Model-Based and Model-Free Mechanisms of Human Motor Learning

Reinforcement Learning: An Introduction

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Forward Models for Physiological Motor Control

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Reinforcement learning

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Experiencing a reaching task passively with one arm while adapting to a visuomotor rotation with the other can lead to substantial transfer of motor learning across the arms

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Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions

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Intermanual transfer and retention of visuomotor adaptation to a large visuomotor distortion are driven by explicit processes

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Investigating Neuroanatomical Features in Top Athletes at the Single Subject Level

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Exploring the role of task success in implicit motor adaptation

Al-Fawakhiri, N., Ma, A., Taylor, J. A., & Kim, O. A. (2023) · Journal of Neurophysiology · doi:10.1152/jn.00061.2023 · Cited by 18

Domain-Specific Working Memory, But Not Dopamine-Related Genetic Variability, Shapes Reward-Based Motor Learning

Holland, P. J., Codol, O., Oxley, E., Taylor, M. D., Hamshere, E., Joseph, S., Huffer, L., & Galea, J. M. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0583-19.2019 · Cited by 17

Individualized feedback to change multiple gait deficits in chronic stroke

Day, K. A., Cherry‐Allen, K. M., & Bastian, A. J. (2019) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-019-0635-4 · Cited by 18

Financial incentives enhance adaptation to a sensorimotor transformation

Gajda, K., Sülzenbrück, S., & Heuer, H. (2016) · Experimental Brain Research · doi:10.1007/s00221-016-4688-3 · Cited by 16

Improving robot dual-system motor learning with intrinsically motivated meta-control and latent-space experience imagination

Hafez, M. B., Weber, C., Kerzel, M., & Wermter, S. (2020) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2020.103630 · Cited by 18

The effects of motor modularity on performance, learning and generalizability in upper-extremity reaching: a computational analysis

Borno, M. A., Hicks, J. L., & Delp, S. L. (2020) · Journal of The Royal Society Interface · doi:10.1098/rsif.2020.0011 · Cited by 17

In Experts, underlying processes that drive visuomotor adaptation are different than in Novices

Leukel, C., Gollhofer, A., & Taube, W. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2015.00050 · Cited by 17

Finding Neural Biomarkers for Motor Learning and Rehabilitation Using an Explainable Graph Neural Network

Han, J., Embs, A., Nardi, F., Haar, S., & Faisal, A. A. (2025) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2025.3530110 · Cited by 16

Enhancing Generalization of Visuomotor Adaptation by Inducing Use-dependent Learning

Lei, Y., Bao, S., Pérez, M. A., & Wang, J. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.10.004 · Cited by 16

Use of explicit processes during a visually guided locomotor learning task predicts 24-h retention after stroke

French, M. A., Morton, S. M., & Reisman, D. S. (2020) · Journal of Neurophysiology · doi:10.1152/jn.00340.2020 · Cited by 15

Effects of subclinical depression on prefrontal–striatal model-based and model-free learning

Heo, S., Sung, Y., & Lee, S. W. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009003 · Cited by 16

Error-based and reinforcement learning in basketball free throw shooting

Truong, C., Ruffino, C., Crognier, A., Païzis, C., Crognier, L., & Papaxanthis, C. (2023) · Scientific Reports · doi:10.1038/s41598-022-26568-2 · Cited by 26

Minimizing endpoint variability through reinforcement learning during reaching movements involving shoulder, elbow and wrist

Mehler, D. M. A., Reichenbach, A., Klein, J., & Diedrichsen, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0180803 · Cited by 17

Prism Adaptation in M1

Panico, F., Fleury, L., Trojano, L., & Rossetti, Y. (2020) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01668 · Cited by 15

Ant colony system with characterization-based heuristics for a bottled-products distribution logistics system

Gomez-Santillan, C. G., Cruz–Reyes, L., Barbosa, J. J. G., H., H. J. F., R., R. A. P., & P., J. J. M. (2013) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2013.10.035 · Cited by 15

Neurophysiological Evidence of Sensory Prediction Errors Driving Speech Sensorimotor Adaptation

Kim, K. S., Hinkley, L. B. N., Brent, K., Gaines, J. L., Pongos, A. L. A., Gupta, S., Dale, C. L., Nagarajan, S. S., & Houde, J. F. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.2084-24.2025 · Cited by 15

Clustering analysis of movement kinematics in reinforcement learning

Sidarta, A., Komar, J., & Ostry, D. J. (2021) · Journal of Neurophysiology · doi:10.1152/jn.00229.2021 · Cited by 14

Asymmetrical Relationship between Prediction and Control during Visuomotor Adaptation

Mathew, J., Bernier, P., & Danion, F. (2018) · eNeuro · doi:10.1523/eneuro.0280-18.2018 · Cited by 14

Basal ganglia contributions during the learning of a visuomotor rotation: Effect of dopamine, deep brain stimulation and reinforcement

Singh, P., Lenka, A., Stezin, A., Jhunjhunwala, K. R., Pal, P. K., Ghosal, A., & Murthy, A. (2019) · European Journal of Neuroscience · doi:10.1111/ejn.14494 · Cited by 14

Dynamic changes in somatosensory and cerebellar activity mediate temporal recalibration of self-touch

Kilteni, K., & Ehrsson, H. H. (2024) · Communications Biology · doi:10.1038/s42003-024-06188-4 · Cited by 13

A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability

Tommasino, P., Maselli, A., Campolo, D., Lacquaniti, F., & d’Avella, A. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253626 · Cited by 13

Error-related Persistence of Motor Activity in Resting-state Networks

Bernardi, N. F., van Vugt, F. T., Valle-Mena, R. R., Vahdat, S., & Ostry, D. J. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01323 · Cited by 12

Articulatory Uniformity Through Articulatory Reuse: insights from an Ultrasound Study of Sūzhōu Chinese

Faytak, M. (2018) · UC Berkeley Phonology Lab Annual Reports · doi:10.5070/p7141042486 · Cited by 13

A generative learning model for saccade adaptation

Cassanello, C. R., Ostendorf, F., & Rolfs, M. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006695 · Cited by 13

Motor learning in real-world pool billiardsPreprint

Haar, S., van Assel, C. M., & Faisal, A. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/612218 · Cited by 12

Distinct learning, retention, and generalization patterns in de novo learning versus motor adaptation

Gastrock, R. Q., Hart, B. M. ’., & Henriques, D. Y. P. (2024) · Scientific Reports · doi:10.1038/s41598-024-59445-1 · Cited by 11

Motor imagery helps updating internal models during microgravity exposure

Monany, D. R., Barbiero, M., Lebon, F., Babič, J., Blohm, G., Nozaki, D., & White, O. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00214.2021 · Cited by 11

The decay and consolidation of effector-independent motor memories

Bao, S., Wang, J., Wright, D. L., Buchanan, J. J., & Lei, Y. (2022) · Scientific Reports · doi:10.1038/s41598-022-07032-7 · Cited by 11

Computational role of exploration noise in error-based de novo motor learning

Dal’Bello, L. R., & Izawa, J. (2022) · Neural Networks · doi:10.1016/j.neunet.2022.06.011 · Cited by 12

A Mobile Phone App for the Generation and Characterization of Motor Habits

Banca, P., McNamee, D., Piercy, T., Luo, Q., & Robbins, T. W. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.02850 · Cited by 11

When less is more: Enhanced statistical learning of non-adjacent dependencies after disruption of bilateral DLPFCPreprint

Ambrus, G. G., Vékony, T., Janacsek, K., Trimborn, A. B. C., Kovács, G., & Németh, D. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/198515 · Cited by 10

Evidence of an optimal error rate for motor skill learningPreprint

Al-Fawakhiri, N., Kayani, S., & McDougle, S. D. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.19.549705 · Cited by 10

Persistence of adaptation following visuomotor training

Ebrahimi, S., & Ostry, D. J. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00164.2022 · Cited by 10

Visuomotor perturbation in a continuous circle tracing task: novel approach for quantifying motor adaptation

Cohen, E. J., Wei, K., & Minciacchi, D. (2019) · Scientific Reports · doi:10.1038/s41598-019-55241-4 · Cited by 9

Haptic Assistance That Restricts the Use of Redundant Solutions is Detrimental to Motor Learning

Lokesh, R., & Ranganathan, R. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2990129 · Cited by 9

Did we get sensorimotor adaptation wrong? Implicit adaptation as direct policy updating rather than forward-model-based learningPreprint

Hadjiosif, A. M., Krakauer, J. W., & Haith, A. M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.22.914473 · Cited by 10

Value-free reinforcement learning: Policy optimization as a minimal model of operant behaviorPreprint

Bennett, D., Niv, Y., & Langdon, A. (2021) · doi:10.31234/osf.io/ew58m · Cited by 13

Emotion and reward are dissociable from error during motor learning

Festini, S. B., Preston, S. D., Reuter‐Lorenz, P. A., & Seidler, R. D. (2016) · Experimental Brain Research · doi:10.1007/s00221-015-4542-z · Cited by 7

Shift of the Muscular Inhibition Latency during On-Line Acquisition of Anticipatory Postural Adjustments

Barlaam, F., Vaugoyeau, M., Fortin, C., Assaiante, C., & Schmitz, C. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154775 · Cited by 9

Memory decay and generalization following distinct motor learning mechanisms

Bao, S., & Lei, Y. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00105.2022 · Cited by 8

Improvement in Hand Trajectory of Reaching Movements by Error-Augmentation

Israely, S., Leisman, G., & Carmeli, E. (2018) · Advances in experimental medicine and biology · doi:10.1007/5584_2018_151 · Cited by 8

Early stages of sensorimotor map acquisition: learning with free exploration, without active movement or global structure

van Vugt, F. T., & Ostry, D. J. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00429.2019 · Cited by 8

Recent Advancements in Deep Learning Applications and Methods for Autonomous Navigation: A Comprehensive ReviewPreprint

Golroudbari, A. A., & Sabour, M. H. (2023) · doi:10.22541/au.168664884.43899660/v2 · Cited by 9

Reinforcement learning in motor skill acquisition: using the reward positivity to understand the mechanisms underlying short- and long-term behavior adaptation

Bacelar, M. F. B., Lohse, K. R., Parma, J. O., & Miller, M. W. (2024) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2024.1466970 · Cited by 7

Consolidation of use-dependent motor memories induced by passive movement training

Tays, G. D., Bao, S., Javidialsaadi, M., & Wang, J. (2020) · Neuroscience Letters · doi:10.1016/j.neulet.2020.135080 · Cited by 7

Distinct Kinematic Adjustments over Multiple Timescales Accompany Locomotor Skill Development in Mice

Nguyen, K. P., Sharma, A., Gil-Silva, M., Gittis, A., & Chase, S. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.05.002 · Cited by 8

Efficacy of fine motor and balance exercises on fine motor skills in children with sensorineural hearing loss

Mehrem, E. S., Fergany, L. A., Mohamed, S. A., Fares, H. M., & Kamel, R. M. (2021) · Restorative Neurology and Neuroscience · doi:10.3233/rnn-211156 · Cited by 7

From Illusions to Beyond-Real Interactions in Virtual Reality

Abtahi, P. (2021) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3474349.3477586 · Cited by 7

The level of performance stabilization influences motor adaptation on an isometric force control task

Santos, S. P., Benda, R. N., Couto, C. R., Campos, C. E., de Andrade, A. G. P., Lage, G. M., & Ugrinowitsch, H. (2017) · PLoS ONE · doi:10.1371/journal.pone.0185939 · Cited by 7

The Effect of Rewards and Punishments on Learning Action Selection and Execution Components of a Motor Skill

Bacelar, M. F. B., Lohse, K. R., & Miller, M. W. (2020) · Journal of Motor Learning and Development · doi:10.1123/jmld.2019-0039 · Cited by 8

Learning vs. minding: How subjective costs can mask motor learning

Healy, C. M., Berniker, M., & Ahmed, A. A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282693 · Cited by 6

Age-related differences in task-related modulation of cerebellar brain inhibition

Malderen, S. V., Hehl, M., Nuyts, M., Verstraelen, S., Heemels, R. E., Hardwick, R. M., Swinnen, S. P., & Cuypers, K. (2025) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2025.02.009 · Cited by 7

The nature of savings associated with a visuomotor adaptation task that involves one arm or both arms

James, R., Bao, S., D’Amato, A., & Wang, J. (2021) · Human Movement Science · doi:10.1016/j.humov.2021.102896 · Cited by 6

Even well-practiced movements benefit from repetition

Sutter, K., Wijdenes, L. O., van Beers, R. J., & Medendorp, W. P. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00003.2022 · Cited by 6

Can we improve slow learning in cerebellar patients?Preprint

Hulst, T., Mamlins, A., Frens, M. A., Chang, D., Goericke, S. L., Timmann, D., & Donchin, O. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.03.185959 · Cited by 6

Effect of sensory experience on motor learning strategy

Zhou, S.-H., Oetomo, D., Tan, Y., Mareels, I., & Burdet, E. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00470.2014 · Cited by 5

A systematic review of observational practice for adaptation of reaching movements

Rudisch, J., Holzhauer, L. K. H., Kravanja, K., Hamker, F. H., & Voelcker‐Rehage, C. (2024) · npj Science of Learning · doi:10.1038/s41539-024-00271-5 · Cited by 5

Motor adaptation and internal model formation in a robot-mediated forcefield

Taga, M., Curci, A., Pizzamigglio, S., Lacal, I., Turner, D., & Fu, C. H. Y. (2021) · Psychoradiology · doi:10.1093/psyrad/kkab007 · Cited by 3

Characterizing Motor System to Improve Training Protocols Used in Brain-Machine Interfaces Based on Motor Imagery

Alonso-Valerdi, L. M., & González‐Garrido, A. A. (2018) · InTech eBooks · doi:10.5772/intechopen.72667 · Cited by 5

Direct-effects and after-effects of dynamic adaptation on intralimb and interlimb transfer

Lei, Y., Akbar, A., & Wang, J. (2018) · Human Movement Science · doi:10.1016/j.humov.2018.05.014 · Cited by 5

Learning to shape virtual patient locomotor patterns: internal representations adapt to exploit interactive dynamics

Hasson, C. J., & Goodman, S. E. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00408.2018 · Cited by 5

Book Review

Krakauer, J. W. (2021) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2021.05.014 · Cited by 5

The relationship between habits and motor skills in humansPreprint

Du, Y., Krakauer, J. W., & Haith, A. M. (2021) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/9qrgd · Cited by 5

Success-efficient/failure-safe strategy for hierarchical reinforcement motor learning

Babič, J., Kunavar, T., Öztop, E., & Kawato, M. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013089 · Cited by 4

Biomimetic composite learning for robot motion control

Pan, Y., Sun, T., & Yu, H. (2016) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob.2016.7523622 · Cited by 4

Cortically Evoked Movement in Humans Reflects History of Prior Executions, Not Plan for Upcoming Movement

Suleiman, A., Solomonow‐Avnon, D., & Mawase, F. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.2170-22.2023 · Cited by 4

Using an ankle robotic device for motor performance and motor learning evaluation

Martelli, F., Palermo, E., Prete, Z. D., & Rossi, S. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e03262 · Cited by 4

Speech sensorimotor learning through a virtual vocal tract

Berry, J., North, C., Meyers, B. S., & Johnson, M. T. (2013) · The Journal of the Acoustical Society of America · doi:10.1121/1.4805649 · Cited by 4

Neural biomarkers of multiple motor-learning mechanisms in a real-world taskPreprint

Haar, S., & Faisal, A. A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.04.976951v1 · Cited by 4

Measures of explicit and implicit in motor learning: what we know and what we don’tPreprint

Maresch, J., Mudrik, L., & Donchin, O. (2020) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/pzr7t · Cited by 6

Physical Cognition in Altered Gravity: Link Between Sensorimotor and Cognitive AdaptabilityPreprint

Cheng, M., Han, D., Haq, M., & Ossmy, O. (2024) · doi:10.31234/osf.io/xm2j9 · Cited by 4

Policy-Gradient Reinforcement Learning as a General Theory of Practice-Based Motor Skill LearningPreprint

Haith, A. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.17.682587 · Cited by 7

When Can AI Models Explain Learning? Validity Criteria for AI as Cognitive Models in Education

Wang, P., Viberg, O., Law, E. L.-C., & Greiff, S. (2026) · Educational Psychology Review · doi:10.1007/s10648-026-10202-y · Cited by 3

Action control, forward models and expected rewards: representations in reinforcement learning

Rusanen, A.-M., Lappi, O., Kuokkanen, J., & Pekkanen, J. (2021) · Synthese · doi:10.1007/s11229-021-03408-w · Cited by 3

Efficacy of balance exercises intervention on postural control-related impairment in children with sensorineural hearing loss

Kamel, R. M., Khaireldin, A., Allah, M. A. G., Bakhoom, R. Y. F., Abdelhakiem, N. M., & Mehrem, E. S. (2024) · Neurorehabilitation · doi:10.3233/nre-230284 · Cited by 3

Impaired arbitration between reward-related decision-making strategies in Alcohol Users compared to Alcohol Non-Users: a computational modeling study

Ramakrishnan, S. A., Shaik, R., Kanagamani, T., Neppala, G. K., Chen, J., Fiore, V. G., Hammond, C. J., Srinivasan, S., Ivanov, I., Chakravarthy, V. S., et al. (2025) · NPP—Digital Psychiatry and Neuroscience · doi:10.1038/s44277-024-00023-8 · Cited by 3

Bayesian Integration in a Spiking Neural System for Sensorimotor Control

Grillo, M., Geminiani, A., Alessandro, C., D'Angelo, E. U., Pedrocchi, A., & Casellato, C. (2022) · Neural Computation · doi:10.1162/neco_a_01525 · Cited by 3

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Walia, P., Fu, Y., Norfleet, J., Schwaitzberg, S. D., Intes, X., De, S., Cavuoto, L. A., & Dutta, A. (2024) · Frontiers in Neuroergonomics · doi:10.3389/fnrgo.2023.1135729 · Cited by 3

On the Benefits of Sensorimotor Regularities as Design Constraints for Superpower Interactions in Mixed Reality

Li, J., & Kristensson, P. O. (2025) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2025.3549876 · Cited by 3

Aktuelle Motoriktheorien

Künzell, S. (2021) · Springer eBooks · doi:10.1007/978-3-662-53386-4_56-1 · Cited by 3

Model-free robust optimal feedback mechanisms of biological motor control

Bian, T., & Jiang, Z. (2016) · World Congress on Intelligent Control and Automation · doi:10.1109/wcica.2016.7578698 · Cited by 3

The Attention Schema Theory of Consciousness

Graziano, M. S. A. (2018) · Routledge eBooks · doi:10.4324/9781315676982-14 · Cited by 3

Learning generalizable visuomotor mappings fo r de novo skillsPreprint

Velázquez-Vargas, C. A., Daw, N. D., & Taylor, J. A. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.18.549179 · Cited by 3

Distinct learning, retention, and generalization in de novo learningPreprint

Gastrock, R. Q., Hart, B. M. ’., & Henriques, D. Y. P. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.02.560506 · Cited by 3

Updating BCI paradigms: Why to design in terms of the user?

Alonso-Valerdi, L. M., & Mercado, V. (2021) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner49283.2021.9441337 · Cited by 2

Modeling and Evaluation of Human Motor Learning by Finger Manipulandum

Okasha, A., Şengezer, S., Özdemir, O., Yozgatlıgil, C., Turgut, A. E., & Arıkan, K. B. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-24667-8_29 · Cited by 2

Reinforcement Motor Learning After Cerebellar Damage Is Related to State Estimation

White, C. M., Snow, E. C., & Therrien, A. S. (2023) · The Cerebellum · doi:10.1007/s12311-023-01615-4 · Cited by 2

Movement-goal relevant object shape properties act as poor but viable cues for the attribution of motor errors to external objects

Modchalingam, S., Ayala, M. N., & Henriques, D. Y. P. (2024) · PLoS ONE · doi:10.1371/journal.pone.0300020 · Cited by 2

Visual properties of action consequences and not environments affect context-specific motor learning

Modchalingam, S., King, A. J., Hart, B. M. ’., & Henriques, D. Y. P. (2025) · Journal of Neurophysiology · doi:10.1152/jn.00268.2024 · Cited by 2

Model-Based Optimization for the Personalization of Robot-Assisted Gait Training

Christou, A., Gordon, D., Stouraitis, T., Moreno, J. C., & Vijayakumar, S. (2025) · IEEE Transactions on Medical Robotics and Bionics · doi:10.1109/tmrb.2025.3550649 · Cited by 2

Visuomotor Memory Is Not Bound to Visual Motion

Warburton, M., Campagnoli, C., Mon-Williams, M. A., Mushtaq, F., & Morehead, J. R. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1884-24.2025 · Cited by 2

Double-leg attack vs. arm-drag: Examining muscle synergy consistency between elite and sub-elite freestyle wrestlers

Beinabaji, H., Eslami, M., Hosseininejad, S. E., Afrakoti, I. E. P., & Movaghar, A. F. (2025) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2025.112637 · Cited by 2

Intentional binding decreases during learning: Implications for sense of agency

Seghezzi, S., Parés-Pujolràs, E., & Haggard, P. (2025) · Quarterly Journal of Experimental Psychology · doi:10.1177/17470218251349521 · Cited by 2

Science of the gaps

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