Littérature scientifique sur le sujet « Motor learning and execution »
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Articles de revues sur le sujet "Motor learning and execution"
Diedrichsen, Jörn, et Katja Kornysheva. « Motor skill learning between selection and execution ». Trends in Cognitive Sciences 19, no 4 (avril 2015) : 227–33. http://dx.doi.org/10.1016/j.tics.2015.02.003.
Texte intégralTorriero, Sara, Massimiliano Oliveri, Giacomo Koch, Emanuele Lo Gerfo, Silvia Salerno, Fabio Ferlazzo, Carlo Caltagirone et Laura Petrosini. « Changes in Cerebello-motor Connectivity during Procedural Learning by Actual Execution and Observation ». Journal of Cognitive Neuroscience 23, no 2 (février 2011) : 338–48. http://dx.doi.org/10.1162/jocn.2010.21471.
Texte intégralJäger, Anna-Thekla P., Julia M. Huntenburg, Stefanie A. Tremblay, Uta Schneider, Sophia Grahl, Julia Huck, Christine L. Tardif et al. « Motor sequences ; separating the sequence from the motor. A longitudinal rsfMRI study ». Brain Structure and Function 227, no 3 (27 octobre 2021) : 793–807. http://dx.doi.org/10.1007/s00429-021-02412-7.
Texte intégralTorriani-Pasin, Camila, Gisele Carla dos Santos Palma, Cristiane Matsumoto Jakabi, Cinthya Walter, Andrea Michele Freudenheim et Umberto César Correa. « Motor Learning of a cognitive-motor task after stroke ». Revista Brasileira de Educação Física e Esporte 34, no 1 (4 juin 2020) : 1–9. http://dx.doi.org/10.11606/1807-5509202000010001.
Texte intégralTorriani-Pasin, Camila, Gisele Carla dos Santos Palma, Cristiane Matsumoto Jakabi, Cinthya Walter, Andrea Michele Freudenheim et Umberto César Correa. « Motor Learning of a cognitive-motor task after stroke ». Revista Brasileira de Educação Física e Esporte 34, no 1 (4 juin 2020) : 1–9. http://dx.doi.org/10.11606/issn.1981-4690.v34i1p1-9.
Texte intégralDomingues, Clayton Amaral, Sergio Machado, Emerson Garcia Cavaleiro, Vernon Furtado, Mauricio Cagy, Pedro Ribeiro et Roberto Piedade. « Alpha absolute power : motor learning of practical pistol shooting ». Arquivos de Neuro-Psiquiatria 66, no 2b (juin 2008) : 336–40. http://dx.doi.org/10.1590/s0004-282x2008000300010.
Texte intégralSobierajewicz, Jagna, Sylwia Szarkiewicz, Anna Przekoracka-Krawczyk, Wojciech Jaśkowski et Rob H. J. van der Lubbe. « To What Extent Can Motor Imagery Replace Motor Execution While Learning a Fine Motor Skill ? » Advances in Cognitive Psychology 12, no 4 (31 décembre 2016) : 178–91. http://dx.doi.org/10.5709/acp-0197-1.
Texte intégralStoter, Arjan J. R., Erik J. A. Scherder, Yvo P. T. Kamsma et Theo Mulder. « Rehearsal Strategies during Motor-Sequence Learning in Old Age : Execution vs Motor Imagery ». Perceptual and Motor Skills 106, no 3 (juin 2008) : 967–78. http://dx.doi.org/10.2466/pms.106.3.967-978.
Texte intégralAriani, Giacomo, et Jörn Diedrichsen. « Sequence learning is driven by improvements in motor planning ». Journal of Neurophysiology 121, no 6 (1 juin 2019) : 2088–100. http://dx.doi.org/10.1152/jn.00041.2019.
Texte intégralCho, Nam Jun, Sang Hyoung Lee, Jong Bok Kim et Il Hong Suh. « Learning, Improving, and Generalizing Motor Skills for the Peg-in-Hole Tasks Based on Imitation Learning and Self-Learning ». Applied Sciences 10, no 8 (15 avril 2020) : 2719. http://dx.doi.org/10.3390/app10082719.
Texte intégralThèses sur le sujet "Motor learning and execution"
Marchant, David Christopher. « The effects of internally and externally directed attention during motor skill execution and learning ». Thesis, University of Hull, 2005. http://hydra.hull.ac.uk/resources/hull:11168.
Texte intégralKo, Raymond. « The Role of the Basal Ganglia in Executing and Learning Complex Motor Sequences ». Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493272.
Texte intégralBiology, Organismic and Evolutionary
Parziale, Antonio. « A neurocomputational model of reaching movements ». Doctoral thesis, Universita degli studi di Salerno, 2016. http://hdl.handle.net/10556/2341.
Texte intégralHow the brain controls movement is a question that has fascinated researchers from different areas as neuroscience, robotics and psychology. To understand how we move is not only an intellectual challenge, but it is important for finding new strategies for nursing people with movement diseases, for rehabilitation and to develop new robotic technology. While there is an agreement about the role of the primary motor cortex (M1) in the execution of voluntary movements, it is still debated what (and how) is encoded by the neural activity of the motor cortex. To unveil the "code" used for executing voluntary movements we investigated the interaction between the motor cortex and the spinal cord, the main recipient of the descending signals departing from M1 neurons. In particular, the research presented in this thesis aims at understanding how primary motor cortex and spinal cord cooperate to execute a reaching movement, and whether a modular organization of the spinal cord can be exploited for controlling the movement. On the basis of physiological studies about the primary motor cortex organization, we have hypothesized that this brain area encodes both movement's parameters and patterns of muscle activation. We argue that the execution of voluntary movements results from the cooperation of different clusters of neurons distributed in the rostral and caudal regions of primary motor cortex, each of which represents different aspects of the ongoing movement. In particular, kinetic aspects of movement are directly represented by the caudal part of primary motor cortex as activations of alpha motoneurons, while kinematic aspects of the movement are encoded by the rostral region and are translated by spinal cord interneurons into alpha motoneurons activation. The population of corticomotoneuron (CM) cells in the caudal part of M1 creates muscle synergies for a direct control of muscle activity, useful to execute highly novel skills that require a direct control of multijoint and single joint movements by the central nervous system (CNS). On the other side, clusters of neurons in the rostral M1 are devoted to the activation of different subpopulations of interneurons in the spinal cord organized in functional modules. Each spinal module implements hardwired muscle synergies regulating the activity of a subset of muscles working around one or more joints. The way a module regulates the muscles activations is related to its structural properties. One area recruits the hard-wired motor primitives hosted in the spinal cord as spatiotemporal synergies, while the other one has direct access to the alpha motoneurons and may build new synergies for the execution of very demanding movements. The existence of these two areas regulating directly and indirectly the muscle activity can explain the controversy about what kind of parameter is encoded by the brain. In order to validate our conjecture about the coexistence of an explicit representation of both kinetic and kinematics aspects of the movement, we have developed and implemented the computational model of the spinal cord and its connections with supraspinal brain. The model incorporates the key anatomical and physiological features of the neurons in the spinal cord (interneurons Ia, Ib and PN and Renshaw cells, and their interconnections). The model envisages descending inputs coming from both rostral and caudal M1 motor cortex and cerebellum (through the rubro- and reticulo-spinal tracts), local inputs from both Golgi tendon organs and spindles, and its output is directed towards alfa motoneurons, which also receive descending inputs from the cortex and local inputs from spindles. The musculoskeletal model used in this study is a one degree-of-freedom arm whose motion is restricted to the extension/flexion of the elbow. The musculoskeletal model includes three muscles: Biceps Short, Brachialis and Triceps Lateral. Our simulations show that the CNS may produce elbow flexion movements with different properties by adopting different strategies for the recruitment and the modulation of interneurons and motoneurons. The results obtained using our computational model confirm what has been hypothesized in literature: modularity may be the organizational principle that the central nervous system exploits in motor control. In humans, the central nervous system can execute motor tasks by recruiting the motor primitives in the spinal cord or by learning new collections of synergies essential for executing novel skills typical of our society. To get more insights about how brain encodes movements and to unveil the role played by the different areas of the brain we verified if the movement generated by our model satisfied the trade-off between speed and accuracy predicted by the Fitts’ law. An interesting result is that the speed-accuracy tradeoff does not follow from the structure of the system, that is capable of performing fast and precise movements, but arises from the strategy adopted to produce faster movements, by starting from a prelearned set of motor commands useful to reach the target position and by modifying only the activations of alfa motoneurons. These results suggest that the brain may use the clusters of neurons in the rostral M1 for encoding the direction of the movement and the clusters of CM cells in the caudal M1 for regulating the tradeoff between speed and accuracy. The simulation performed with our computational model have shown that the activation of an area cannot exclude the activation of the other one but, on the contrary, both the activations are needed to have a simulated behaviour that fits the real behavior. [edited by Author]
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Pompéu, José Eduardo. « Melhora funcional de pacientes com doença de Parkinson após treinamento em ambientes real e virtual ». Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/47/47135/tde-05102012-113814/.
Texte intégralThe objective of this work was to compare the effects of two balance training programs, one Nintendo Wii Fit-based and the other traditionally-based without the use of a gaming system, on the balance, functionality and cognition of patients with Parkinson´s disease. It was a prospective, single blinded, randomized clinical trial performed at Brazil Parkinson Association and Center of Research of the courses of Speech Therapy, Physical Therapy and Occupational Therapy of São Paulo University. 32 patients with Parkinson´s disease on stages 1 and 2,5 of Hoehn e Yahr participated of this work. Patients were randomized in control and experimental group, 16 each one. Both groups performed 14 training sessions, twice a week, for seven weeks. Each session was composed of a 30 minute-global-exercise series including stretching, muscle strengthen and axial mobility exercises. After this, both groups performed more 30 minutes of balance training: the control group performed balance exercises without external cues, visual or auditory feedbacks or cognitive stimulations; the experimental group performed the balance training with 10 Wii Fit games which stimulated motor and cognitive functions. The main outcome measures were: (1) Unified Parkinson´s Disease Rating Scale (UPDRS); (2) Berg Balance Scale (BBS); (3) Unipedal Stance Test (UST) and (4) Montreal Cognitive Assessment (MoCA). The statistical analysis was done by repeated measures ANOVA in order to assess the possible differences among the analyzed variables. Both groups showed improvement in the section II of UPDRS, BBS, UST and MoCA. Patients with Parkinson´s disease showed balance and cognitive improvement with positive repercussion on daily living activities after 14 sessions of balance training without additional advantages to the virtual training
Weinberg, Isobel Claire. « Expectation in motor planning and execution ». Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10049246/.
Texte intégralKadlec, Daniel. « Motor capacity and sidestepping execution strategies in female athletes ». Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2022. https://ro.ecu.edu.au/theses/2536.
Texte intégralDahlén, Olle, et Axel Rantil. « Optimized Trade Execution with Reinforcement Learning ». Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150186.
Texte intégralMorris, Nicole K. « Perception, Cognition, and Action in the Execution of a Motor Skill ». Miami University Honors Theses / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=muhonors1303917744.
Texte intégralShalabi, Kholood Matouq. « Motor learning and inter-manual transfer of motor learning after a stroke ». Thesis, University of Newcastle upon Tyne, 2017. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.768491.
Texte intégral侯江濤 et Kong-to William Hau. « Artificial neural networks, motor programs and motor learning ». Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31240227.
Texte intégralLivres sur le sujet "Motor learning and execution"
Rothstein, Anne L. Motor learning. Reston, Va : American Alliance for Health, Physical Education, Recreation, and Dance, 1987.
Trouver le texte intégralRothstein, Anne L. Motor learning. Reston, Va : American Alliance for Health, Physical Education, Recreation, and Dance, 1987.
Trouver le texte intégralKober, Jens, et Jan Peters. Learning Motor Skills. Cham : Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03194-1.
Texte intégralA, Crutchfield Carolyn, et Barnes Marylou R, dir. Motor control and motor learning in rehabilitation. Atlanta, Ga : Stokesville Pub. Co., 1993.
Trouver le texte intégralLatash, Mark L., et Francis Lestienne, dir. Motor Control and Learning. Boston, MA : Springer US, 2006. http://dx.doi.org/10.1007/0-387-28287-4.
Texte intégralShea, Charles H. Motor learning and control. Boston, Mass : Allyn and Bacon, 1993.
Trouver le texte intégral1948-, Reid Greg, et Collier Douglas Holden 1953-, dir. Motor learning and development. Champaign, IL : Human Kinetics, 2011.
Trouver le texte intégralA, Wrisberg Craig, dir. Motor learning and performance. 3e éd. Champaign, IL : Human Kinetics, 2004.
Trouver le texte intégralWayne, Shebilske, et Worchel Stephen, dir. Motor learning and control. Englewood Cliffs, N.J : Prentice Hall, 1993.
Trouver le texte intégralA, Wrisberg Craig, dir. Motor learning and performance. 2e éd. Champaign, IL : Human Kinetics, 2000.
Trouver le texte intégralChapitres de livres sur le sujet "Motor learning and execution"
Delgado-García, J. M., A. Gruart, J. A. Domingo et J. A. Trigo. « Quantal neural mechanisms underlying movement execution and motor learning ». Dans Biological and Artificial Computation : From Neuroscience to Technology, 124–32. Berlin, Heidelberg : Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0032470.
Texte intégralWulf, Gabriele. « Motor Learning ». Dans Encyclopedia of the Sciences of Learning, 2348–50. Boston, MA : Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_869.
Texte intégralMorgan, Michael M., MacDonald J. Christie, Thomas Steckler, Ben J. Harrison, Christos Pantelis, Christof Baltes, Thomas Mueggler et al. « Motor Learning ». Dans Encyclopedia of Psychopharmacology, 805. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_3411.
Texte intégralGoertzel, Ben. « Motor Learning ». Dans The Structure of Intelligence, 141–47. New York, NY : Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-4336-6_11.
Texte intégralCarrière, Beate. « Motor Learning ». Dans The Swiss Ball, 36–42. Berlin, Heidelberg : Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58864-8_3.
Texte intégralBoehm, Matthias, Arun Kumar et Jun Yang. « Execution Strategies ». Dans Data Management in Machine Learning Systems, 53–71. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-031-01869-5_5.
Texte intégralKokai, Yuki, Isao Nambu et Yasuhiro Wada. « Identifying Motor Imagery-Related Electroencephalogram Features During Motor Execution ». Dans Neural Information Processing, 90–97. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63836-8_8.
Texte intégralSherwood, David E. « Motor Control and Motor Learning ». Dans Introduction to Exercise Science, 241–62. Fifth edition. | Milton Park, Abingdon, Oxon ; New York, NY : : Routledge, 2017. http://dx.doi.org/10.4324/9781315177670-10.
Texte intégralSheridan, Martin R. « Initiation and Execution of Movement : A Unified Approach ». Dans Tutorials in Motor Neuroscience, 313–32. Dordrecht : Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3626-6_26.
Texte intégralAnnett, John. « Motor Learning : A Review ». Dans Motor Behavior, 189–212. Berlin, Heidelberg : Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-69749-4_6.
Texte intégralActes de conférences sur le sujet "Motor learning and execution"
Aslan, Oğuzhan, Kurt Kağan Kurtoğlu, Kutay Yeşilalan et Sinem Burcu Erdoğan. « Machine Learning Based Prediction of Motor Imagery and Motor Execution Tasks from Functional Near Infrared Spectroscopy Signals ». Dans Optics and the Brain. Washington, D.C. : OSA, 2020. http://dx.doi.org/10.1364/brain.2020.bm4c.2.
Texte intégralCorlaci, Ionut, et Mihaela Puiu. « THE WAYS FOR IMPROVING THE USE OF VISUAL FEEDBACK BY E-PROGRAMMES IN MEN'S ARTISTIC GYMNASTICS ». Dans eLSE 2016. Carol I National Defence University Publishing House, 2016. http://dx.doi.org/10.12753/2066-026x-16-225.
Texte intégralCasellato, Claudia, Marta Gandolla, Alessandro Crippa et Alessandra Pedrocchi. « Robotic set-up to quantify hand-eye behavior in motor execution and learning of children with autism spectrum disorder ». Dans 2017 International Conference on Rehabilitation Robotics (ICORR). IEEE, 2017. http://dx.doi.org/10.1109/icorr.2017.8009372.
Texte intégralBelov, Dmitry, Samba BA, Ji Tang Liu, Anton Kolyshkin et Sergio Daniel Rocchio. « Data-Driven PHM Solution for Health Monitoring of Mud Motor Power Sections While Drilling ». Dans SPE Europec featured at 82nd EAGE Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205219-ms.
Texte intégralYadav, Singh Anurag, et Imran Muhammad Chohan. « Offset Data Analysis and Seam Less Execution Through Real Time Monitoring Results in Step Change in Drilling Performance ». Dans SPE Europec featured at 82nd EAGE Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205152-ms.
Texte intégralGong, J. Q., et Bin Yao. « Indirect Neural Network Adaptive Robust Control of Linear Motor Drive System ». Dans ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33420.
Texte intégralNguyen, Van-Hanh, Fre´de´ric Me´rienne, Jean-Luc Martinez et Thierry Pozzo. « An Approach for Measuring the Human Gesture Learning Ability in Third-Person View Virtual Environment for Motor Rehabilitation ». Dans ASME 2010 World Conference on Innovative Virtual Reality. ASMEDC, 2010. http://dx.doi.org/10.1115/winvr2010-3736.
Texte intégralThomas Philip, Titto, et Sergey Ziatdinov. « Learnings from Building a Vendor Agnostic Automated Directional Drilling System ». Dans SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205864-ms.
Texte intégralGrosu, Vlad teodor, Tatiana Dobrescu et Emilia Grosu. « GENERAL AND HAND-EYES COORDINATION IN MENTAL TRAINING OF ALPINE SKIERS ». Dans eLSE 2016. Carol I National Defence University Publishing House, 2016. http://dx.doi.org/10.12753/2066-026x-16-231.
Texte intégralTeodoru, Marian daniel, et Razvanliviu Petre. « THE EFFICIENT LEARNING OF STRIKES IN RELATION TO THE KARATE-DO STANCES BY MEANS OF THE PEDAR-X PLANTAR PRESSURE MEASUREMENT SYSTEM ». Dans eLSE 2013. Carol I National Defence University Publishing House, 2013. http://dx.doi.org/10.12753/2066-026x-13-240.
Texte intégralRapports d'organisations sur le sujet "Motor learning and execution"
Hudson, Kesha N., et Michael T. Willoughby. The Multiple Benefits of Motor Competence Skills in Early Childhood. RTI Press, août 2021. http://dx.doi.org/10.3768/rtipress.2021.rb.0027.2108.
Texte intégralji, yuqin, hao tian, qiang ye, zhuoyan ye et zeyu zheng. Effectiveness of exercise intervention on improving fundamental motor skills in children with autism spectrum disorder : A systematic review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, décembre 2022. http://dx.doi.org/10.37766/inplasy2022.12.0013.
Texte intégralThrun, Sebastian. MAPLE : Multi-Agent Planning, Learning, and Execution. Fort Belvoir, VA : Defense Technical Information Center, février 2004. http://dx.doi.org/10.21236/ada421529.
Texte intégralZhu, Song-Chun. MATHEMATICS OF SENSING, EXPLOITATION, AND EXECUTION (MSEE) Sensing, Exploitation, and Execution (SEE) on a Foundation for Representation, Inference, and Learning. Fort Belvoir, VA : Defense Technical Information Center, juillet 2016. http://dx.doi.org/10.21236/ad1011558.
Texte intégralThompson, Richard F. A Biological Neural Network Analysis of Learning and Memory : The Cerebellum and Sensory Motor Conditioning. Fort Belvoir, VA : Defense Technical Information Center, novembre 1995. http://dx.doi.org/10.21236/ada304568.
Texte intégralNickerson, Jeffrey, Kalle Lyytinen et John L. King. Automated Vehicles : A Human/Machine Co-learning Perspective. SAE International, avril 2022. http://dx.doi.org/10.4271/epr2022009.
Texte intégralJelsma, Dorothee, Reza Abdollahipour, Farhad Ghadiri, Fatemeh Alaei, Miriam Paloma Nieto, Zdenek Svoboda, Miguel Villa de Gregorio, Paola Violasdotter Nilsson, Dido Green et Kamila Banatova. Evidence-based practice interventions for children and young people with Developmental Coordination Disorder - A scoping review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, février 2023. http://dx.doi.org/10.37766/inplasy2023.2.0028.
Texte intégralSAINI, RAVINDER, AbdulKhaliq Alshadid et Lujain Aldosari. Investigation on the application of artificial intelligence in prosthodontics. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, décembre 2022. http://dx.doi.org/10.37766/inplasy2022.12.0096.
Texte intégralKulhandjian, Hovannes. AI-based Pedestrian Detection and Avoidance at Night using an IR Camera, Radar, and a Video Camera. Mineta Transportation Institute, novembre 2022. http://dx.doi.org/10.31979/mti.2022.2127.
Texte intégralAvellán, Leopoldo, Zulima Leal Calderon et Giulia Lotti. Why do some Development Projects Disburse Funds Faster than Others. Inter-American Development Bank, novembre 2021. http://dx.doi.org/10.18235/0003839.
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