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Journal articles on the topic 'Motor learning and execution'

Author: Grafiati

Published: 10 March 2023

Last updated: 31 July 2025

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1

Diedrichsen, Jörn, and Katja Kornysheva. "Motor skill learning between selection and execution." Trends in Cognitive Sciences 19, no. 4 (2015): 227–33. http://dx.doi.org/10.1016/j.tics.2015.02.003.

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Torriero, Sara, Massimiliano Oliveri, Giacomo Koch, et al. "Changes in Cerebello-motor Connectivity during Procedural Learning by Actual Execution and Observation." Journal of Cognitive Neuroscience 23, no. 2 (2011): 338–48. http://dx.doi.org/10.1162/jocn.2010.21471.

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The cerebellum is involved in motor learning of new procedures both during actual execution of a motor task and during observational training. These processes are thought to depend on the activity of a neural network that involves the lateral cerebellum and primary motor cortex (M1). In this study, we used a twin-coil TMS technique to investigate whether execution and observation of a visuomotor procedural learning task is related to modulation of cerebello-motor connectivity. We observed that, at rest, a magnetic conditioning pulse applied over the lateral cerebellum reduced the motor-evoked

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Jäger, Anna-Thekla P., Julia M. Huntenburg, Stefanie A. Tremblay, et al. "Motor sequences; separating the sequence from the motor. A longitudinal rsfMRI study." Brain Structure and Function 227, no. 3 (2021): 793–807. http://dx.doi.org/10.1007/s00429-021-02412-7.

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AbstractIn motor learning, sequence specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stage

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Torriani-Pasin, Camila, Gisele Carla dos Santos Palma, Cristiane Matsumoto Jakabi, Cinthya Walter, Andrea Michele Freudenheim, and Umberto César Correa. "Motor Learning of a cognitive-motor task after stroke." Revista Brasileira de Educação Física e Esporte 34, no. 1 (2020): 1–9. http://dx.doi.org/10.11606/1807-5509202000010001.

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The aim of this study was investigated a maze learning in stroke individuals. Forty participants assigned into two groups: experimental (stroke participants; n = 20) and control (neurologically healthy participants; n = 20). The study involved an acquisition phase, a transfer test, and a short-and longterm retention tests. The task consisted in complete a maze, with paper and pen, in the shortest time possible. The dependent variables were execution time and error. Data were analyzed with an Anova- two way with Repeated Measures for these variables. Results showed learning for both groups, but

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Torriani-Pasin, Camila, Gisele Carla dos Santos Palma, Cristiane Matsumoto Jakabi, Cinthya Walter, Andrea Michele Freudenheim, and Umberto César Correa. "Motor Learning of a cognitive-motor task after stroke." Revista Brasileira de Educação Física e Esporte 34, no. 1 (2020): 1–9. http://dx.doi.org/10.11606/issn.1981-4690.v34i1p1-9.

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The aim of this study was investigated a maze learning in stroke individuals. Forty participants assigned into two groups: experimental (stroke participants; n = 20) and control (neurologically healthy participants; n = 20). The study involved an acquisition phase, a transfer test, and a short-and longterm retention tests. The task consisted in complete a maze, with paper and pen, in the shortest time possible. The dependent variables were execution time and error. Data were analyzed with an Anova- two way with Repeated Measures for these variables. Results showed learning for both groups, but

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Domingues, Clayton Amaral, Sergio Machado, Emerson Garcia Cavaleiro, et al. "Alpha absolute power: motor learning of practical pistol shooting." Arquivos de Neuro-Psiquiatria 66, no. 2b (2008): 336–40. http://dx.doi.org/10.1590/s0004-282x2008000300010.

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The present study aimed at investigating changes in behavior (shooting precision) and electrophysiological variables (absolute alpha power) during the motor learning of practical pistol shooting. The sample was composed of 23 healthy subjects, right-handed, male, between 18 and 20 years of age. The task consisted of four learning blocks. A One-way ANOVA with repeated measures and a post hoc analysis were employed to observe modifications on behavioral and electrophysiological measures (p<0.05). The results showed significative differences between blocks according to motor learning, and a si

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Sobierajewicz, Jagna, Sylwia Szarkiewicz, Anna Przekoracka-Krawczyk, Wojciech Jaśkowski, and 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 (2016): 178–91. http://dx.doi.org/10.5709/acp-0197-1.

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Stoter, Arjan J. R., Erik J. A. Scherder, Yvo P. T. Kamsma, and Theo Mulder. "Rehearsal Strategies during Motor-Sequence Learning in Old Age: Execution vs Motor Imagery." Perceptual and Motor Skills 106, no. 3 (2008): 967–78. http://dx.doi.org/10.2466/pms.106.3.967-978.

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Badr, Laïla, Léandre Gagné-Pelletier, Hugo Massé-Alarie, and Catherine Mercier. "Effect of Phasic Experimental Pain Applied during Motor Preparation or Execution on Motor Performance and Adaptation in a Reaching Task: A Randomized Trial." Brain Sciences 14, no. 9 (2024): 851. http://dx.doi.org/10.3390/brainsci14090851.

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Musculoskeletal conditions often involve pain related to specific movements. However, most studies on the impact of experimental pain on motor performance and learning have used tonic pain models. This study aimed to evaluate the effect of experimental phasic pain during the preparation or execution of a reaching task on the acquisition and retention of sensorimotor adaptation. Participants were divided into three groups: no pain, pain during motor preparation, and pain during motor execution. Pain was induced over the scapula with a laser while participants performed a force field adaptation

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Cho, Nam Jun, Sang Hyoung Lee, Jong Bok Kim, and 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 (2020): 2719. http://dx.doi.org/10.3390/app10082719.

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We propose a framework based on imitation learning and self-learning to enable robots to learn, improve, and generalize motor skills. The peg-in-hole task is important in manufacturing assembly work. Two motor skills for the peg-in-hole task are targeted: “hole search” and “peg insertion”. The robots learn initial motor skills from human demonstrations and then improve and/or generalize them through reinforcement learning (RL). An initial motor skill is represented as a concatenation of the parameters of a hidden Markov model (HMM) and a dynamic movement primitive (DMP) to classify input signa

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Ariani, Giacomo, and Jörn Diedrichsen. "Sequence learning is driven by improvements in motor planning." Journal of Neurophysiology 121, no. 6 (2019): 2088–100. http://dx.doi.org/10.1152/jn.00041.2019.

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The ability to perform complex sequences of movements quickly and accurately is critical for many motor skills. Although training improves performance in a large variety of motor sequence tasks, the precise mechanisms behind such improvements are poorly understood. Here we investigated the contribution of single-action selection, sequence preplanning, online planning, and motor execution to performance in a discrete sequence production task. Five visually presented numbers cued a sequence of five finger presses, which had to be executed as quickly and accurately as possible. To study how seque

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Pavlides, C., E. Miyashita, and H. Asanuma. "Projection from the sensory to the motor cortex is important in learning motor skills in the monkey." Journal of Neurophysiology 70, no. 2 (1993): 733–41. http://dx.doi.org/10.1152/jn.1993.70.2.733.

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1. The projection from the somatosensory cortex to the primary motor cortex has been proposed to play an important role in learning novel motor skills. This hypothesis was examined by studying the effects of lesions to the sensory cortex on learning of new motor skills. 2. We used two experimental paradigms to reveal the effects of lesions on learning of new motor skills. One task was to catch a food pellet falling at various velocities. The other task was to catch a food pellet from a rotating level. Both tasks required acquisition of novel motor skills. 3. The training was started after a le

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Pérez-Velasco, Sergio, Diego Marcos-Martínez, Eduardo Santamaría-Vázquez, Víctor Martínez-Cagigal, and Roberto Hornero. "Bridging motor execution and motor imagery BCI paradigms: An inter-task transfer learning approach." Biomedical Signal Processing and Control 107 (September 2025): 107834. https://doi.org/10.1016/j.bspc.2025.107834.

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Kaviri, Sina Makhdoomi, and Ramana Vinjamuri. "Decoding motor execution and motor imagery from EEG with deep learning and source localization." Biomedical Engineering Advances 9 (June 2025): 100156. https://doi.org/10.1016/j.bea.2025.100156.

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Nakahara, Hiroyuki, Kenji Doya, and Okihide Hikosaka. "Parallel Cortico-Basal Ganglia Mechanisms for Acquisition and Execution of Visuomotor Sequences—A Computational Approach." Journal of Cognitive Neuroscience 13, no. 5 (2001): 626–47. http://dx.doi.org/10.1162/089892901750363208.

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Experimental studies have suggested that many brain areas, including the basal ganglia (BG), contribute to procedural learning. Focusing on the basal ganglia-thalamo-cortical (BG-TC) system, we propose a computational model to explain how different brain areas work together in procedural learning. The BG-TC system is composed of multiple separate loop circuits. According to our model, two separate BG-TC loops learn a visuomotor sequence concurrently but using different coordinates, one visual, and the other motor. The visual loop includes the dorsolateral prefrontal (DLPF) cortex and the anter

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King, Bradley R., Florian A. Kagerer, Jose L. Contreras-Vidal, and Jane E. Clark. "Evidence for Multisensory Spatial-to-Motor Transformations in Aiming Movements of Children." Journal of Neurophysiology 101, no. 1 (2009): 315–22. http://dx.doi.org/10.1152/jn.90781.2008.

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The extant developmental literature investigating age-related differences in the execution of aiming movements has predominantly focused on visuomotor coordination, despite the fact that additional sensory modalities, such as audition and somatosensation, may contribute to motor planning, execution, and learning. The current study investigated the execution of aiming movements toward both visual and acoustic stimuli. In addition, we examined the interaction between visuomotor and auditory-motor coordination as 5- to 10-yr-old participants executed aiming movements to visual and acoustic stimul

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Herszage, Jasmine, Haggai Sharon, and Nitzan Censor. "Reactivation-induced motor skill learning." Proceedings of the National Academy of Sciences 118, no. 23 (2021): e2102242118. http://dx.doi.org/10.1073/pnas.2102242118.

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Learning motor skills commonly requires repeated execution to achieve gains in performance. Motivated by memory reactivation frameworks predominantly originating from fear-conditioning studies in rodents, which have extended to humans, we asked the following: Could motor skill learning be achieved by brief memory reactivations? To address this question, we had participants encode a motor sequence task in an initial test session, followed by brief task reactivations of only 30 s each, conducted on separate days. Learning was evaluated in a final retest session. The results showed that these bri

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Sobierajewicz, Jagna, Anna Przekoracka-Krawczyk, Wojciech Jaśkowski, and Rob H. J. van der Lubbe. "How effector-specific is the effect of sequence learning by motor execution and motor imagery?" Experimental Brain Research 235, no. 12 (2017): 3757–69. http://dx.doi.org/10.1007/s00221-017-5096-z.

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Kadmon Harpaz, Naama, Kiah Hardcastle, and Bence P. Ölveczky. "Learning-induced changes in the neural circuits underlying motor sequence execution." Current Opinion in Neurobiology 76 (October 2022): 102624. http://dx.doi.org/10.1016/j.conb.2022.102624.

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Areej, Hameed Al-Anbary, and Al-Qaraawi‎ Salih. "Classification of EEG signals for facial expression and ‎motor ‎execution with deep learning." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 19, no. 5 (2021): 1588–93. https://doi.org/10.12928/telkomnika.v19i5.19850.

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Recently, algorithms of machine learning are widely used with the field of &lrm;electroencephalography (EEG) brain-computer interfaces (BCI). The &lrm;preprocessing stage for the EEG signals is performed by applying the principle &lrm;component analysis (PCA) algorithm to extract the important features and &lrm;reducing the data redundancy. A model for classifying EEG, time series, signals for facial &lrm;expression and some motor execution processes had been designed. A neural &lrm;network of three hidden layers with deep learning classifier had been used in &lrm;this work. Data of four diffe

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Wang, Chenyu, Yinghua Yu, and Jiajia Yang. "Contributions of the Primary Sensorimotor Cortex and Posterior Parietal Cortex to Motor Learning and Transfer." Brain Sciences 14, no. 12 (2024): 1184. http://dx.doi.org/10.3390/brainsci14121184.

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Background: Transferring learned manipulations to new manipulation tasks has enabled humans to realize thousands of dexterous object manipulations in daily life. Two-digit grasp and three-digit grasp manipulations require different fingertip forces, and our brain can switch grasp types to ensure good performance according to motor memory. We hypothesized that several brain areas contribute to the execution of the new type of motor according to the motor memory. However, the motor memory mechanisms during this transfer period are still unclear. In the present functional magnetic resonance imagi

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de Almeida Marcelino, Ana Luísa, Andreas Horn, Patricia Krause, Andrea A. Kühn, and Wolf-Julian Neumann. "Subthalamic neuromodulation improves short-term motor learning in Parkinson’s disease." Brain 142, no. 8 (2019): 2198–206. http://dx.doi.org/10.1093/brain/awz152.

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Abstract The basal ganglia and cerebellum are implicated in both motor learning and Parkinson’s disease. Deep brain stimulation (DBS) is an established treatment for advanced Parkinson’s disease that leads to motor and non-motor effects by modulating specific neural pathways. Recently, a disynaptic projection from the subthalamic nucleus (STN) to cerebellar hemispheres was discovered. To investigate the functional significance of this pathway in motor learning, short-term improvement in motor execution in 20 patients with Parkinson’s disease on and off STN-DBS and 20 age-matched healthy contro

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Floyer-Lea, A., and P. M. Matthews. "Changing Brain Networks for Visuomotor Control With Increased Movement Automaticity." Journal of Neurophysiology 92, no. 4 (2004): 2405–12. http://dx.doi.org/10.1152/jn.01092.2003.

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Learning a motor skill is associated with changes in patterns of brain activation with movement. Here we have further characterized these dynamics during fast (short-term) learning of a visuomotor skill using functional magnetic resonance imaging. Subjects ( n = 15) were studied as they learned to visually track a moving target by varying the isometric force applied to a pressure plate held in the right hand. Learning was confirmed by demonstration of improved performance and automaticity (the relative lack of need for conscious attention during task execution). We identified two distinct, tim

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Lomelin-Ibarra, Vicente A., Andres E. Gutierrez-Rodriguez, and Jose A. Cantoral-Ceballos. "Motor Imagery Analysis from Extensive EEG Data Representations Using Convolutional Neural Networks." Sensors 22, no. 16 (2022): 6093. http://dx.doi.org/10.3390/s22166093.

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Motor imagery is a complex mental task that represents muscular movement without the execution of muscular action, involving cognitive processes of motor planning and sensorimotor proprioception of the body. Since the mental task has similar behavior to that of the motor execution process, it can be used to create rehabilitation routines for patients with some motor skill impairment. However, due to the nature of this mental task, its execution is complicated. Hence, the classification of these signals in scenarios such as brain–computer interface systems tends to have a poor performance. In t

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Gehringer, James E., David J. Arpin, Elizabeth Heinrichs-Graham, Tony W. Wilson, and Max J. Kurz. "Neurophysiological changes in the visuomotor network after practicing a motor task." Journal of Neurophysiology 120, no. 1 (2018): 239–49. http://dx.doi.org/10.1152/jn.00020.2018.

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Although it is well appreciated that practicing a motor task updates the associated internal model, it is still unknown how the cortical oscillations linked with the motor action change with practice. The present study investigates the short-term changes (e.g., fast motor learning) in the α- and β-event-related desynchronizations (ERD) associated with the production of a motor action. To this end, we used magnetoencephalography to identify changes in the α- and β-ERD in healthy adults after participants practiced a novel isometric ankle plantarflexion target-matching task. After practicing, th

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Tsuji, Toshio, Yusuke Ishida, Koji Ito, Mitsuo Nagamachi, and Tatsuo Nishino. "Motor Schema Model Learned by Structural Neural Networks." Journal of Robotics and Mechatronics 2, no. 4 (1990): 258–65. http://dx.doi.org/10.20965/jrm.1990.p0258.

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Human beings remember plans concerning typical motions which occur frequently as schema, and by selecting suitable schema depending on conditions, generate muscular motion almost unconsciously. Though a motor schema represents typical motions, it is equipped with superior plan structure taking into consideration the concurrency and seriality of motions as seen in grasping actions and walking motions, and the structure of plans can be acquired by learning. In this paper, a study is made of the modeling of such motor schema with the use of neural networks. For this purpose, the neural network is

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Shrestha, Shaj, Nistha Shrestha, Abhishek Dhalachhe Shrestha, and Shambhu Prasad Adhikari. "Immediate Effect of Physiotherapist-demonstrated Action Observation with Execution for Improving Upper Extremity Motor Function in Stroke: a Pre-post Pilot Study." Journal of Nepal Health Research Council 21, no. 3 (2024): 400–409. http://dx.doi.org/10.33314/jnhrc.v21i3.4471.

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Background: Video-demonstrated action-observation-execution is an effective intervention for motor re-learning in stroke rehabilitation. But customization of video for each task repeatedly questions its feasibility within limited resources, particularly for daily routine practice and in community settings. Physiotherapist-demonstrated action-observation-execution is a practical intervention based on the principle of observation and consecutive repetitions of observed real, live movements. The main objective of this study was to investigate the immediate effect of Physiotherapist-demonstrated a

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Jastrzębski, Marcin, and Jacek Kabziński. "Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks." Energies 14, no. 18 (2021): 5619. http://dx.doi.org/10.3390/en14185619.

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New results in the area of neural network modeling applied in electric drive automation are presented. Reliable models of permanent magnet motor flux as a function of current and rotor position are particularly useful in control synthesis—allowing one to minimize the losses, analyze motor performance (torque ripples etc.) and to identify motor parameters—and may be used in the control loop to compensate flux and torque variations. The effectiveness of extreme learning machine (ELM) neural networks used for approximation of permanent magnet motor flux distribution is evaluated. Two original net

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Lagarrigue, Yannick, Céline Cappe, and Jessica Tallet. "Regular rhythmic and audio-visual stimulations enhance procedural learning of a perceptual-motor sequence in healthy adults: A pilot study." PLOS ONE 16, no. 11 (2021): e0259081. http://dx.doi.org/10.1371/journal.pone.0259081.

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Procedural learning is essential for the effortless execution of many everyday life activities. However, little is known about the conditions influencing the acquisition of procedural skills. The literature suggests that sensory environment may influence the acquisition of perceptual-motor sequences, as tested by a Serial Reaction Time Task. In the current study, we investigated the effects of auditory stimulations on procedural learning of a visuo-motor sequence. Given that the literature shows that regular rhythmic auditory rhythm and multisensory stimulations improve motor speed, we expecte

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Kase, Kei, Noboru Matsumoto, and Tetsuya Ogata. "Leveraging Motor Babbling for Efficient Robot Learning." Journal of Robotics and Mechatronics 33, no. 5 (2021): 1063–74. http://dx.doi.org/10.20965/jrm.2021.p1063.

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Deep robotic learning by learning from demonstration allows robots to mimic a given demonstration and generalize their performance to unknown task setups. However, this generalization ability is heavily affected by the number of demonstrations, which can be costly to manually generate. Without sufficient demonstrations, robots tend to overfit to the available demonstrations and lose the robustness offered by deep learning. Applying the concept of motor babbling – a process similar to that by which human infants move their bodies randomly to obtain proprioception – is also effective for allowin

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Orrell, Alison J., Frank F. Eves, and Rich SW Masters. "Motor Learning of a Dynamic Balancing Task After Stroke: Implicit Implications for Stroke Rehabilitation." Physical Therapy 86, no. 3 (2006): 369–80. http://dx.doi.org/10.1093/ptj/86.3.369.

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Abstract Background and Purpose. After a stroke, people often attempt to consciously control their motor actions, which, paradoxically, disrupts optimal performance. A learning strategy that minimizes the accrual of explicit knowledge may circumvent attempts to consciously control motor actions, thereby resulting in better performance. The purpose of this study was to examine the implicit learning of a dynamic balancing task after stroke by use of 1 of 2 motor learning strategies: learning without errors and discovery learning. Participants and Methods. Ten adults with stroke and 12 older adul

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McDougle, Samuel D., Matthew J. Boggess, Matthew J. Crossley, Darius Parvin, Richard B. Ivry, and Jordan A. Taylor. "Credit assignment in movement-dependent reinforcement learning." Proceedings of the National Academy of Sciences 113, no. 24 (2016): 6797–802. http://dx.doi.org/10.1073/pnas.1523669113.

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When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the ke

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Panconi, Giulia, Vincenzo Sorgente, Sara Guarducci, Riccardo Bravi, and Diego Minciacchi. "The Role of Visual Information Quantity in Fine Motor Performance." Journal of Functional Morphology and Kinesiology 9, no. 4 (2024): 267. https://doi.org/10.3390/jfmk9040267.

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Background/Objectives: Fine motor movements are essential for daily activities, such as handwriting, and rely heavily on visual information to enhance motor complexity and minimize errors. Tracing tasks provide an ecological method for studying these movements and investigating sensorimotor processes. To date, our understanding of the influence of different quantities of visual information on fine motor control remains incomplete. Our study examined how variations in the amount of visual feedback affect motor performance during handwriting tasks using a graphic pen tablet projecting on a monit

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Elsayed, Nesma E., Ahmed S. Tolba, Magdi Z. Rashad, Tamer Belal, and Shahenda Sarhan. "A Deep Learning Approach for Brain Computer Interaction-Motor Execution EEG Signal Classification." IEEE Access 9 (2021): 101513–29. http://dx.doi.org/10.1109/access.2021.3097797.

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Al-Anbary, Areej Hameed, and Salih Mahdi Al-Qaraawi. "Classification of EEG signals for facial expression and motor execution with deep learning." TELKOMNIKA (Telecommunication Computing Electronics and Control) 19, no. 5 (2021): 1588. http://dx.doi.org/10.12928/telkomnika.v19i5.19850.

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Al-Anbary, Areej Hameed, and Salih Mahdi Al-Qaraawi. "Classification of EEG signals for facial expression and motor execution with deep learning." TELKOMNIKA (Telecommunication Computing Electronics and Control) 19, no. 5 (2021): 1588. http://dx.doi.org/10.12928/telkomnika.v19i5.19850.

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Wagner, Mark J., Tony Hyun Kim, Jonathan Kadmon, et al. "Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task." Cell 177, no. 3 (2019): 669–82. http://dx.doi.org/10.1016/j.cell.2019.02.019.

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Ranganathan, Rajiv, and Karl M. Newell. "Motor Learning through Induced Variability at the Task Goal and Execution Redundancy Levels." Journal of Motor Behavior 42, no. 5 (2010): 307–16. http://dx.doi.org/10.1080/00222895.2010.510542.

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Zhang, Hang, Lele Xu, Rushao Zhang, et al. "Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning." PLoS ONE 7, no. 5 (2012): e36052. http://dx.doi.org/10.1371/journal.pone.0036052.

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Roland, P. E. "Partition of the Human Cerebellum in Sensory-Motor Activities, Learning and Cognition." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 20, S3 (1993): S75—S77. http://dx.doi.org/10.1017/s0317167100048563.

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ABSTRACT:The circuitry of the cerebellum is quite well understood. The computation takes place in the cerebellar cortex, which functions in synchronized strips to provide excellent timing signals to the cerebral cortex and the spinal cord. The cerebellar cortex is also the site where error signals from other parts of the central nervous system are incorporated. For voluntary limb movements the cerebellular cortex is important for the timing of the innervation of the agonist and antagonist anterior horn neurons. It is also important for the temporal order of and precision in the execution of mo

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De Marco, Doriana, Elisa De Stefani, and Giovanni Vecchiato. "Embodying Language through Gestures: Residuals of Motor Memories Modulate Motor Cortex Excitability during Abstract Words Comprehension." Sensors 22, no. 20 (2022): 7734. http://dx.doi.org/10.3390/s22207734.

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There is a debate about whether abstract semantics could be represented in a motor domain as concrete language. A contextual association with a motor schema (action or gesture) seems crucial to highlighting the motor system involvement. The present study with transcranial magnetic stimulation aimed to assess motor cortex excitability changes during abstract word comprehension after conditioning word reading to a gesture execution with congruent or incongruent meaning. Twelve healthy volunteers were engaged in a lexical-decision task responding to abstract words or meaningless verbal stimuli. M

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Murgia, Mauro, and Alessandra Galmonte. "Editorial: The Role of Sound in Motor Perception and Execution." Open Psychology Journal 8, no. 1 (2015): 171–73. http://dx.doi.org/10.2174/1874350101508010171.

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“Perception and action” is one of the main research fields in which experimental psychologists work together with experts of other disciplines, such as medicine, physiotherapy, engineering, and sport. Traditionally, researchers have mainly focused on visual perception and on its influences on motor processes, while less attention has been dedicated to the role of auditory perception. However, in the last decade, the interest towards the influence of sounds on both action perception and motor execution has increased significantly. On the one hand, researchers have been interested in determining

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Tecchio, Franca, Filippo Zappasodi, Giovanni Assenza, et al. "Anodal Transcranial Direct Current Stimulation Enhances Procedural Consolidation." Journal of Neurophysiology 104, no. 2 (2010): 1134–40. http://dx.doi.org/10.1152/jn.00661.2009.

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The primary motor cortex (M1) area recruitment enlarges while learning a finger tapping sequence. Also M1 excitability increases during procedural consolidation. Our aim was to investigate whether increasing M1 excitability by anodal transcranial DC stimulation (AtDCS) when procedural consolidation occurs was able to induce an early consolidation improvement. Forty-seven right-handed healthy participants were trained in a nine-element serial finger tapping task (SFTT) executed with the left hand. Random series blocks were interspersed with training series blocks. Anodal or sham tDCS was admini

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Bacelar, Mariane F. B., Keith R. Lohse, and Matthew W. Miller. "The Effect of Rewards and Punishments on Learning Action Selection and Execution Components of a Motor Skill." Journal of Motor Learning and Development 8, no. 3 (2020): 475–96. http://dx.doi.org/10.1123/jmld.2019-0039.

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It is unknown whether rewards improve the capability to select appropriate targets for one’s movement (action selection) and/or the movement itself (action execution). Thus, we devised an experimental task wherein participants categorized a complex visual stimulus to determine toward which one of two targets to execute an action (putt a golf ball) on each trial under one of three conditions: reward, punishment, or neutral. After practicing the task under their assigned condition, participants performed an immediate, 24-hr, and 7-day post-test. Results revealed participants putted to the correc

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Kosma, Maria. "Phenomenological Body Schema as Motor Habit in Skill Acquisition – Intentionality is in Action." Athens Journal of Sports 10, no. 2 (2023): 83–94. http://dx.doi.org/10.30958/ajspo.10-2-2.

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The purpose of this concept-based paper was to showcase the importance of Merleau-Ponty’s (1945/2014) phenomenological body schema as motor habit in skill acquisition and perception of the world and contrast it with the standard information processing models that are solely based on cognition. Examples of disability cases are used, including Schneider’s brain damage and instances of apraxia, to exhibit that difficulty in executing certain motor skills is based on lack of body schema/motor habit and not on some gnostic disorder that inhibits representation as proposed in information processing.

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Shea, Charles H., Jin-Hoon Park, and Heather Wilde Braden. "Age-Related Effects in Sequential Motor Learning." Physical Therapy 86, no. 4 (2006): 478–88. http://dx.doi.org/10.1093/ptj/86.4.478.

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Abstract Background and Purpose. When learning multi-element movement sequences, participants organize individual elements into subsequences. Imposing this type of structure on the elements leads to the efficient production of sequences because the processing of all but the first elements in a subsequence can be completed prior to their execution. The primary purpose of this study was to determine whether older adults organize lengthy movement sequences with the same efficiency as young adults. Subjects and Methods. Participants were young adults (N=8, 19–23 years of age) and older adults (N=8

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Bernardi, Nicolò F., Floris T. Van Vugt, Ricardo Ruy Valle-Mena, Shahabeddin Vahdat, and David J. Ostry. "Error-related Persistence of Motor Activity in Resting-state Networks." Journal of Cognitive Neuroscience 30, no. 12 (2018): 1883–901. http://dx.doi.org/10.1162/jocn_a_01323.

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The relationship between neural activation during movement training and the plastic changes that survive beyond movement execution is not well understood. Here we ask whether the changes in resting-state functional connectivity observed following motor learning overlap with the brain networks that track movement error during training. Human participants learned to trace an arched trajectory using a computer mouse in an MRI scanner. Motor performance was quantified on each trial as the maximum distance from the prescribed arc. During learning, two brain networks were observed, one showing incre

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Muehlberg, Christoph, Christopher Fricke, Mirko Wegscheider, et al. "Motor learning is independent of effects of subthalamic deep brain stimulation on motor execution." Brain Communications, March 17, 2023. http://dx.doi.org/10.1093/braincomms/fcad070.

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Abstract Motor learning is defined as an improvement in performance through practice. The ability to learn new motor skills may be particularly challenged in patients with Parkinson's disease, in whom motor execution is impaired by the disease-defining motor symptoms such as bradykinesia. Subthalamic deep brain stimulation is an effective treatment in advanced Parkinson’s disease, and its beneficial effects on Parkinsonian motor symptoms and motor execution have been widely demonstrated. Much less is known about whether deep brain stimulation directly interacts with motor learning independent

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Wolff, Steffen B. E., Raymond Ko, and Bence P. Ölveczky. "Distinct roles for motor cortical and thalamic inputs to striatum during motor skill learning and execution." Science Advances 8, no. 8 (2022). http://dx.doi.org/10.1126/sciadv.abk0231.

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The acquisition and execution of motor skills are mediated by a distributed motor network, spanning cortical and subcortical brain areas. The sensorimotor striatum is an important cog in this network, yet the roles of its two main inputs, from motor cortex and thalamus, remain largely unknown. To address this, we silenced the inputs in rats trained on a task that results in highly stereotyped and idiosyncratic movement patterns. While striatal-projecting motor cortex neurons were critical for learning these skills, silencing this pathway after learning had no effect on performance. In contrast

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Lorenzi, Roberta Maria, Gökçe Korkmaz, Adnan A. S. Alahmadi, et al. "Cerebellar control over inter-regional excitatory/inhibitory dynamics discriminates execution from observation of an action." Cerebellum 24, no. 4 (2025). https://doi.org/10.1007/s12311-025-01863-6.

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Abstract The motor learning theory anticipates that cerebro-cerebellar loops perform sensorimotor prediction, thereby regulating motor control during action execution (AE) and observation (AO), but the causal interaction between the cerebellum and cerebral cortex remains unclear. Therefore, our aim was to understand what triggers neuronal activity between brain areas engaged in a visuo-motor task that involves cortico-cerebellar interactions, organised in loops. We used Dynamic Causal Modelling (DCM) to study functional MRI (fMRI) data obtained in healthy participants during a squeeze-ball tas

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