessed learning by obtaining expert evaluation of performance and objective kinematic measures before, immediately after, and 1 week after practice (transfer test). During acquisition, the blocked group showed superior performance for simple skills but not for more complex skills. For the expert-based measures of performance, all groups improved from pretest to posttest and remained constant from posttest to transfer. Measures of the final product showed that the whole-practice group's outcomes were significantly better than those of the random group on transfer. All groups showed better efficiency of motions in the posttest than in the pretest. Those measures were also poorer on the transfer test than on the posttest. The present evidence does not support the contextual interference effect--hypothetically, because of the inherent cognitive effort effect associated with some of the component skills. The authors recommend that surgical tasks composed of several discrete skills be practiced as a whole. The results of this study demonstrate the importance of critically appraising basic theories in applied environments.     

Methodology for motor learning: a paradigm for kinematic feedback

Knowledge of results (KR)--information feedback about goal achievement--has been one of the most extensively examined variables in motor learning. In most natural movement learning situations, however, instructors more common]y provide augmented information regarding various kinematic or kinetic aspects of the movement pattern itself (sometimes termed knowledge of performance, KP). But despite the inherent interest in kinematic feedback, several factors reviewed here have operated to inhibit its study, the most important of which has been the lack of a suitable laboratory task and paradigm. The limitations of earlier paradigms have concerned (a) the use of overly simple motor behaviors, probably to minimize the problems in kinematic measurement, (b) the tendency for the environmental goal or the task to be isomorphic with the kinematic pattern, and (c) thc failure to use transfer or retention tests as measures of learning effects of the feedback manipulations. In this article, we describe our efforts to create a new paradigm for kinematic feedback, the rationale for its development, and the details of its operation. Finally, we provide evidence that the task and paradigm are sensitive to manipulations of kinematic feedback, providing some assurance that the paradigm can potentially answer future research questions about the role of kinematic feedback for learning.     

The automaticity of complex motor skill learning as a function of attentional focus

The present experiment was designed to test the predictions of the constrained-action hypothesis. This hypothesis proposes that when performers utilize an internal focus of attention (focus on their movements) they may actually constrain or interfere with automatic control processes that would normally regulate the movement, whereas an external focus of attention (focus on the movement effect) allows the motor system to more naturally self-organize. To test this hypothesis, a dynamic balance task (stabilometer) was used with participants instructed to adopt either an internal or external focus of attention. Consistent with earlier experiments, the external focus group produced generally smaller balance errors than did the internal focus group and responded at a higher frequency indicating higher confluence between voluntary and reflexive mechanisms. In addition, probe reaction times (RTs) were taken as a measure of the attention demands required under the two attentional focus conditions. Consistent with the hypothesis, the external focus participants demonstrated lower probe RTs than did the internal focus participants, indicating a higher degree of automaticity and less conscious interference in the control processes associated with the balance task.     

Modular motor learning

An interesting theory of sensorimotor control has been recently extended and simulated. The simulation can learn to control an arm in several mutually exclusive 'contexts', situations where the arm carries one of four objects with different mechanical properties. It provides a good theoretical framework for testing biological motor systems.     

Memoirs of a locust: Density-dependent behavioral change as a model for learning and memory

A locust outbreak is a stupendous natural phenomenon that remains in the memory of whoever has been lucky (or unlucky) enough to witness it. Recent years have provided novel and important insights into the neurobiology of locust swarming. However, the central nervous system processes that accompany and perhaps even lie at the basis of locust phase transformation are still far from being fully understood. Our current work deals with the memory of a locust outbreak from a new perspective: that of the individual locust. We take locust density-dependent phase transformation – a unique example of extreme behavioral plasticity, and place it within the context of the accepted scheme of learning and memory. We confirm that a short time period of exposure to a small crowd of locusts is sufficient to induce a significant behavioral change in a previously solitary locust. Our results suggest that part of the behavioral change is due to long-term habituation of evasive and escape responses. We further demonstrate that the memory of a crowding event lasts for at least 24 h, and that this memory is sensitive to a protein synthesis blocker. These findings add much to our understanding of locust density-dependent phase polyphenism. Furthermore, they offer a novel and tractable model for the study of learning and memory-related processes in a very distinctive behavioral context.     

Questioning implicit motor learning as instantiated by the pursuit-tracking task

The effect of concurrent visual feedback on the implicit learning of repeated segments in a task of pursuit tracking has been tested. Although this feedback makes it possible to regulate the positional error during the movement, it could also induce negative guidance effects. To test this hypothesis, a first set of participants (N?=?42) were assigned to two groups, which performed either the standard pursuit-tracking task based on the experimental paradigm of Pew (1974 Pew, R. W. 1974. Levels of analysis in motor control. Brain Research, 71: 393–400. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; group F-ST), or a task called “movement reproduction” in which the feedback was suppressed (group noF-ST). A second set of participants (N?=?26) performed in the same feedback condition groups but in a dual-task situation (F-DT and noF-DT; Experiment 2). The results appear to confirm our predictions since the participants in groups without feedback, contrary to those in groups with feedback, succeeded with practice in differentiating their performances as a function of the nature of the segments (repeated or nonrepeated) both in simple (Experiment 1) and in dual-task (Experiment 2) situations. These experiments indicate that the feedback in the pursuit-tracking task induces a guidance function potentially resulting in an easiness tracking that prevents the participants from learning the repetition.     

Questioning implicit motor learning as instantiated by the pursuit-tracking task

The effect of concurrent visual feedback on the implicit learning of repeated segments in a task of pursuit tracking has been tested. Although this feedback makes it possible to regulate the positional error during the movement, it could also induce negative guidance effects. To test this hypothesis, a first set of participants (N=42) were assigned to two groups, which performed either the standard pursuit-tracking task based on the experimental paradigm of Pew ( 1974 ; group F-ST), or a task called "movement reproduction" in which the feedback was suppressed (group noF-ST). A second set of participants (N=26) performed in the same feedback condition groups but in a dual-task situation (F-DT and noF-DT; Experiment 2). The results appear to confirm our predictions since the participants in groups without feedback, contrary to those in groups with feedback, succeeded with practice in differentiating their performances as a function of the nature of the segments (repeated or nonrepeated) both in simple (Experiment 1) and in dual-task (Experiment 2) situations. These experiments indicate that the feedback in the pursuit-tracking task induces a guidance function potentially resulting in an easiness tracking that prevents the participants from learning the repetition.     

Mechanical efficiency and metabolic cost as measures of learning a novel gross motor task

"Efficiency, " or economy of movement with respect to energy expended in achieving the goal of the task, is implicit in many definitions of skilled performance. This study examined changes in mechanical efficiency and transport efficiency on a novel gross motor skill. The subjects were 5 physically fit adult males who were asked to perform 20 3-min trials walking on hands and feet (crawling) on a motor-driven treadmill at constant speed (0.76 m/s). Transport efficiency, the metabolic cost of transporting the body mass a given distance at constant speed, improved significantly over practice trials. Mechanical efficiency, derived from the mechanical power output of individual body segments, showed an overall improvement of 13.7% by the last day of practice. Even though this improvement was not statistically significant it appears to be greater than that expected due to physiological training effects. The efficiency measures correlated significantly with changes in limb kinematics. It was concluded that with practice subjects tailored their movement pattern to produce energy efficient adaptations to task constraints. These findings provide empirical support for theoretical perspectives that have emphasized biological principles in the organization of motor coordination and control.     

Model learning for robot control: a survey

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.