Representation Of Skills Research Articles

Functional somatotopy revealed across multiple cortical regions using a model of complex motor task

The primary motor cortex (M1) possesses a functional somatotopic structure—representations of adjacent within-limb joints overlap to facilitate coordination while maintaining discrete centers for individuated movement. We examined whether similar organization exists across other sensorimotor cortices. Twenty-four right-handed healthy subjects underwent functional magnetic resonance imaging (fMRI) while tracking complex targets with flexion/extension at right finger, elbow and ankle separately. Activation related to each joint at false discovery rate of 0.005 served as its representation across multiple regions. Within each region, we identified the center of mass (COM) for each representation, and the overlap between the representations of within-limb (finger and elbow) and between-limb joints (finger and ankle). Somatosensory (S1) and premotor cortices (PMC) demonstrated greater distinction of COM and minimal overlap for within- and between-limb representations. In contrast, M1 and supplementary motor area (SMA) showed more integrative somatotopy with higher sharing for within-limb representations. Superior and inferior parietal lobule (SPL and IPL) possessed both types of structure. Some clusters exhibited extensive overlap of within- and between-limb representations, while others showed discrete COMs for within-limb representations. Our results help to infer hierarchy in motor control. Areas such as S1 may be associated with individuated movements, while M1 may be more integrative for coordinated motion; parietal associative regions may allow switch between both modes of control. Such hierarchy creates redundant opportunities to exploit in stroke rehabilitation. The use of complex rather than traditionally used simple movements was integral to illustrating comprehensive somatotopic structure; complex tasks can potentially help to understand cortical representation of skill and learning-related plasticity.

360-Degree Feedback

Originally started during World War II by the Germans, and later implemented by the Esso Research and Engineering Company in the 1950’s, utilization of the 360-degree feedback model is increasing in popularity. In this model, qualitative or quantitative ratings are collected from designated individuals, which may include supervisors, subordinates, peers, and internal and/or external customers (Dessler, 2010). Proponents of this model contend that it allows for a clear representation of behaviors, leadership skills, strengths, and weaknesses so that the individual may create a plan for personal growth and development, thereby improving the company as a whole. Opponents, however, argue that this model typically does not provide accurate data and must consider too many variables to be successful. Regardless of these arguments, the 360 feedback model is a very important component within Human Resources with nearly all Global 1000 companies implementing some type of multi-rater feedback instrument to evaluate key contributors and managers.

Developmental trajectories of grey and white matter in dyscalculia

Abstract Developmental dyscalculia is a significant neural deficit with broad social impact. A number of techniques have been used to identify the brain basis of dyscalculia, and many of these have highlighted the role of the intraparietal sulci and a left fronto-parietal network in the representation of core number skills. These studies offer conflicting explanations of the neurobiological deficits associated with dyscalculia, and to date few studies have elucidated the timeline of cortical changes involved. Here we report a volumetric study comparing well-characterized dyscalculic learners aged from 8 to 14 years with tightly matched controls. Using automated cortical parcellation of anatomical MRI, we show that the posterior parietal and fronto-parietal systems in dyscalculia may undergo abnormal development during the pre-teenage and teenage years. As a result, the present study more clearly characterizes the underlying neural basis of dyscalculia than previous studies have hitherto achieved.

From action representation to action execution: exploring the links between cognitive and biomechanical levels of motor control.

Along with superior performance, research indicates that expertise is associated with a number of mediating cognitive adaptations. To this extent, extensive practice is associated with the development of general and task-specific mental representations, which play an important role in the organization and control of action. Recently, new experimental methods have been developed, which allow for investigating the organization and structure of these representations, along with the functional structure of the movement kinematics. In the current article, we present a new approach for examining the overlap between skill representations and motor output. In doing so, we first present an architecture model, which addresses links between biomechanical and cognitive levels of motor control. Next, we review the state of the art in assessing memory structures underlying complex action. Following we present a new spatio-temporal decomposition method for illuminating the functional structure of movement kinematics, and finally, we apply these methods to investigate the overlap between the structure of motor representations in memory and their corresponding kinematic structures. Our aim is to understand the extent to which the output at a kinematic level is governed by representations at a cognitive level of motor control.

Structural Summary Tree with Complete Path Representation for Intelligent Query of Social-Web Documents

 Abstract—Compiling documents in extensible markup language (XML) increasingly requires access to data services which provide both rapid response and the precise use of search engines. Efficient data service should be based on a skillful representation that can support low complexity and high precision search capabilities. In this paper, a novel complete path representation (CPR) associated with a modified inverted index is presented for the provision of efficient XML data services, where queries can be versatile in terms of predicates. CPR can completely preserve hierarchical information, and the new index is used to save semantic information. The CPR approach can provide template-based indexing for fast data search. An experiment is also conducted for the evaluation of the CPR approach.

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

A salient feature of human motor skill learning is the ability to exploit similarities across related tasks. In biological motor control, it has been hypothesized that muscle synergies, coherent activations of groups of muscles, allow for exploiting shared knowledge. Recent studies have shown that a rich set of complex motor skills can be generated by a combination of a small number of muscle synergies. In robotics, dynamic movement primitives are commonly used for motor skill learning. This machine learning approach implements a stable attractor system that facilitates learning and it can be used in high-dimensional continuous spaces. However, it does not allow for reusing shared knowledge, i.e., for each task an individual set of parameters has to be learned. We propose a novel movement primitive representation that employs parametrized basis functions, which combines the benefits of muscle synergies and dynamic movement primitives. For each task a superposition of synergies modulates a stable attractor system. This approach leads to a compact representation of multiple motor skills and at the same time enables efficient learning in high-dimensional continuous systems. The movement representation supports discrete and rhythmic movements and in particular includes the dynamic movement primitive approach as a special case. We demonstrate the feasibility of the movement representation in three multi-task learning simulated scenarios. First, the characteristics of the proposed representation are illustrated in a point-mass task. Second, in complex humanoid walking experiments, multiple walking patterns with different step heights are learned robustly and efficiently. Finally, in a multi-directional reaching task simulated with a musculoskeletal model of the human arm, we show how the proposed movement primitives can be used to learn appropriate muscle excitation patterns and to generalize effectively to new reaching skills.

Humanoid Robot Interactions by Motion Description Language and Dialogue

This paper describes the development of a system for facilitating humanoid robots to acquire sequence of movements by motion description and dialogue. The unique feature of our system is that we define a descriptive language and framework that allows the specification of humanoid motions and the representation of motor skills. We subsequently developed and tested a virtual reality simulation system that can execute the motion descriptive language. We then extended the system to allow humanoid robots to acquire motion descriptions through conversing with human. We implemented and tested the proposed system on the NAO humanoid robot. Our implementation includes a dialogue module that continues to update the encoded motion descriptions as the conversation advances and an action module that retrieves the acquired motion descriptions and direct the robot to perform the specified tasks.

From dynamic movement primitives to associative skill memories

In recent years, research on movement primitives has gained increasing popularity. The original goals of movement primitives are based on the desire to have a sufficiently rich and abstract representation for movement generation, which allows for efficient teaching, trial-and-error learning, and generalization of motor skills (Schaal 1999). Thus, motor skills in robots should be acquired in a natural dialog with humans, e.g., by imitation learning and shaping, while skill refinement and generalization should be accomplished autonomously by the robot. Such a scenario resembles the way we teach children and connects to the bigger question of how the human brain accomplishes skill learning. In this paper, we review how a particular computational approach to movement primitives, called dynamic movement primitives, can contribute to learning motor skills. We will address imitation learning, generalization, trial-and-error learning by reinforcement learning, movement recognition, and control based on movement primitives. But we also want to go beyond the standard goals of movement primitives. The stereotypical movement generation with movement primitives entails predicting of sensory events in the environment. Indeed, all the sensory events associated with a movement primitive form an associative skill memory that has the potential of forming a most powerful representation of a complete motor skill.

Assistive listening devices drive neuroplasticity in children with dyslexia.

Children with dyslexia often exhibit increased variability in sensory and cognitive aspects of hearing relative to typically developing peers. Assistive listening devices (classroom FM systems) may reduce auditory processing variability by enhancing acoustic clarity and attention. We assessed the impact of classroom FM system use for 1 year on auditory neurophysiology and reading skills in children with dyslexia. FM system use reduced the variability of subcortical responses to sound, and this improvement was linked to concomitant increases in reading and phonological awareness. Moreover, response consistency before FM system use predicted gains in phonological awareness. A matched control group of children with dyslexia attending the same schools who did not use the FM system did not show these effects. Assistive listening devices can improve the neural representation of speech and impact reading-related skills by enhancing acoustic clarity and attention, reducing variability in auditory processing.

A neurocomputational approach to automaticity in motor skill learning

Abstract Cognitive agents physically interacting with the world can best adapt to their task environments if they are able to learn motor skills from experience. Many cognitive architectures have focused on a single learning mechanism to accomplish such adaptation. Behavioral studies with humans, however, have shown that the acquisition of a motor skill generally occurs in two stages. In the initial stage, acquisition is performed via attention-demanding neural processes, producing a high cognitive load. This is followed by more fluent automatic processing, requiring less deliberation. Neuroscientific studies have since identified two relevant interacting neural systems, suggesting that the acquisition of a motor skill involves a transition from heavy dependence on a system involving cognitive control to only weak dependence on such a system. This cognitive control system, which includes the prefrontal cortex, is thought to be responsible for acquiring and manipulating declarative representations of skills. This frontal system is seen as modulating processing in a more automatic neural pathway, which develops procedural representations over time. In this paper, we propose a biologically plausible computational model of motor skill automaticity. This model offers a neurocomputational account of the translation of declarative into procedural knowledge during learning. In support of the model, we review some previously reported experimental results, and we demonstrate, through simulation, how the model provides a parsimonious explanation for these results. The model is seen as exemplifying a novel approach to motor skill learning in artificial agents.

'Knowledge Representation and Pattern Recognition Skills of Elite Adult and Youth Soccer Players'

This study investigated knowledge representation and pattern of play recognition skills of elite adult and youth soccer players, while participating in conditioned phases of play. Players (n = 16) participated in their own expertise group and verbal reports were transcribed and coded into concepts (Goals, Conditions, Actions) based on a modified model of protocol structure used for tennis by (McPherson & Kernodle 2007). A Mann Whitney test was used to analyse the mean scores of the participants for knowledge representation and a Chi Square test was performed using percentage scores to identify differences in the players’ ability to recognise patterns of play. The study showed that adult experts (n = 8) were able to generate more content and details, when verbalising their cognitive thought processes in game situations than youth (n = 8) elite players. The findings support previous research in that more experienced adult players are able to consistently call upon more developed long term memory whilst processing information with the existence of action plans and current event profiles. Differences were recorded in the percentage scores for players’ ability to recognise patterns of play, which provide evidence that elite youth players’ game-reading skills (pattern recognition) are as well developed as elite adults.

The Values of Water: Development Cultures and Indigenous Cultures in Highland Ecuador

This article examines the symbolic transformations and material consequences of an irrigation development project designed to empower indigenous peoples in Canar, Ecuador. It argues that the project deepened market society and reproduced colonialism more than it empowered indigenous peoples, but indigenous people found ways to ap- propriate project resources and embed the market in alternative principles of social life. Market society deepened through the neoliberal hegemony of international development policy and through the indigenous movement's incorporation of market rationalities. Colonialism recurred through hierarchical representations of knowledge and skills remi- niscent of long-standing stereotypes of natives, which local indigenous leaders internal- ized. Both processes urifolded through constructions of value arid acts of evaluation. The gap between the market ideal communicated in the irrigation development project and the conditions of actually existing markets that local indigenous people engaged after project closure limited the concrete empowerment of indigenous peoples. In 1998, Tucuy Canar Ayllucunapa Tantanacuy (Tucayta), an indigenous or- ganization in Ecuador's Canar Province, secured control of significant irrigation infrastructure. Citing this acquisition as empowerment, the organization's lead- ers asserted professional competence and market competitiveness, seemingly conforming to neoliberal principles that they had rejected four years earlier when protesting an agrarian law that subjected land access to market competition. By 1998, local indigenous leaders believed that they had discerned more success- ful ways to pursue aims and procure capabilities. In this article, I demonstrate that emergent cultures of development conditioned Tucayta's attainment of the Patococha irrigation system and labeled it a qualified success. I advance a cul- tural conception of development based on neo-Polanyian, anthropologica l, and postcolonial theory. I argue that the Patococha project deepened market society and reproduced coloniality more than it empowered indigenous peoples, but in- digenous people found ways to appropriate Patococha and embed the market in alternative projects of social life.'

Neuro-fuzzy-based skill learning for robots

SUMMARYEndowing robots with the ability of skill learning enables them to be versatile and skillful in performing various tasks. This paper proposes a neuro-fuzzy-based, self-organizing skill-learning framework, which differs from previous work in its capability of decomposing a skill by self-categorizing it into significant stimulus-response units (SRU, a fundamental unit of our skill representation), and self-organizing learned skills into a new skill. The proposed neuro-fuzzy-based, self-organizing skill-learning framework can be realized by skill decomposition and skill synthesis. Skill decomposition aims at representing a skill and acquiring it by SRUs, and is implemented by stages with a five-layer neuro-fuzzy network with supervised learning, resolution control, and reinforcement learning to enable robots to identify a sufficient number of significant SRUs for accomplishing a given task without extraneous actions. Skill synthesis aims at organizing a new skill by sequentially planning learned skills composed of SRUs, and is realized by stages, which establish common SRUs between two similar skills and self-organize a new skill from these common SRUs and additional new SRUs by reinforcement learning. Computer simulations and experiments with a Pioneer 3-DX mobile robot were conducted to validate the self-organizing capability of the proposed skill-learning framework in identifying significant SRUs from task examples and in common SRUs between similar skills and learning new skills from learned skills.

Learning to be fast: Gain accuracy with speed

Our recent neurophysiological findings provided evidence for collinear facilitation in detecting low-contrast Gabor patches (GPs) and for the abolishment of these collinear interactions by backward masking (BM) (Sterkin et al., 2008; Sterkin, Yehezkel, Bonneh, et al., 2009). We suggested that the suppression induced by the BM eliminates the collinear facilitation. Moreover, our recent study showed that training on a BM task overcomes the BM effect, hence, improves the processing speed (Polat, 2009). Here we applied training on detecting a target that is followed by BM in order to study whether reinforced facilitatory interactions can overcome the suppressive effects induced by BM. Event-Related Potentials (ERPs) were recorded before and after ten training sessions performed on different days. Low-contrast, foveal target GP was simultaneously flanked by two collinear high-contrast GPs. In the BM task, another identical mask was presented at different time-intervals (ISIs). Before training, BM induced suppression of target detection, at the ISI of 50ms, in agreement with earlier behavioral findings. This ISI coincides with the active time-window of lateral interactions. After training, our results show a remarkable improvement in all behavioral measurements, including percent of correct responses, sensitivity (d’), reaction time (RT) and the decision criterion for this ISI. The ERP results show that before training,BM attenuated the physiological markers of facilitation at the same ISI of 50ms, measured as the amplitude of the negative N1 peak (latency of 260ms). After the training, the sensory representation, reflected by P1 peak, has not changed, consistent with the unchanged physical parameters of the stimulus. Instead, the shorter latency (by 20ms, latency of 240ms) and the increased amplitude of N1 represent the development of faster and stronger facilitatory lateral interactions between the target and the collinear flankers. Thus, previously effective backward masking became ineffective in disrupting the collinear facilitation. Moreover, a high-amplitude late peak (P4, latency of 610–630ms) was not affected by training, however its high correlation with RT (95%) before training was significantly decreased (to 76%), consistent with a lower-level representation of a trained skill. We suggest that perceptual learning that strengthens collinear facilitation results in a faster processing speed.

Time-Limited Consolidation and Task Interference: No Direct Link

Perceptual skills improve with daily practice (Fahle and Poggio, 2002; Fine and Jacobs, 2002). Practice induces plasticity in task-relevant brain regions during an "offline" consolidation period thought to last several hours, during which initially fragile memory traces become stable (Karni, 1996; Dudai, 2004). Impaired retention of a task if followed by training in another task is considered evidence for the instability of memory traces during consolidation (Dudai, 2004). However, it remains unknown when after training memory traces become stable and resistant against interference, where in the brain the neuronal mechanisms responsible for interference are localized, and how these mechanisms produce interference. Here, we show in human participants strong interference between two visual skill-learning tasks for surprisingly long time intervals between training periods (up to 24 h). Interference occurred during asymptotic learning, but only when stimuli were similar between tasks. This supports a strong contribution to interference of low-level visual cortical areas (Karni and Bertini, 1997; Ahissar and Hochstein, 2004), where similar stimuli recruit overlapping neuronal populations. Our finding of stimulus-dependent and time-independent interference reveals a fundamental limit in cortical plasticity that constrains the simultaneous representation of multiple skills in a single neuronal population, rather than a time-limited consolidation process.

SIG 16 Perspectives Vol. 12, No. 3, October 2011

SIG 16 Perspectives Vol. 12, No. 3, October 2011

Practice makes transfer of motor skills imperfect

We investigated the practice-effects on motor skill transfer and the associated representational memory changes that occur during the within-practice and between-practice phases. In two experiments, participants produced extension-flexion movements with their dominant right arm for a limited or prolonged practice session arranged in either a single- or multi-session format. We tested the ability of participants to transfer the original pattern (extrinsic transformation) or the mirrored one (intrinsic transformation) to the non-dominant left arm, 10 min and 24 h after the practice sessions. Results showed that practice induces rapid motor skill improvements that are non-transferable irrespective of the amount of acquisition trials. Furthermore, the extrinsic component of the skill develops early and remains the dominant coding system during practice. Conversely, we found distinct between-practice memory changes: a limited practice induces an off-line development of the extrinsic component, whereas a prolonged practice session subserves the off-line development of the intrinsic component (experiment 2). We provided further evidence that the long-term representation of the motor skill also depends on the nature of the practice session itself: the parsing of practice into multiple sessions narrows the effector-transfer capacities in comparison to a single session (experiment 1). These findings yield theoretical and practical implications that are discussed in the context of recent motor skill learning models.

Knowledge and Skill Representations for Robotized Production

AbstractModel-based systems in control are a means to utilize efficiently human knowledge and achieve high performance. While models consisting of formalized knowledge are used during the engineering step, running systems usually do not contain a high-level, symbolic representation of the control and most of its properties, typically named numerical parameters. On a system level and beyond the plant data, there is also a need to represent the meaning of the data such that deployment and fault analysis could be augmented with partly automated inference based on the semantics of the data. To that end, we extended the formalized knowledge traditionally used in control to include the control purpose, engineering assumption, quality, involved state machines, and so on. We then represented the control semantics in a format that allows an easier extraction of information using querying and reasoning. It aims at making knowledge in control engineering reusable so that it can be shipped together with the control systems. We implemented prototypes that include automatic conversion of plant data from AutomationML into RDF triples, as well as the automated extraction of control properties, the conversion of parameters, and their storage in the same triple store. Although these techniques are standard within the semantic web community, we believe that our robotic prototypes for semantic control represent a novel approach.

The cognitive representation of a throwing technique in judo experts – Technological ways for individual skill diagnostics in high-performance sports

Objectives The paper addresses the cognitive skill representation of a judo technique and presents two examples on how to measure and interpret individual skill profiles based on these representations in high-performance sports. Method The cognitive skill representation of a throwing technique in high-level judo experts was tested with the Structure Dimension Analysis - Motorics (SDA-M). This method provides psychometric data on the mental structure and feature dimensions of movement representations in long-term memory. The cognitive units of such representation structures are so-called basic action concepts (BACs), which correspond to functionally meaningful body postures and sub-movements. Participants performed a hierarchical distance scaling (splitting task), in which they sorted a list of BACs according to their functional relevance in movement execution. Through a hierarchical cluster analysis, the SDA-M uncovered the cognitive structures of the throwing technique in participant’s long-term memory, and enabled the assessment of group and individual representations. Results Expert skill representations were organized in a distinctive hierarchical tree-like structure, which matched the functional and biomechanical demands of the task well. Also, insights about specific movement problems could be gained for two experts after assessing their individual structures. Conclusions The SDA-M method can be used as a diagnostic tool to measure individual skill representations, which helps to improve performance-related instructions and to optimize technical training routines in high-performance sports.

Representations of librarianship in the UK press

PurposeThe image of the library and information professional has been a source of professional anxiety for many years. The purpose of this paper is to investigate this long‐standing issue by studying the portrayal of librarianship in UK national newspapers during a period of rapid technological change. It also proposes to examine the representation of the professional role, determined by the skills and competencies depicted and the topics associated with librarianship.Design/methodology/approachThe approach takes the form of a content analysis of a sample of 264 newspaper articles taken from The Times and The Mirror between January 1, 1998, and December 31, 2008.FindingsThe findings reveal a lack of representation of skills and duties performed by librarians. The usefulness and relevance of those depicted are overshadowed by the reported value of libraries. When professional duties are depicted, however, the results appear positive: librarians were seen as having an expert knowledge of content, technological competence and skills in collection development. The reporting of negative behavioural traits was infrequent and it was found that newspapers were not perpetuating negative stereotypes.Research limitations/implicationsAlthough The Times and The Mirror are important publications in terms of circulation, their depiction of the library and information profession does not form a complete picture of the representation of librarianship in the UK press.Originality/valueThe paper contributes to debates about the image of the profession, and raises awareness about the skills and competencies that practitioners and professional bodies need to promote for the library and information profession to flourish.