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A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms

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Abstract

Motor learning encompasses a broad set of phenomena that requires a diverse set of experimental paradigms. However, excessive variation in tasks across studies creates fragmentation that can adversely affect the collective advancement of knowledge. Here, we show that motor learning studies tend toward extreme fragmentation in the choice of tasks, with almost no overlap between task paradigms across studies. We argue that this extreme level of task fragmentation poses serious theoretical and methodological barriers to advancing the field. To address these barriers, we propose the need for developing common ‘model’ task paradigms which could be widely used across labs. Combined with the open sharing of methods and data, we suggest that these model task paradigms could be an important step in increasing the robustness of the motor learning literature and facilitate the cumulative process of science.

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References

  • Abbas ZA, North JS (2018) Good-vs. poor-trial feedback in motor learning: the role of self-efficacy and intrinsic motivation across levels of task difficulty. Learn Instr 55:105–112

    Google Scholar 

  • Adams JA (1971) A closed-loop theory of motor learning. J Mot Behav 3:111–150

    CAS  PubMed  Google Scholar 

  • Adolph KE, Gilmore RO, Freeman C, Sanderson P, Millman D (2012) Toward open behavioral science. Psychol Inq 23:244–247

    PubMed  PubMed Central  Google Scholar 

  • Aiken CA, Pan Z, Van Gemmert AWA (2017) The effects of a two-step transfer on a visuomotor adaptation task. Exp Brain Res 235:3459–3467

    PubMed  Google Scholar 

  • Albers C, Lakens D (2018) When power analyses based on pilot data are biased: inaccurate effect size estimators and follow-up bias. J Exp Soc Psychol 74:187–195

    Google Scholar 

  • Baguley T (2009) Standardized or simple effect size: what should be reported? Br J Psychol Lond Engl 1953(100):603–617

    Google Scholar 

  • Bahrick HP, Fitts PM, Briggs GE (1957) Learning curves; Facts or artifacts? Psychol Bull 54:255–268

    CAS  PubMed  Google Scholar 

  • Bingham GP, Snapp-Childs W, Zhu Q (2018) Information about relative phase in bimanual coordination is modality specific (not amodal), but kinesthesis and vision can teach one another. Hum Mov Sci 60:98–106

    PubMed  Google Scholar 

  • Bond KM, Taylor JA (2015) Flexible explicit but rigid implicit learning in a visuomotor adaptation task. J Neurophysiol 113:3836–3849

    PubMed  PubMed Central  Google Scholar 

  • Boyer ÉO, Bevilacqua F, Susini P, Hanneton S (2017) Investigating three types of continuous auditory feedback in visuo-manual tracking. Exp Brain Res 235:691–701

    PubMed  Google Scholar 

  • Button KS, Ioannidis JPA, Mokrysz C, Nosek BA, Flint J, Robinson ESJ, Munafò MR (2013) Power failure: Why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 14:365–376

    CAS  PubMed  Google Scholar 

  • Caldwell A, Vigotsky AD, Nuckols G, Boardley I, Schmidt J, Tenan M, Skarabot J, Radel R, Naughton M, Schoenfeld BJ, et al. (2019). Moving sport and exercise science forward: a call for the adoption of more transparent research practices (SportRxiv). https://osf.io/fxe7a. Accessed July 16 2019.

  • Camerer CF, Dreber A, Holzmeister F, Ho T-H, Huber J, Johannesson M, Kirchler M, Nave G, Nosek BA, Pfeiffer T et al (2018) Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nat Hum Behav 2:637

    PubMed  Google Scholar 

  • Canaveral CA, Danion F, Berrigan F, Bernier P-M (2017) Variance in exposed perturbations impairs retention of visuomotor adaptation. J Neurophysiol 118:2745–2754

    PubMed  PubMed Central  Google Scholar 

  • Cardis M, Casadio M, Ranganathan R (2017) High variability impairs motor learning regardless of whether it affects task performance. J Neurophysiol 119:39–48

    PubMed  Google Scholar 

  • Cardis M, Casadio M, Ranganathan R (2018) High variability impairs motor learning regardless of whether it affects task performance. J Neurophysiol 119:39–48

    PubMed  Google Scholar 

  • Cattan E, Perrier P, Bérard F, Gerber S, Rochet-Capellan A (2018) Adaptation to visual feedback delays on touchscreens with hand vision. Exp Brain Res 236:3191–3201

    CAS  PubMed  Google Scholar 

  • Chambers CD (2013) Registered reports: a new publishing initiative at cortex. Cortex. J Devoted Study Nerv Syst Behav 49:609–610

    Google Scholar 

  • Chambers CD (2017) The seven deadly sins of psychology (Princeton, NJ: Princeton University Press).

  • Chauvel G, Maquestiaux F, Ruthruff E, Didierjean A, Hartley AA (2013) Novice motor performance: better not to verbalize. Psychon Bull Rev 20:177–183

    PubMed  Google Scholar 

  • Chauvel G, Wulf G, Maquestiaux F (2015) Visual illusions can facilitate sport skill learning. Psychon Bull Rev 22:717–721

    PubMed  Google Scholar 

  • Chien K-P, Chen S (2018) The influence of guided error-based learning on motor skills self-efficacy and achievement. J Mot Behav 50:275–284

    PubMed  Google Scholar 

  • Chua L-K, Wulf G, Lewthwaite R (2018) Onward and upward: optimizing motor performance. Hum Mov Sci 60:107–114

    PubMed  Google Scholar 

  • Couth S, Gowen E, Poliakoff E (2018) How does ageing affect grasp adaptation to a visual–haptic size conflict? Exp Brain Res 236:2173–2184

    CAS  PubMed  PubMed Central  Google Scholar 

  • Daou M, Lohse KR, Miller MW (2016) Expecting to teach enhances motor learning and information processing during practice. Hum Mov Sci 49:336–345

    PubMed  Google Scholar 

  • Daou M, Hutchison Z, Bacelar M, Rhoads JA, Lohse KR, Miller MW (2019) Learning a skill with the expectation of teaching it impairs the skill’s execution under psychological pressure. J Exp Psychol Appl 25:219–229

    PubMed  Google Scholar 

  • Day KA, Leech KA, Roemmich RT, Bastian AJ (2018) Accelerating locomotor savings in learning: compressing four training days to one. J Neurophysiol 119:2100–2113

    PubMed  PubMed Central  Google Scholar 

  • de Barros JAC, Tani G, Corrêa UC (2017) Effects of practice schedule and task specificity on the adaptive process of motor learning. Hum Mov Sci 55:196–210

    PubMed  Google Scholar 

  • Donchin E (1989) The learning strategies project: introductory remarks. Acta Psychol (Amst) 71:1–15

    Google Scholar 

  • Dotov D, Froese T (2018) Entraining chaotic dynamics: a novel movement sonification paradigm could promote generalization. Hum Mov Sci 61:27–41

    PubMed  Google Scholar 

  • Doyon J, Korman M, Morin A, Dostie V, Tahar AH, Benali H, Karni A, Ungerleider LG, Carrier J (2009) Contribution of night and day sleep vs. simple passage of time to the consolidation of motor sequence and visuomotor adaptation learning. Exp Brain Res 195:15–26

    PubMed  PubMed Central  Google Scholar 

  • Dyer JF, Stapleton P, Rodger MWM (2017) Advantages of melodic over rhythmic movement sonification in bimanual motor skill learning. Exp Brain Res 235:3129–3140

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fazeli D, Taheri H, Saberi Kakhki A (2017) Random versus blocked practice to enhance mental representation in golf putting. Percept Mot Skills 124:674–688

    PubMed  Google Scholar 

  • Fialho JVAP, Tresilian JR (2017) Intercepting accelerated moving targets: effects of practice on movement performance. Exp Brain Res 235:1257–1268

    PubMed  PubMed Central  Google Scholar 

  • Frank C, Land WM, Schack T (2013) Mental representation and learning: the influence of practice on the development of mental representation structure in complex action. Psychol Sport Exerc 14:353–361

    Google Scholar 

  • Frank C, Land WM, Popp C, Schack T (2014) Mental representation and mental practice: experimental investigation on the functional links between motor memory and motor imagery. PLoS ONE 9:e95175

    PubMed  PubMed Central  Google Scholar 

  • Frank C, Land WM, Schack T (2016) Perceptual-cognitive changes during motor learning: the influence of mental and physical practice on mental representation, gaze behavior, and performance of a complex action. Front Psychol 6: https://www.frontiersin.org/articles/10.3389/fpsyg.2015.01981/full. Accessed Aug 27 2019.

  • Frank MC, Bergelson E, Bergmann C, Cristia A, Floccia C, Gervain J, Hamlin JK, Hannon EE, Kline M, Levelt C et al (2017) A Collaborative approach to infant research: promoting reproducibility, best practices, and theory-building. Infancy Off J Int Soc Infant Stud 22:421–435

    Google Scholar 

  • Frank C, Kim T, Schack T (2018) Observational practice promotes action-related order formation in long-term memory: investigating action observation and the development of cognitive representation in complex motor action. J Mot Learn Dev 6:53–72

    Google Scholar 

  • French MA, Morton SM, Charalambous CC, Reisman DS (2018) A locomotor learning paradigm using distorted visual feedback elicits strategic learning. J Neurophysiol 120:1923–1931

    PubMed  PubMed Central  Google Scholar 

  • Gilmore RO, Adolph KE (2017) Video can make behavioural science more reproducible. Nat Hum Behav 1:0128

    PubMed  PubMed Central  Google Scholar 

  • Gorgolewski KJ, Poldrack RA (2016) A practical guide for improving transparency and reproducibility in neuroimaging research. PLOS Biol 14:e1002506

    PubMed  PubMed Central  Google Scholar 

  • Grand KF, Daou M, Lohse KR, Miller MW (2017) Investigating the mechanisms underlying the effects of an incidental choice on motor learning. J Mot Learn Dev 5:207–226

    Google Scholar 

  • Guadagnoli MA, Lee TD (2004) Challenge point: a framework for conceptualizing the effects of various practice conditions in motor learning. J Mot Behav 36:212–224

    PubMed  Google Scholar 

  • Haarman JAM, Choi JT, Buurke JH, Rietman JS, Reenalda J (2017) Performance of a visuomotor walking task in an augmented reality training setting. Hum Mov Sci 56:11–19

    PubMed  Google Scholar 

  • Hasson CJ, Zhang Z, Abe MO, Sternad D (2016) Neuromotor noise is malleable by amplifying perceived errors. PLoS Comput Biol 12:e1005044

    PubMed  PubMed Central  Google Scholar 

  • He K, Liang Y, Abdollahi F, Fisher Bittmann M, Kording K, Wei K (2016) The statistical determinants of the speed of motor learning. PLoS Comput Biol 12:e1005023

    PubMed  PubMed Central  Google Scholar 

  • Hebert E (2018) The effects of observing a learning model (or two) on motor skill acquisition. J Mot Learn Dev 6:4–17

    Google Scholar 

  • Hinkel-Lipsker JW, Hahn ME (2017) The effects of variable practice on locomotor adaptation to a novel asymmetric gait. Exp Brain Res 235:2829–2841

    PubMed  Google Scholar 

  • Hinkel-Lipsker JW, Hahn ME (2018) Coordinative structuring of gait kinematics during adaptation to variable and asymmetric split-belt treadmill walking—a principal component analysis approach. Hum Mov Sci 59:178–192

    PubMed  Google Scholar 

  • Holland P, Codol O, Galea JM (2018) Contribution of explicit processes to reinforcement-based motor learning. J Neurophysiol 119:2241–2255

    PubMed  PubMed Central  Google Scholar 

  • Itaguchi Y, Fukuzawa K (2018) Influence of speed and accuracy constraints on motor learning for a trajectory-based movement. J Mot Behav 50:653–663

    PubMed  Google Scholar 

  • Jalali R, Miall RC, Galea JM (2017) No consistent effect of cerebellar transcranial direct current stimulation on visuomotor adaptation. J Neurophysiol 118:655–665

    PubMed  PubMed Central  Google Scholar 

  • Jiang W, Yuan X, Yin C, Wei K (2018) Visuomotor learning is dependent on direction-specific error saliency. J Neurophysiol 120:162–170

    PubMed  Google Scholar 

  • Kaipa R, Kaipa RM (2018) Role of constant, random and blocked practice in an electromyography-based oral motor learning task. J Mot Behav 50:599–613

    PubMed  Google Scholar 

  • Kaipa R, Robb M, Jones R (2017) The effectiveness of constant, variable, random, and blocked practice in speech-motor learning. J Mot Learn Dev 5:103–125

    Google Scholar 

  • Karlinsky A, Hodges NJ (2018) Dyad practice impacts self-directed practice behaviors and motor learning outcomes in a contextual interference paradigm. J Mot Behav 50:579–589

    PubMed  Google Scholar 

  • Kearney PE (2015) A distal focus of attention leads to superior performance on a golf putting task. Int J Sport Exerc Psychol 13:371–381

    Google Scholar 

  • Kerr R, Booth B (1978) Specific and varied practice of motor skill. Percept Mot Skills 46:395–401

    CAS  PubMed  Google Scholar 

  • Kim T, Frank C, Schack T (2017) A Systematic investigation of the effect of action observation training and motor imagery training on the development of mental representation structure and skill performance. Front Hum Neurosci. https://link-galegroup-com.proxy2.cl.msu.edu/apps/doc/A511188490/AONE?sid=lms. Accessed Aug 27 2019.

  • Kim JH, Han JK, Han DH (2018) Training effects of interactive metronome® on golf performance and brain activity in professional woman golf players. Hum Mov Sci 61:63–71

    PubMed  Google Scholar 

  • Kimura T, Kaneko F, Nagahata K, Shibata E, Aoki N (2017) Working memory training improves dual-task performance on motor tasks. J Mot Behav 49:388–397

    PubMed  Google Scholar 

  • Klein O, Hardwicke TE, Aust F, Breuer J, Danielsson H, Mohr AH, Ijzerman H, Nilsonne G, Vanpaemel W, Frank MC (2018) A Practical guide for transparency in psychological science. Collabra Psychol 4:20

    Google Scholar 

  • Krajenbrink H, van Abswoude F, Vermeulen S, van Cappellen S, Steenbergen B (2018) Motor learning and movement automatization in typically developing children: the role of instructions with an external or internal focus of attention. Hum Mov Sci 60:183–190

    PubMed  Google Scholar 

  • Krakauer JW, Mazzoni P (2011) Human sensorimotor learning: adaptation, skill, and beyond. Curr Opin Neurobiol 21:636–644

    CAS  PubMed  Google Scholar 

  • Krause D, Brüne A, Fritz S, Kramer P, Meisterjahn P, Schneider M, Sperber A (2014) Learning of a golf putting task with varying contextual interference levels induced by feedback schedule in novices and experts. Percept Mot Skills 118:384–399

    PubMed  Google Scholar 

  • Krause D, Agethen M, Zobe C (2018) Error feedback frequency affects automaticity but not accuracy and consistency after extensive motor skill practice. J Mot Behav 50:144–154

    PubMed  Google Scholar 

  • Krishnan C, Washabaugh EP, Seetharaman Y (2015) A low cost real-time motion tracking approach using webcam technology. J Biomech 48:544–548

    PubMed  Google Scholar 

  • Kumar N, Kumar A, Sonane B, Mutha PK (2018) Interference between competing motor memories developed through learning with different limbs. J Neurophysiol 120:1061–1073

    PubMed  PubMed Central  Google Scholar 

  • Kwakkel G, Lannin NA, Borschmann K, English C, Ali M, Churilov L, Saposnik G, Winstein C, van Wegen EE, Wolf SL et al (2017) Standardized measurement of sensorimotor recovery in stroke trials: consensus-based core recommendations from the stroke recovery and rehabilitation roundtable. Int J Stroke Off J Int Stroke Soc 12:451–461

    Google Scholar 

  • Lakens D, Scheel AM, Isager PM (2018) Equivalence testing for psychological research: a tutorial. Adv Methods Pract Psychol Sci 1:259–269

    Google Scholar 

  • Land WM, Frank C, Schack T (2014) The influence of attentional focus on the development of skill representation in a complex action. Psychol Sport Exerc 15:30–38

    Google Scholar 

  • Lawrence GP, Cassell VE, Beattie S, Woodman T, Khan MA, Hardy L, Gottwald VM (2014) Practice with anxiety improves performance, but only when anxious: evidence for the specificity of practice hypothesis. Psychol Res 78:634–650

    PubMed  Google Scholar 

  • Lee TD, Genovese ED (1989) Distribution of practice in motor skill acquisition: different effects for discrete and continuous tasks. Res Q Exerc Sport 60:59–65

    CAS  PubMed  Google Scholar 

  • Leow L-A, Gunn R, Marinovic W, Carroll TJ (2017) Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time. J Neurophysiol 118:666–676

    PubMed  PubMed Central  Google Scholar 

  • Levac D, Driscoll K, Galvez J, Mercado K, O’Neil L (2017) OPTIMAL practice conditions enhance the benefits of gradually increasing error opportunities on retention of a stepping sequence task. Hum Mov Sci 56:129–138

    PubMed  Google Scholar 

  • Lewthwaite R, Chiviacowsky S, Drews R, Wulf G (2015) Choose to move: the motivational impact of autonomy support on motor learning. Psychon Bull Rev 22:1383–1388

    PubMed  Google Scholar 

  • Lin T-H, Denomme A, Ranganathan R (2018) Learning alternative movement coordination patterns using reinforcement feedback. Exp Brain Res. https://doi.org/10.1007/s00221-018-5227-1

    Article  PubMed  PubMed Central  Google Scholar 

  • Lo AC, Guarino PD, Richards LG, Haselkorn JK, Wittenberg GF, Federman DG, Ringer RJ, Wagner TH, Krebs HI, Volpe BT et al (2010) Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med 362:1772–1783

    CAS  PubMed  PubMed Central  Google Scholar 

  • Lohse K, Buchanan T, Miller M (2016) Underpowered and overworked: problems with data analysis in motor learning studies. J Mot Learn Dev 4:37–58

    Google Scholar 

  • LoJacono CT, MacPherson RP, Kuznetsov NA, Raisbeck LD, Ross SE, Rhea CK (2018) Obstacle crossing in a virtual environment transfers to a real environment. J Mot Learn Dev 6:234–249

    Google Scholar 

  • Maeda RS, McGee SE, Marigold DS (2016) Consolidation of visuomotor adaptation memory with consistent and noisy environments. J Neurophysiol 117:316–326

    PubMed  PubMed Central  Google Scholar 

  • Mané A, Donchin E (1989) The space fortress game. Acta Psychol (Amst) 71:17–22

    Google Scholar 

  • Mansfield A, Aqui A, Fraser JE, Rajachandrakumar R, Lakhani B, Patterson KK (2017) Can augmented feedback facilitate learning a reactive balance task among older adults? Exp Brain Res 235:293–304

    PubMed  Google Scholar 

  • Marchal-Crespo L, Rappo N, Riener R (2017) The effectiveness of robotic training depends on motor task characteristics. Exp Brain Res 235:3799–3816

    PubMed  Google Scholar 

  • Mathis A, Mamidanna P, Cury KM, Abe T, Murthy VN, Mathis MW, Bethge M (2018) DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat Neurosci 21:1281–1289

    CAS  PubMed  Google Scholar 

  • McGregor HR, Gribble PL (2017) Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing. J Neurophysiol 118:1235–1243

    PubMed  PubMed Central  Google Scholar 

  • McGregor HR, Cashaback JGA, Gribble PL (2018) Somatosensory perceptual training enhances motor learning by observing. J Neurophysiol 120:3017–3025

    PubMed  PubMed Central  Google Scholar 

  • McKenna E, Bray LCJ, Zhou W, Joiner WM (2017) The absence or temporal offset of visual feedback does not influence adaptation to novel movement dynamics. J Neurophysiol 118:2483–2498

    PubMed  PubMed Central  Google Scholar 

  • Meira CM, Fairbrother JT (2018) Ego-oriented learners show advantage in retention and transfer of balancing skill. J Mot Learn Dev 6:209–219

    Google Scholar 

  • Melendez-Calderon A, Tan M, Bittmann MF, Burdet E, Patton JL (2017) Transfer of dynamic motor skills acquired during isometric training to free motion. J Neurophysiol 118:219–233

    PubMed  PubMed Central  Google Scholar 

  • Milner TE, Firouzimehr Z, Babadi S, Ostry DJ (2018) Different adaptation rates to abrupt and gradual changes in environmental dynamics. Exp Brain Res 236:2923–2933

    PubMed  Google Scholar 

  • Mischel, W. (2008). The Toothbrush Problem. APS Obs. 21. Available at: https://www.psychologicalscience.org/observer/the-toothbrush-problem [Accessed April 4, 2019].

  • Moshontz H, Campbell L, Ebersole CR, IJzerman H, Urry HL, Forscher PS, Grahe JE, McCarthy RJ, Musser ED, Antfolk J et al (2018) The Psychological Science Accelerator: advancing psychology through a distributed collaborative network. Adv. Methods Pract. Psychol. Sci. 1:501–515

    PubMed  PubMed Central  Google Scholar 

  • Munzert J, Maurer H, Reiser M (2014) Verbal-motor attention-focusing instructions influence kinematics and performance on a golf-putting task. J Mot Behav 46:309–318

    PubMed  Google Scholar 

  • Navarro M, van der Kamp J, Schor P, Savelsbergh GJP (2018) Implicit learning increases shot accuracy of football players when making strategic decisions during penalty kicking. Hum Mov Sci 61:72–80

    PubMed  Google Scholar 

  • Neville K-M, Trempe M (2017) Serial practice impairs motor skill consolidation. Exp Brain Res 235:2601–2613

    PubMed  Google Scholar 

  • Newell, K.M. (1986). Constraints on the development of coordination. In: Motor development in children: Aspects of coordination and control, M. G. Wade and H. T. A. Whiting, eds. (Nijhoff).

  • Newell KM (1989) On task and theory specificity. J Mot Behav 21:92–96

    CAS  PubMed  Google Scholar 

  • Newell KM (1991) Motor skill acquisition. Annu Rev Psychol 42:213–237

    CAS  PubMed  Google Scholar 

  • Nunes ME, de S, Correa UC, Souza MGTX, de Basso L, Coelho DB, Santos S (2019) No improvement on the learning of golf putting by older persons with self-controlled knowledge of performance. J Aging Phys Act 27:300–308

  • Ong NT, Hodges NJ (2018) Balancing our perceptions of the efficacy of success-based feedback manipulations on motor learning. J Mot Behav 50:614–630

    PubMed  Google Scholar 

  • Open Science Collaboration (2015) Estimating the reproducibility of psychological science. Science 349:aac716

    Google Scholar 

  • Overduin SA, Richardson AG, Lane CE, Bizzi E, Press DZ (2006) Intermittent practice facilitates stable motor memories. J Neurosci 26:11888–11892

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pacheco MM, Newell KM (2018) Learning a specific, individual and generalizable coordination function: evaluating the variability of practice hypothesis in motor learning. Exp Brain Res 236:3307–3318

    PubMed  Google Scholar 

  • Palmer K, Chiviacowsky S, Wulf G (2016) Enhanced expectancies facilitate golf putting. Psychol Sport Exerc 22:229–232

    Google Scholar 

  • Panzer S, Kennedy D, Wang C, Shea CH (2018) The simplest acquisition protocol is sometimes the best protocol: performing and learning a 1:2 bimanual coordination task. Exp Brain Res 236:539–550

    PubMed  Google Scholar 

  • Pashler H, Harris CR (2012) Is the replicability crisis overblown? Three arguments examined. Perspect Psychol Sci 7:531–536

    PubMed  Google Scholar 

  • Pinder RA, Davids K, Renshaw I, Araújo D (2011) Representative learning design and functionality of research and practice in sport. J Sport Exerc Psychol 33:146–155

    PubMed  Google Scholar 

  • Raisbeck LD, Diekfuss JA (2017) Verbal cues and attentional focus: a simulated target-shooting experiment. J Mot Learn Dev 5:148–159

    Google Scholar 

  • Reilly KJ, Pettibone C (2017) Vowel generalization and its relation to adaptation during perturbations of auditory feedback. J Neurophysiol 118:2925–2934

    PubMed  PubMed Central  Google Scholar 

  • Ring C, Cooke A, Kavussanu M, McIntyre D, Masters R (2015) Investigating the efficacy of neurofeedback training for expediting expertise and excellence in sport. Psychol Sport Exerc 16:118–127

    Google Scholar 

  • Rossum JHAV, Bootsma RJ (1989) The underarm throw for accuracy in children. J Sports Sci 7:101–112

    PubMed  Google Scholar 

  • Ruffino C, Papaxanthis C, Lebon F (2017) The influence of imagery capacity in motor performance improvement. Exp Brain Res 235:3049–3057

    CAS  PubMed  Google Scholar 

  • Russell DM, Newell KM (2007) On No-KR tests in motor learning, retention and transfer. Hum Mov Sci 26:155–173

    PubMed  Google Scholar 

  • Schmitz G, Bock OL (2017) Properties of intermodal transfer after dual visuo- and auditory-motor adaptation. Hum Mov Sci 55:108–120

    PubMed  Google Scholar 

  • Seidler RD, Gluskin BS, Greeley B (2016) Right prefrontal cortex transcranial direct current stimulation enhances multi-day savings in sensorimotor adaptation. J Neurophysiol 117:429–435

    PubMed  PubMed Central  Google Scholar 

  • Shuggi IM, Shewokis PA, Herrmann JW, Gentili RJ (2018) Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective. Exp Brain Res 236:433–451

    PubMed  Google Scholar 

  • Simmons JP, Nelson LD, Simonsohn U (2011) False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychol Sci 22:1359–1366

    PubMed  Google Scholar 

  • Sobierajewicz J, Przekoracka-Krawczyk A, JaÅ›kowski W, van der Lubbe RHJ (2017) How effector-specific is the effect of sequence learning by motor execution and motor imagery? Exp Brain Res 235:3757–3769

    CAS  PubMed  PubMed Central  Google Scholar 

  • Song Y, Smiley-Oyen AL (2017) Probability differently modulating the effects of reward and punishment on visuomotor adaptation. Exp Brain Res 235:3605–3618

    PubMed  Google Scholar 

  • Swinnen SP (1996) Information feedback for motor skill learning: a review. In: Zelaznik HN (ed) Advances in motor learning and control. Human Kinetics, Champaign, IL, pp 37–66

    Google Scholar 

  • Thorp EB, Kording KP, Mussa-Ivaldi FA (2016) Using noise to shape motor learning. J Neurophysiol 117:728–737

    PubMed  PubMed Central  Google Scholar 

  • van Ginneken WF, Poolton JM, Capio CM, van der Kamp J, Choi CSY, Masters RSW (2018) Conscious control is associated with freezing of mechanical degrees of freedom during motor learning. J Mot Behav 50:436–456

    PubMed  Google Scholar 

  • Vine S, Moore L, Cooke A, Ring C, Wilson M (2013) Quiet eye training: a means to implicit motor learning quiet eye training: a means to implicit motor learning. Int J Sport Psychol 44:367

    Google Scholar 

  • Walker B, Kording K (2013) The database for reaching experiments and models. PLoS ONE 8:e78747

    PubMed  PubMed Central  Google Scholar 

  • Wulf G, Shea CH (2002) Principles derived from the study of simple skills do not generalize to complex skill learning. Psychon Bull Rev 9:185–211

    PubMed  Google Scholar 

  • Wulf G, Iwatsuki T, Machin B, Kellogg J, Copeland C, Lewthwaite R (2018) Lassoing skill through learner choice. J Mot Behav 50:285–292

    PubMed  Google Scholar 

  • Yartsev MM (2017) The emperor’s new wardrobe: rebalancing diversity of animal models in neuroscience research. Science 358:466–469

    CAS  PubMed  Google Scholar 

  • Yen S-C, Olsavsky LC, Cloonan CM, Llanos AR, Dwyer KJ, Nabian M, Farjadian AB (2018) An examination of lower limb asymmetry in ankle isometric force control. Hum Mov Sci 57:40–49

    PubMed  Google Scholar 

  • Yokoi A, Bai W, Diedrichsen J (2016) Restricted transfer of learning between unimanual and bimanual finger sequences. J Neurophysiol 117:1043–1051

    PubMed  PubMed Central  Google Scholar 

  • Zhu FF, Yeung AY, Poolton JM, Lee TMC, Leung GKK, Masters RSW (2015) Cathodal transcranial direct current stimulation over left dorsolateral prefrontal cortex area promotes implicit motor learning in a golf putting task. Brain Stimulat 8:784–786

    Google Scholar 

  • Ziv G, Lidor R (2015) Focusing attention instructions, accuracy, and quiet eye in a self-paced task—an exploratory study. Int J Sport Exerc Psychol 13:104–120

    Google Scholar 

  • Zwaan RA, Etz A, Lucas RE, Donnellan MB (2018) Making replication mainstream. Behav Brain Sci 41:e120

    Google Scholar 

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Acknowledgements

The authors thank Dr. Chandramouli Krishnan for his comments on a previous version of this manuscript. The authors also thank Drs. Les Carlton and Mary Carlton for their comments, especially for pointing us to the work on the Learning strategies project. This material is based upon work supported by the National Science Foundation under Grant No. 1823889 (RR) and a National Science Foundation Graduate Fellowship (ADT).

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Authors and Affiliations

  1. Department of Kinesiology, Michigan State University, 308 W Circle Dr, East Lansing, MI, 48824, USA

    Rajiv Ranganathan, Aimee D. Tomlinson, Rakshith Lokesh, Tzu-Hsiang Lin & Priya Patel

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  1. Rajiv Ranganathan
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  2. Aimee D. Tomlinson
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  3. Rakshith Lokesh
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  4. Tzu-Hsiang Lin
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  5. Priya Patel
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Correspondence to Rajiv Ranganathan.

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Communicated by Patrick Haggard.

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Ranganathan, R., Tomlinson, A.D., Lokesh, R. et al. A tale of too many tasks: task fragmentation in motor learning and a call for model task paradigms. Exp Brain Res 239, 1–19 (2021). https://doi.org/10.1007/s00221-020-05908-6

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  • DOI: https://doi.org/10.1007/s00221-020-05908-6

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