Computational models and motor learning paradigms: Could they provide insights for neuroplasticity after stroke? An overview

Computational approaches for modelling the central nervous system (CNS) aim to develop theories on processes occurring in the brain that allow the transformation of all information needed for the execution of motor acts. Computational models have been proposed in several fields, to interpret not only the CNS functioning, but also its efferent behaviour. Computational model theories can provide insights into neuromuscular and brain function allowing us to reach a deeper understanding of neuroplasticity. Neuroplasticity is the process occurring in the CNS that is able to permanently change both structure and function due to interaction with the external environment. To understand such a complex process several paradigms related to motor learning and computational modeling have been put forward. These paradigms have been explained through several internal model concepts, and supported by neurophysiological and neuroimaging studies. Therefore, it has been possible to make theories about the basis of different learning paradigms according to known computational models. Here we review the computational models and motor learning paradigms used to describe the CNS and neuromuscular functions, as well as their role in the recovery process. These theories have the potential to provide a way to rigorously explain all the potential of CNS learning, providing a basis for future clinical studies

Working memory capacity limits motor learning when implementing multiple instructions.

Although it is generally accepted that certain practice conditions can place large demands on working memory (WM) when performing and learning a motor skill, the influence that WM capacity has on the acquisition of motor skills remains unsubstantiated. This study examined the role of WM capacity in a motor skill practice context that promoted WM involvement through the provision of explicit instructions. A cohort of 90 children aged 8 to 10 years were assessed on measures of WM capacity and attention. Children who scored in the lowest and highest thirds on the WM tasks were allocated to lower WM capacity (n D 24) and higher WM capacity (n D 24) groups, respectively. The remaining 42 participants did not participate in the motor task. The motor task required children to practice basketball shooting for 240 trials in blocks of 20 shots, with pre- and post-tests occurring before and after the intervention. A retention test was administered 1 week after the post-test. Prior to every practice block, children were provided with five explicit instructions that were specific to the technique of shooting a basketball. Results revealed that the higher WM capacity group displayed consistent improvements from pre- to post-test and through to the retention test, while the opposite effect occurred in the lower WM capacity group. This implies that the explicit instructions had a negative influence on learning by the lower WM capacity children. Results are discussed in relation to strategy selection for dealing with instructions and the role of attention control

Exploring the Neural Mechanisms of Physics Learning

This dissertation presents a series of neuroimaging investigations and achievements that strive to deepen and broaden our understanding of human problem solving and physics learning. Neuroscience conceives of dynamic relationships between behavior, experience, and brain structure and function, but how neural changes enable human learning across classroom instruction remains an open question. At the same time, physics is a challenging area of study in which introductory students regularly struggle to achieve success across university instruction. Research and initiatives in neuroeducation promise a new understanding into the interactions between biology and education, including the neural mechanisms of learning and development. These insights may be particularly useful in understanding how students learn, which is crucial for helping them succeed. Towards this end, we utilize methods in functional magnetic resonance imaging (fMRI), as informed by education theory, research, and practice, to investigate the neural mechanisms of problem solving and learning in students across semester-long University-level introductory physics learning environments. In the first study, we review and synthesize the neuroimaging problem solving literature and perform quantitative coordinate-based meta-analysis on 280 problem solving experiments to characterize the common and dissociable brain networks that underlie human problem solving across different representational contexts. Then, we describe the Understanding the Neural Mechanisms of Physics Learning project, which was designed to study functional brain changes associated with learning and problem solving in undergraduate physics students before and after a semester of introductory physics instruction. We present the development, facilitation, and data acquisition for this longitudinal data collection project. We then perform a sequence of fMRI analyses of these data and characterize the first-time observations of brain networks underlying physics problem solving in students after university physics instruction. We measure sustained and sequential brain activity and functional connectivity during physics problem solving, test brain-behavior relationships between accuracy, difficulty, strategy, and conceptualization of physics ideas, and describe differences in student physics-related brain function linked with dissociations in conceptual approach. The implications of these results to inform effective instructional practices are discussed. Then, we consider how classroom learning impacts the development of student brain function by examining changes in physics problem solving-related brain activity in students before and after they completed a semester-long Modeling Instruction physics course. Our results provide the first neurobiological evidence that physics learning environments drive the functional reorganization of large-scale brain networks in physics students. Through this collection of work, we demonstrate how neuroscience studies of learning can be grounded in educational theory and pedagogy, and provide deep insights into the neural mechanisms by which students learn physics

Visual memory improvement in recognition

Fluid intelligence and working memory has been improved by training on a visual working memory n-back task (Jaeggi, Buschkuehl, Jonides & Perrig, 2008). The present study investigated whether n-back training can improve visual memory using a test of visual recognition. A sample of 47 participants were trained for 20 days on either the single n-back task (n = 26) or a general knowledge and vocabulary task (n = 21). The results showed that training using the single n-back task did not significantly increase scores on a test of visual recognition when compared with general knowledge and vocabulary training. However, when initial scores were compared with final scores at completion of the training period, participants who had a high gain in scores on the vocabulary training task improved their visual recognition scores significantly more than those participants who had a low gain in scores on the vocabulary training task. This pattern was not repeated for those participants who were trained in the n-back task. During debrief, participants in the high gain vocabulary training group described shape recognition strategies which they used to improve their performance. It was concluded that the vocabulary task was more successful at training visual recognition than the n-back task which suggested the vocabulary task had a confounding effect on the results of this experiment

Scaling Up with Radically Embodied Cognition

Radically embodied cognitive science (REC) is typically concerned with basic cognition such as perception and action. However, complex cognition or higher-order cognition is difficult to explain for REC, as these theories eschew traditional representational explanations. This leaves REC with a scaling-up problem. In this dissertation I will explore options for REC to fix its scaling-up problem. I am specifically interested in autonoetic cognition, which is the ability to remember and imagine objects and events in the way they would be experienced if they were immediately present to be perceived. I contend that a simulationist account provides many of th necessary conceptual tools for understanding autonoetic cognition from a REC perspective. Furthermore, simulationist accounts are generally useful, as they are suggestive of a way to understand the observed neural activity and can be used to make empirical predictions. I will examine different simulationist theories in order to determine whether or not they can cohere with REC and help solve the scaling-up problem. Eventually I will argue that the REC commitment to reject representations makes the scaling-up problem insurmountable at this time

カイワ ダイアログ アンショウ ニ ジュウジ サセル ガイコクゴ シドウホウ ガ スピｰキングジ ノ テイケイ ヒョウゲン ノ シヨウ ト アンキ ガクシュウ ニ オヨボス エイキョウ ニ カンスル キソ ケンキュウ

PDF/A formatsAccess: via World Wide Web東京外国語大学大学院総合国際学研究科博士 (学術) 論文 (2016年4月)Author's thesis (Ph.D)--Tokyo University of Foreign Studies, 2016博甲第214号Bibliography: p. 183-195Summary in English and Japanese東京外国語大学 (Tokyo University of Foreign Studies)博士 (学術

Designing tabletop applications for collaboration in non-collaborative learning tasks in the classroom : learning persuasive writing

PhD ThesisLearning in a face to face collaborative setting can have many benefits, such as leveraging differing peer proficiency to obtain an outcome not reachable by the individuals involved. Including expertise provided by teachers decreases this gap between potential and current ability, while also providing opportunity for the expert to impart timely and appropriate assistance to the learners. In the fields of Human Computer Interaction and Educational Technology, digital tabletops have come to the fore as a medium for facilitating small groups of collaborative learners, and suitable applications can provide at least some of the support that the teacher’s expertise would in the learning process. Previously, most explorations in this area have concentrated on learning tasks that are already collaborative in nature, and have focused on single group deployments, and usually in controlled settings such as a research lab. This thesis focuses on two main aims: (i) investigating the design of such applications, and how learning tasks not normally considered collaborative, such as Persuasive Extended Writing, might be adapted to a digital tabletop mediated collaborative learning task; and (ii), how to expand this application from a single group to a classroom scenario, and overcoming all the challenges that an “in the wild” deployment of this kind might entail. A review of previous literature on collaborative learning and collaborative learning technology inform a learner centred design process of an application for the collaborative learning of Persuasive Extended Writing. This design process was conducted with three groups of three learners aged 13 – 15 in the lab. Based on this investigation of the literature around collaborative learning, there is a potential learning impact from allowing collaboration in a usually non-collaborative learning setting. The application incorporates factors designed to elicit collaborative behaviours, such as visuospatial representations and decision points. The work then sets about identifying and evaluating these collaborative behaviours, with a view that they are potentially in line with this ultimate learning goal. iii The Collocated Collaborative Writing application (CCW) is deployed and evaluated in an “in the wild” classroom setting. This involved two studies in real classrooms in schools, with eight digital tabletops allowing for a class-wide deployment. In the first study, participants were students of mixed ability, year 8 (aged 13-14), studying English, Geography and History. In the second study, participants were mixed ability year 8 students (aged 13-14) studying English. Studies were facilitated by teachers who had created the material for the studies based on their current teaching and curriculum. The process identified the issues and challenges involved in this kind of “in the wild” deployment. The lessons learned from this process about the differing expectations of the stakeholders involved in the first study informed the second deployment. A combination of addressing the issues directly, forming a more equal partnership with the school and teacher, and differences in culture between the schools lead to a study in which the collaborative writing application is evaluated. There are two main contributions of this work. Firstly, a set of design guidelines derived from lessons learned during the design process. Their intention is to assist in the process of making a normally non-collaborative learning task into a collaborative one, by exploiting affordances of the technology. The second contribution comes from lessons learned from two “in the wild” classroom studies. It outlines a deeper understanding of how this kind of application can be extended to the classroom by gaining insight into expectations of the parties involved, understanding the culture of the school and making the process a partnership rather than an imposition. The work also evaluated the Collaborative Writing Application in terms of the type and quality of the collaborative behaviours of the participants, and how they changed over time, as well as the adoption of the technology by the teacher, eventually being seen as a tool for their own agenda rather than an external element in the classroom

Decoding intentions of self and others from fMRI activity patterns

Previous studies using multi-voxel pattern analysis have decoded the content of participants' delayed intentions from patterns of fMRI data. Here we investigate whether this technique can be used to decode not only participants' own intentions, but also their representation of the intentions held by other people. In other words: if Sam is thinking about Hoki, can we decode the content of Hoki's intention by scanning Sam's brain? We additionally distinguished two components of intentions: action-plans versus goals, and included novel control analyses that allowed us to distinguish intending an outcome from simply expecting it to occur or simulating its consequences. Regions of frontal, parietal, and occipital cortex contained patterns from which it was possible to decode intentions of both self and other. Furthermore, crossclasification between self and other was possible, suggesting overlap between the two. Control analyses suggested that these results reflected visuo-spatial processes by which intentions were generated in our paradigm, rather than anything special about intentions per se. There was no evidence for any representation of intentions as mental states distinct from visuospatial processes involved in generating their content and/or simulating their outcomes. These findings suggest that the brain activity patterns decoded in intention-decoding fMRI studies may reflect domain-general processes rather than being intention-specific

Study protocol and rationale of the “Cogniaction project” a cross-sectional and randomized controlled trial about physical activity, brain health, cognition, and educational achievement in schoolchildren

Background: Education and health are crucial topics for public policies as both largely determine the future wellbeing of the society. Currently, several studies recognize that physical activity (PA) benefits brain health in children. However, most of these studies have not been carried out in developing countries or lack the transference into the education field. The Cogni-Action Project is divided into two stages, a cross-sectional study and a crossover-randomized trial. The aim of the first part is to establish the associations of PA, sedentarism, and physical fitness with brain structure and function, cognitive performance and academic achievement in Chilean schoolchildren (10–13 years-old). The aim of the second part is to determinate the acute effects of three PA protocols on neuroelectric indices during a working memory and a reading task. Methods: PA and sedentarism will be self-reported and objectively-assessed with accelerometers in a representative subsample, whilst physical fitness will be evaluated through the ALPHA fitness test battery. Brain structure and function will be assessed by magnetic resonance imaging (MRI) in a randomized subsample. Cognitive performance will be assessed through the NeuroCognitive Performance Test, and academic achievement by school grades. In the second part 32 adolescents (12–13 year-old) will be cross-over randomized to these condition (i) “Moderate-Intensity Continuous Training” (MICT), (ii) “Cooperative High-Intensity Interval Training” (C-HIIT), and (iii) Sedentary condition. Neuroelectric indices will be measures by electroencephalogram (EEG) and eye-tracking, working memory by n-back task and reading comprehension by a reading task