The constraints-based approach to motor learning : Implications for a non-linear pedagogy in sport and physical education

Recently, a constraints- led approach has been promoted as a framework for understanding how children and adults acquire movement skills for sport and exercise (see Davids, Button & Bennett, 2008; Araújo et al., 2004). The aim of a constraints- led approach is to identify the nature of interacting constraints that influence skill acquisition in learners. In this chapter the main theoretical ideas behind a constraints- led approach are outlined to assist practical applications by sports practitioners and physical educators in a non- linear pedagogy (see Chow et al., 2006, 2007). To achieve this goal, this chapter examines implications for some of the typical challenges facing sport pedagogists and physical educators in the design of learning programmes.

Auditory spatial acuity approximates the resolving power of space-specific neurons

The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination.

Emergent task-specific object semantics through distributed experience networks

Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

Teaching motor racing engineering through real-life projects: benefits and challenges

Project-based learning (PBL) is widely used in engineering courses. The closer to real-life the project, the greater the relevance and depth of learning experienced by students. Formula Society of Automotive Engineering (FSAE) is a fine example of a team-based project modelled on real-life problems whereby each student team designs and builds a small race car for competitive evaluation. Queensland University of Technology (QUT) has participated in FSAE-Australia since 2004. Based on the success of the project, QUT has gone the additional step of introducing a motor-racing specialization (second major) to complement its mechanical engineering degree. In this paper, the benefits of teaching motor-racing engineering through real-life projects are presented together with a discussion of the challenges faced and how they have been addressed. In order to validate the authors' observations on the teaching approaches used, student feedback was solicited through QUT's online learning experience survey (LEX), as well as a customized paper-based survey. The results of the surveys are analysed and discussed in this paper.

Corneal markers of diabetic neuropathy

Diabetic neuropathy is a significant clinical problem that currently has no effective therapy, and in advanced cases, leads to foot ulceration and lower limb amputation. The accurate detection, characterization and quantification of this condition are important in order to define at-risk patients, anticipate deterioration, monitor progression, and assess new therapies This review evaluates novel corneal methods of assessing diabetic neuropathy. Two new non-invasive corneal markers have emerged, and in cross-sectional studies have demonstrated their ability to stratify the severity of this disease. Corneal confocal microscopy allows quantification of corneal nerve parameters and non-contact corneal esthesiometry, the functional correlate of corneal structure, assesses the sensitivity of the cornea. Both these techniques are quick to perform, produce little or no discomfort for the patient, and are suitable for clinical settings. Each has advantages and disadvantages over traditional techniques for assessing diabetic neuropathy. Application of these new corneal markers for longitudinal evaluation of diabetic neuropathy has the potential to reduce dependence on more invasive, costly, and time-consuming assessments, such as skin biopsy.

Factors effecting motor vehicle growth in Dhaka

Dhaka’s traffic is heterogeneous, both motorized (MT) and non-motorized (NMT) transport are common. Traffic congestion has become a part of city dwellers’ lives. This paper explores the factors for motor vehicle growth in Dhaka. The scope of the paper will be limited to literature review...

Pharmacological consequence of the A118G μ opioid receptor polymorphism on morphine-and fentanyl-mediated modulation of Ca2+ channels in humanized mouse sensory neurons

Background: The most common functional single nucleotide polymorphism of the human OPRM1 gene, A118G, has been shown to be associated with interindividual differences in opioid analgesic requirements, particularly with morphine, in patients with acute postoperative pain. The purpose of this study was to examine whether this polymorphism would modulate the morphine and fentanyl pharmacological profile of sensory neurons isolated from a humanized mouse model homozygous for either the 118A or 118G allele. Methods: The coupling of wild-type and mutant μ opioid receptors to voltage-gated Ca channels after exposure to either ligand was examined by employing the whole cell variant of the patch-clamp technique in acutely dissociated trigeminal ganglion neurons. Morphine-mediated antinociception was measured in mice carrying either the 118AA or 118GG allele. RESULTS:: The biophysical parameters (cell size, current density, and peak current amplitude potential) measured from both groups of sensory neurons were not significantly different. In 118GG neurons, morphine was approximately fivefold less potent and 26% less efficacious than that observed in 118AA neurons. On the other hand, the potency and efficacy of fentanyl were similar for both groups of neurons. Morphine-mediated analgesia in 118GG mice was significantly reduced compared with the 118AA mice. Conclusions: This study provides evidence to suggest that the diminished clinical effect observed with morphine in 118G carriers results from an alteration of the receptor's pharmacology in sensory neurons. In addition, the impaired analgesic response with morphine may explain why carriers of this receptor variant have an increased susceptibility to become addicted to opioids. © 2011 the American Society of Anesthesiologists, Inc. Lippincott Williams & Wilkins. Anesthesiology.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

A focus on risk compensation and its role in motor vehicle crashes

• What is risk compensation, and why is relevant to motor vehicle crashes? • Recent simulator work that revealed risk compensation • Current and future work on risk compensation

Induction motor load impact on power system eigenvalue sensitivity analysis

Load modelling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is parametric sensitivity analysis. A composite load model-based load sensitivity analysis framework is proposed. It enables comprehensive investigation into load modelling impacts on system stability considering the dynamic interactions between load and system dynamics. The effect of the location of individual as well as patches of composite loads in the vicinity on the sensitivity of the oscillatory modes is investigated. The impact of load composition on the overall sensitivity of the load is also investigated.