Skip to main content
The Journal of Physiology logoLink to The Journal of Physiology
. 2007 Aug 23;586(Pt 1):65–70. doi: 10.1113/jphysiol.2007.142661

The olympic brain. Does corticospinal plasticity play a role in acquisition of skills required for high-performance sports?

Jens Bo Nielsen 1, Leonardo G Cohen 2
PMCID: PMC2375560  PMID: 17717010

Abstract

Non-invasive electrophysiological and imaging techniques have recently made investigation of the intact behaving human brain possible. One of the most intriguing new research areas that have developed through these new technical advances is an improved understanding of the plastic adaptive changes in neuronal circuitries underlying improved performance in relation to skill training. Expansion of the cortical representation or modulation of corticomotor excitability of specific muscles engaged in task performance is required for the aquisition of the skill. These changes at cortical level appear to be paralleled by changes in transmission in spinal neuronal circuitries, which regulate the contribution of sensory feedback mechanisms to the execution of the task. Such adaptive changes also appear to be essential for the consolidation of a memory of performance of motor tasks and thus for the lasting ability of performing highly skilled movements such as those required for Olympic sports.


It looks easy – and it may feel easy – but the seemingly effortless coordination of muscles acting at different body segments and joints, which is necessary in any high-performance sport, is still far beyond anything that can be achieved by robotic engineering and requires much more computational power than what can be delivered by the most powerful computers available. The beauty of any gymnastic move or the overwhelming power of a javelin throw relies on the ability of the nervous system to ensure that the right muscles are activated to the proper extent at the right time, and in the right sequence. It is trivial to note that this has been predominantly achieved by repeated training day in and day out for years on end and that the mastering of any sport at a level qualifying for an Olympic medal is not achieved by reading all available literature on the subject, but rather by the dull and tedious repeated performance of the motor task involved until it is mastered to perfection.

Neuroscience has made major advances within the past 10–20 years in order to understand the mechanisms involved in this gradual mastering of motor skills with repeated performance. A major breakthrough in our mechanistic understanding of these processes has been the introduction of non-invasive electrophysiological and imaging techniques, which have made investigations of the intact human brain possible. Such studies have revealed how different parts of the human nervous system change activity as new tasks are learned and an understanding of the way that networks in the brain build and optimize the motor programs that are responsible for coordination of muscle activity involved in complex motor learning is now emerging. In this short review we will briefly describe plastic changes in the corticospinal pathway, which is responsible for conveying the command for voluntary movements from the cortex to the spinal cord.

Plasticity in the motor cortex and corticospinal tract

Whenever we optimize the performance of a motor skill by repeatedly performing the task, there is initially an expansion in the volume of the primary motor cortex and/or an increase in motor cortical excitability of the cortical representation devoted to the muscles involved in that task in the primary motor cortex. This was demonstrated originally by Pascual-Leone et al. (1995a) for learning of sequences of finger movements (piano playing) using transcranial magnetic stimulation (TMS) by which corticospinal projections to specific muscles may be activated in the intact behaving human. Expansions of the cortical representation/increases in corticomotor excitability of specific muscles has since then been demonstrated in relation to the acquisition of a number of different motor skills involving both the hand (Pascual-Leone et al. 1995a; Latash et al. 2003), arm (Jensen et al. 2005) and leg (Perez et al. 2004). Using functional magnetic resonance imaging, expansions of the local cerebral blood flow have also been demonstrated in relation to practice of a complex sequence of finger movements (Karni et al. 1995).

It is difficult to draw any firm conclusions regarding underlying neuronal mechanisms based on observations of the behaviour of muscular responses evoked by TMS, but there seems to be several processes at play (see Fig. 1 for schematic examples of different forms of plasticity in healthy volunteers and patients with brain lesions).

Figure 1. The purpose of this figure is to depict schematically some of the many different ways in which plasticity in the human motor cortex can be studied physiologically in health and disease.

Figure 1

TMS application over the hand representation of M1 (Yousry et al. 1997) in a representative subject showing: A, maximum calculated induced field for this particular 8-shaped coil (light red dot) and position (green oval) using a stereotactic TMS device (Nexstim in this case) which localizes the target scalp position (in this case M1) on the same subject anatomical MRI; B, representative distribution of the motor map for a hand muscle (scalp locations which, upon TMS stimulation, elicited MEP responses from the target hand muscles) before training in a normal volunteer; C, centrifugal enlargement of the motor map (increase in the number of scalp positions which, upon stimulation, evoked MEP in target hand muscles) in a healthy volunteer, often described after motor training (see text). Note that a similar result in terms of centrifugal expansion of a motor map could be induced by an expansion in the motor cortical representation of that muscle or by an increase in motor cortical or spinal excitability of a topographically unchanged motor cortical representation (Ridding & Rothwell, 1995); D, enlargement in the motor map that is directionally more specific, showing a medial expansion of a hand muscle representation in M1 towards the upper arm representations, a more precise example of representational plasticity, as shown for example in amputees with phantom limb pain (Karl et al. 2001). For a detailed discussion of the differences between C and D see Ridding & Rothwell (1995), Ziemann et al. (1998, 2002); E, example of situations in which responses from a left hand or forearm muscles can be obtained by stimulation of the contralesional left M1 in cases of hemispherectomy (red posterior circle in the intact hemisphere) or even from the contralesional dorsal premotor cortex (red anterior circle) in patients with more severe forms of stroke (Benecke et al. 1991; Cohen et al. 1991; Johansen-Berg et al. 2002). The black oval depicts in diagrammatic form a large stroke or hemispherectomy engaging the right hemisphere; F, example of the involvement of ipsilesional dorsal premotor cortex, anterior to M1, in motor control of the paretic hand in patients with less severe stroke (Fridman et al. 2004).

Voluntary activation of a muscle seems to involve a rapid (within some minutes of training), but short-lived (5–10 min) expansion of the representation or/and increase in corticomotor excitability of the muscle, which in all likelihood reflects a functional unmasking (possibly change in the level of GABAergic inhibition leading to increased excitability of corticospinal cells) of existing corticospinal projections to the muscle (Classen et al. 1998; Perez et al. 2004). In addition to changes in different muscle representations, repetition of stereotyped movements results in encoding of elementary motor memories in the primary motor cortex and probably other cortical areas that encode the kinematic details of the practiced movements, a form of memory for movement (Classen et al. 1998; Butefisch et al. 2000; Stefan et al. 2005). This may be regarded as a first step in skill acquisition as the expansion of the cortical representation is more pronounced the more engaging the task and the more learning required to accomplish it (Pascual-Leone et al. 1995; Perez et al. 2004; Jensen et al. 2005). One interesting feature of this form of memory formation for movement is that it can be encoded by action observation, that is, attentive observation of another individual performing a motor task can facilitate the representation of that movement in the primary motor cortex of the observer (Stefan et al. 2005). This form of action observation can enhance training effects under certain conditions (Celnik et al. 2006). One other relevant finding in the literature is that a variety of pharmacological agents can enhance this memory formation including dextroamphetamines (Butefisch et al. 2002) and dopaminergic agents (Floel et al. 2005a,b) in both healthy subjects and in patients with brain lesions like stroke. One consideration, very much under discussion these days, is the extent to which these pharmacological interventions influence performance in healthy volunteers, with obvious implications in relation to doping in sports.

Over the last few years, there has been an important effort to understand the mechanisms underlying reorganizational changes in the brain elicited by different forms of motor training. In one influential study, it was found that repetitive TMS applied to the primary motor cortex at a rate of 1 per second in the breaks inbetween training sessions may prevent the expansion of the cortical representation of the trained muscle and interfere with the consolidation of the learned task (Müllbacher et al. 2002). Repeated training of the task over several days or weeks leads to more or less long lasting expansion of the cortical representation (Karni et al. 1995; Pascual-Leone et al. 1995a, 1999; Jensen et al. 2005), which may reflect structural reorganization of the cortical networks activated by TMS or unmasking of cortical regions that before practice were engaged in performing other tasks (Sanes & Donoghue, 2000). Pascual-Leone et al. (1999) observed that the cortical representation of the trained muscle decreased again once the task had been acquired after some weeks of training despite continued training. This indicates that this longer-lasting cortical expansion may also be more related to the acquisition process than to the improvement in the performance of the task per se. That the expansion of the cortical representation is not simply linked to muscle use, but to the way in which the muscle is used, is indicated by the studies by Carroll et al. (2002) and Jensen et al. (2005). Despite strength training every second day for several weeks leading to 20–30% increases in muscle strength, no changes in cortical excitability were observed in these studies. The picture emerging is consistent with the view that skill acquisition may recruit a large amount of cortical resources which, after the task is well learned, is performed by smaller cortical regions. If this is the case, the release of cortical resources after the task is learned would leave these areas available for engagement in new learning tasks. However, more work is required to test this general model.

Several studies have indicated that daily motor practice of certain tasks may lead to longer lasting and possibly permanent changes in the cortical representation of muscles. This was originally reported by Pascual-Leone et al. (1993) who observed that blind persons who used one hand to read Braille had a larger representation of the first dorsal interossus muscle of that hand as compared with the other hand and that of blind control subjects. On the other hand, later investigations demonstrated that these changes in blind individuals reading Braille may fade after a weekend not practicing (Pascual-Leone et al. 1995b). Magnetic resonance imaging studies have also shown that musicians have a larger volume of the sensorimotor cortex than other subjects (Gaser & Schlaug, 2003), which may be related to a larger representation of the fingers in the sensory cortex (Elbert et al. 1995) and a higher excitability of the corticospinal projections to the fingers (Rosenkranz et al. 2007). Of direct relevance to sports, Pearce et al. (2000) have also reported that the cortical representation of the hand used for playing is larger in elite racquet players as compared with control subjects. It is also of interest that the acquisition of a motor skill as, for example, when learning to generate motor sequences, results not only in performance improvements in the practicing hand but also in the other resting hand, a process referred to as an intermanual transfer of skill learning. This process results in characteristic changes in intracortical inhibitory (predominantly GABAergic) mechanisms and also in interhemispheric (predominantly transcallosal) interactions (Perez et al. 2007).

Plasticity in spinal cord function associated with training

A very significant part of the corticospinal tract is indirectly connected to the spinal motoneurones via spinal interneuronal networks and a large part of the descending motor command is thus influenced by changes in transmission in spinal networks (Nielsen, 2004). While it is widely accepted that cortical reorganization relates in different ways to the process of skill acquisition, it has so far been much less considered whether reorganization in the spinal networks might contribute as well. However, it has been known for quite some time that the monosynaptic spinal stretch reflex may be down- and up-regulated through operant conditioning and that the corticospinal tract is essential for this regulation (Wolpaw, 1994), but evidence for plastic changes related to motor learning have only appeared recently. The size of the soleus H-reflex, which is an equivalent of the stretch reflex evoked by electrical stimulation of the tibial nerve, is thus markedly smaller in ballet dancers than in other subjects with a similar level of daily physical activity (Nielsen et al. 1993). This may reflect habitually smaller reflexes in the dancers, but it may also be caused by lasting adaptive changes in the size of the reflex to the repeated performance of the specific motor repertoire of ballet dancers. One characteristic of ballet dancing is the necessity of high stability in the ankle joint which is ensured by co-contracting the ankle muscles. H-reflexes are indeed depressed during such co-contraction (Nielsen & Kagamihara, 1993) and training of co-contraction tasks lead to a progressive reduction in the reflex size (Monica Perez, Jesper Lundbye-Jensen & Jens Bo Nielsen; unpublished observations). The most likely mechanism for this depression is increased presynaptic inhibition of the Ia afferent terminals on the spinal motoneurones under the control of the corticospinal tract). Increased presynaptic inhibition has also been shown to be responsible for the depression of the H-reflex in relation to training of a task requiring integration of visual and proprioceptive feedback (Perez et al. 2005). Like the expansion of the cortical representation of muscles, this depression appears to be closely associated to the acquisition of the motor task, rather than its performance, and it may in this specific case relate to the necessity of integrating the feedback from the two sensory systems at a cortical level during the acquisition of the new skill. Plastic adaptive changes at spinal and cortical level thus appear to go hand in hand to ensure that the motor control system is optimally tuned for the particular motor task at hand (Perez et al. 2005; Meunier et al. 2007).

Implications of these findings in health and disease

This amazing ability of the brain to reorganize itself in response to new environmental challenges in the setting of training a new task or sport has elicited the interest of sport scientists as well as clinicians. The question that has emerged is that perhaps this ability could operate in the process of rehabilitation following injuries like bone fractures, amputations or after brain lesions like stroke.

Cortical, and probably spinal plasticity as well, appear to play an important role in functional rehabilitation after brain lesions like stroke. For example, after a lesion in one side of the brain, a motor task that used to engage discreet areas of the motor system recruit a much larger network in order to perform the same or a diminished motion (Ward & Cohen, 2004; Butefisch et al. 2005; Ward et al. 2006). What has been an area of active investigation is determining what role each of these areas plays in generating these movements in the process of motor training. One reason this has elicited so much attention is because nowadays there are non-invasive tools that allow us to modulate excitability in different parts of the brain on purpose (Nudo et al. 1990). Recent animal studies have shown that direct epidural stimulation of the primary motor cortex surrounding a small infarct in the lesioned hemisphere elicits improvements in motor function (Brown et al. 2006). In humans, proof of principle studies from different laboratories have shown that non-invasive transcranial magnetic stimulation and direct current stimulation that increased excitability within the ipsi-lesional primary motor cortex (Gow et al. 2004; Khedr et al. 2005; Hummel et al. 2005; Hummel & Cohen, 2006; Talelli et al. 2007; Hesse et al. 2007) or decreased excitability in the contra-lesional primary motor cortex (Takeuchi et al. 2005; Fregni et al. 2005; Mansur et al. 2005; Boggio et al. 2006) results in improvement in motor function in patients with stroke. Possible mechanisms mediating these effects may include the correction of abnormally persistent interhemispheric inhibition when moving the paretic hand, a disorder correlated with the magnitude of impairment (Duque et al. 2005, 2007). Activation of sensory afferent inputs, especially in combination with stimulation of specific motor areas, also appears as an efficient means of promoting plastic changes at both cortical (Ridding & Rothwell, 1999; Khaslavskaia et al. 2002) and spinal level (Perez et al. 2003). Such interventions may with some likelihood be part of the treatment repertoire offered by future neurorehabilitation units for the benefit of disabled people and – who knows – may also be found in the gym of athletes training for the 2012 Olympics or alternatively on the list of illegitimate doping remedies. What is of main importance, and which is what we have tried to point out with this review, is that the development of non-invasive imaging and electrophysiological techniques have made objective measures available that allow us to directly monitor functionally relevant changes in neuronal circuitries in the brain and spinal cord induced by training or other interventions. This gives us the possibility of evaluating and guiding the interventions based on an unprecedented mechanistic understanding.

References

  1. Benecke R, Meyer BU, Freund HJ. Reorganisation of descending motor pathways in patients after hemispherectomy and severe hemispheric lesions demonstrated by magnetic brain stimulation. Exp Brain Res. 1991;83:419–426. doi: 10.1007/BF00231167. [DOI] [PubMed] [Google Scholar]
  2. Boggio PS, Alonso-Alonso M, Mansur CG, Rigonatti SP, Schlaug G, Pascual-Leone A, Fregni F. Hand function improvement with low-frequency repetitive transcranial magnetic stimulation of the unaffected hemisphere in a severe case of stroke. Am J Phys Med Rehabil. 2006;85:927–930. doi: 10.1097/01.phm.0000242635.88129.38. [DOI] [PubMed] [Google Scholar]
  3. Brown JA, Lutsep HL, Weinand M, Cramer SC. Motor cortex stimulation for the enhancement of recovery from stroke: a prospective, multicenter safety study. Neurosurgery. 2006;58:464–473. doi: 10.1227/01.NEU.0000197100.63931.04. [DOI] [PubMed] [Google Scholar]
  4. Butefisch CM, Davis BC, Sawaki L, Waldvogel D, Classen J, Kopylev L, Cohen LG. Modulation of use-dependent plasticity by d-amphetamine. Ann Neurol. 2002;51:59–68. doi: 10.1002/ana.10056. [DOI] [PubMed] [Google Scholar]
  5. Butefisch CM, Davis BC, Wise SP, Sawaki L, Kopylev L, Classen J, Cohen LG. Mechanisms of use-dependent plasticity in the human motor cortex. Proc Natl Acad Sci U S A. 2000;97:3661–3665. doi: 10.1073/pnas.050350297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Butefisch CM, Kleiser R, Korber B, Muller K, Wittsack HJ, Homberg V, Seitz RJ. Recruitment of contralesional motor cortex in stroke patients with recovery of hand function. Neurology. 2005;64:1067–1069. doi: 10.1212/01.WNL.0000154603.48446.36. [DOI] [PubMed] [Google Scholar]
  7. Carroll TJ, Riek S, Carson RG. The sites of neural adaptation induced by resistance training in humans. J Physiol. 2002;544:641–652. doi: 10.1113/jphysiol.2002.024463. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Celnik P, Stefan K, Hummel F, Duque J, Classen J, Cohen LG. Encoding a motor memory in the older adult by action observation. Neuroimage. 2006;29:677–684. doi: 10.1016/j.neuroimage.2005.07.039. [DOI] [PubMed] [Google Scholar]
  9. Classen J, Liepert J, Wise SP, Hallett M, Cohen LG. Rapid plasticity of human cortical movement representation induced by practice. J Neurophysiol. 1998;79:1117–1123. doi: 10.1152/jn.1998.79.2.1117. [DOI] [PubMed] [Google Scholar]
  10. Cohen LG, Roth BJ, Wassermann EM, Topka H, Fuhr P, Schultz J, Hallett M. Magnetic stimulation of the human cerebral cortex, an indicator of reorganization in motor pathways in certain pathological conditions. J Clin Neurophysiol. 1991;8:56–65. doi: 10.1097/00004691-199101000-00007. [DOI] [PubMed] [Google Scholar]
  11. Duque J, Mazzocchio R, Dambrosia J, Murase N, Olivier E, Cohen LG. Kinematically specific interhemispheric inhibition operating in the process of generation of a voluntary movement. Cereb Cortex. 2005;15:588–593. doi: 10.1093/cercor/bhh160. [DOI] [PubMed] [Google Scholar]
  12. Duque J, Murase N, Celnik P, Hummel F, Harris-Love M, Mazzocchio R, Olivier E, Cohen LG. Intermanual differences in movement-related interhemispheric inhibition. J Cogn Neurosci. 2007;19:204–213. doi: 10.1162/jocn.2007.19.2.204. [DOI] [PubMed] [Google Scholar]
  13. Elbert T, Pantev C, Wienbruch C, Rockstroh B, Taub E. Increased cortical representation of the fingers of the left hand in string players. Science. 1995;270:305–307. doi: 10.1126/science.270.5234.305. [DOI] [PubMed] [Google Scholar]
  14. Floel A, Breitenstein C, Hummel F, Celnik P, Gingert C, Sawaki L, Knecht S, Cohen LG. Dopaminergic influences on formation of a motor memory. Ann Neurol. 2005a;58:121–130. doi: 10.1002/ana.20536. [DOI] [PubMed] [Google Scholar]
  15. Floel A, Hummel F, Breitenstein C, Knecht S, Cohen LG. Dopaminergic effects on encoding of a motor memory in chronic stroke. Neurology. 2005b;65:472–474. doi: 10.1212/01.wnl.0000172340.56307.5e. [DOI] [PubMed] [Google Scholar]
  16. Fregni F, Boggio PS, Mansur CG, Knecht S, Cohen LG. Transcranial direct current stimulation of the unaffected hemisphere in stroke patients. Neuroreport. 2005;16:1551–1555. doi: 10.1097/01.wnr.0000177010.44602.5e. [DOI] [PubMed] [Google Scholar]
  17. Fridman EA, Hanakawa T, Chung M, Hummel F, Leiguarda RC, Cohen LG. Reorganization of the human ipsilesional premotor cortex after stroke. Brain. 2004;127:747–758. doi: 10.1093/brain/awh082. [DOI] [PubMed] [Google Scholar]
  18. Gaser C, Schlaug G. Brain structures differ between musicians and non-musicians. J Neurosci. 2003;23:9240–9245. doi: 10.1523/JNEUROSCI.23-27-09240.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Gow D, Rothwell J, Hobson A, Thompson D, Hamdy S. Induction of long-term plasticity in human swallowing motor cortex following repetitive cortical stimulation. Clin Neurophysiol. 2004;115:1044–1051. doi: 10.1016/j.clinph.2003.12.001. [DOI] [PubMed] [Google Scholar]
  20. Hesse S, Werner C, Schonhardt EM, Bardeleben A, Jenrich W, Kirker SG. Combined transcranial direct current stimulation and robot-assisted arm training in subacute stroke patients: a pilot study. Restor Neurol Neurosci. 2007;25:9–15. [PubMed] [Google Scholar]
  21. Hummel F, Celnik P, Giraux P, Floel A, Wu WH, Gerloff C, Cohen LG. Effects of non-invasive cortical stimulation on skilled motor function in chronic stroke. Brain. 2005;128:490–499. doi: 10.1093/brain/awh369. [DOI] [PubMed] [Google Scholar]
  22. Hummel FC, Cohen LG. Non-invasive brain stimulation: a new strategy to improve neurorehabilitation after stroke? Lancet Neurol. 2006;5:708–712. doi: 10.1016/S1474-4422(06)70525-7. [DOI] [PubMed] [Google Scholar]
  23. Jensen JL, Marstrand PC, Nielsen JB. Motor skill training and strength training are associated with different plastic changes in the central nervous system. J Appl Physiol. 2005;99:1558–1568. doi: 10.1152/japplphysiol.01408.2004. [DOI] [PubMed] [Google Scholar]
  24. Johansen-Berg H, Rushworth MF, Bogdanovic MD, Kischka U, Wimalaratna S, Matthews PM. The role of ipsilateral premotor cortex in hand movement after stroke. Proc Natl Acad Sci U S A. 2002;99:14518–14523. doi: 10.1073/pnas.222536799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Karl A, Birbaumer N, Lutzenberger W, Cohen LG, Flor H. Reorganization of motor and somatosensory cortex in upper extremity amputees with phantom limb pain. J Neurosci. 2001;21:3609–3618. doi: 10.1523/JNEUROSCI.21-10-03609.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Karni A, Meyer G, Jezzard P, Adams MM, Turner R, Ungerleider LG. Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature. 1995;377:155–158. doi: 10.1038/377155a0. [DOI] [PubMed] [Google Scholar]
  27. Khaslavskaia S, Ladouceur M, Sinkjaer T. Increase in tibialis anterior motor cortex excitability following repetitive electrical stimulation of the common peroneal nerve. Exp Brain Res. 2002;145:309–315. doi: 10.1007/s00221-002-1094-9. [DOI] [PubMed] [Google Scholar]
  28. Khedr EM, Ahmed MA, Fathy N, Rothwell JC. Therapeutic trial of repetitive transcranial magnetic stimulation after acute ischemic stroke. Neurology. 2005;65:466–468. doi: 10.1212/01.wnl.0000173067.84247.36. [DOI] [PubMed] [Google Scholar]
  29. Latash ML, Yarrow K, Rothwell JC. Changes in finger coordination and responses to single pulse TMS of motor cortex during practice of a multifinger force production task. Exp Brain Res. 2003;151:60–71. doi: 10.1007/s00221-003-1480-y. [DOI] [PubMed] [Google Scholar]
  30. Mansur CG, Fregni F, Boggio PS, Riberto M, Gallucci-Neto J, Santos CM, Wagner T, Rigonatti SP, Marcolin MA, Pascual-Leone A. A sham stimulation-controlled trial of rTMS of the unaffected hemisphere in stroke patients. Neurology. 2005;64:1802–1804. doi: 10.1212/01.WNL.0000161839.38079.92. [DOI] [PubMed] [Google Scholar]
  31. Meunier S, Kwon J, Russmann H, Ravindran S, Mazzocchio R, Cohen L. Spinal use-dependent plasticity of synaptic transmission in humans after a single cycling session. J Physiol. 2007;579:375–388. doi: 10.1113/jphysiol.2006.122911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Müllbacher W, Ziemann U, Wissel J, Dang N, Kofler M, Facchini S, Boroojerdi B, Poewe W, Hallett M. Early consolidation in human primary motor cortex. Nature. 2002;415:640–644. doi: 10.1038/nature712. [DOI] [PubMed] [Google Scholar]
  33. Murase N, Duque J, Mazzocchio R, Cohen LG. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol. 2004;55:400–409. doi: 10.1002/ana.10848. [DOI] [PubMed] [Google Scholar]
  34. Nielsen J, Crone C, Hultborn H. H-reflexes are smaller in dancers from The Royal Danish Ballet than in well-trained athletes. Eur J Appl Physiol Occup Physiol. 1993a;66:116–121. doi: 10.1007/BF01427051. [DOI] [PubMed] [Google Scholar]
  35. Pascual-Leone A, Cammarota A, Wassermann EM, Brasil-Neto JP, Cohen LG, Hallett M. Modulation of motor cortical outputs to the reading hand of braille readers. Ann Neurol. 1993;34:33–37. doi: 10.1002/ana.410340108. [DOI] [PubMed] [Google Scholar]
  36. Pascual-Leone A, Nguyet D, Cohen LG, Brasil-Neto JP, Cammarota A, Hallett M. Modulation of muscle responses evoked by transcranial magnetic stimulation during the acquisition of new fine motor skills. J Neurophysiol. 1995a;74:1037–1045. doi: 10.1152/jn.1995.74.3.1037. [DOI] [PubMed] [Google Scholar]
  37. Pascual-Leone A, Tarazona F, Catala MD. Applications of transcranial magnetic stimulation in studies on motor learning. Electroencephalogr Clin Neurophysiol Suppl. 1999;51:157–161. [PubMed] [Google Scholar]
  38. Pascual-Leone A, Wassermann EM, Sadato N, Hallett M. The role of reading activity on the modulation of motor cortical outputs to the reading hand in Braille readers. Ann Neurol. 1995b;38:910–915. doi: 10.1002/ana.410380611. [DOI] [PubMed] [Google Scholar]
  39. Pearce AJ, Thickbroom GW, Byrnes ML, Mastaglia FL. Functional reorganisation of the corticomotor projection to the hand in skilled racquet players. Exp Brain Res. 2000;130:238–243. doi: 10.1007/s002219900236. [DOI] [PubMed] [Google Scholar]
  40. Perez MA, Field-Fote EC, Floeter MK. Patterned sensory stimulation induces plasticity in reciprocal Ia inhibition in humans. J Neurosci. 2003;23:2014–2018. doi: 10.1523/JNEUROSCI.23-06-02014.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Perez MA, Lungholt BK, Nielsen JB. Presynaptic control of group Ia afferents in relation to acquisition of a visuo-motor skill in healthy humans. J Physiol. 2005;568:343–354. doi: 10.1113/jphysiol.2005.089904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Perez MA, Lungholt BK, Nyborg K, Nielsen JB. Motor skill training induces changes in the excitability of the leg cortical area in healthy humans. Exp Brain Res. 2004;159:197–205. doi: 10.1007/s00221-004-1947-5. [DOI] [PubMed] [Google Scholar]
  43. Perez MA, Wise SP, Willingham DT, Cohen LG. Neurophysiological mechanisms involved in transfer of procedural knowledge. J Neurosci. 2007;27:1045–1053. doi: 10.1523/JNEUROSCI.4128-06.2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Ridding MC, Rothwell JC. Reorganization in human motor cortex. Can J Physiol Pharmacol. 1995;73:218–222. doi: 10.1139/y95-032. [DOI] [PubMed] [Google Scholar]
  45. Ridding MC, Rothwell JC. Afferent input and cortical organisation: a study with magnetic stimulation. Exp Brain Res. 1999;126:536–544. doi: 10.1007/s002210050762. [DOI] [PubMed] [Google Scholar]
  46. Rosenkranz K, Williamon A, Rothwell JC. Motorcortical excitability and synaptic plasticity is enhanced in professional musicians. J Neurosci. 2007;27:5200–5206. doi: 10.1523/JNEUROSCI.0836-07.2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Sanes JN, Donoghue JP. Plasticity and primary motor cortex. Annu Rev Neurosci. 2000;23:393–415. doi: 10.1146/annurev.neuro.23.1.393. [DOI] [PubMed] [Google Scholar]
  48. Stefan K, Cohen LG, Duque J, Mazzocchio R, Celnik P, Sawaki L, Ungerleider L, Classen J. Formation of a motor memory by action observation. J Neurosci. 2005;25:9339–9346. doi: 10.1523/JNEUROSCI.2282-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Takeuchi N, Chuma T, Matsuo Y, Watanabe I, Ikoma K. Repetitive transcranial magnetic stimulation of contralesional primary motor cortex improves hand function after stroke. Stroke. 2005;36:2681–2686. doi: 10.1161/01.STR.0000189658.51972.34. [DOI] [PubMed] [Google Scholar]
  50. Talelli P, Greenwood RJ, Rothwell JC. Exploring theta burst stimulation as an intervention to improve motor recovery in chronic stroke. Clin Neurophysiol. 2007;118:333–342. doi: 10.1016/j.clinph.2006.10.014. [DOI] [PubMed] [Google Scholar]
  51. Ward NS, Cohen LG. Mechanisms underlying recovery of motor function after stroke. Arch Neurol. 2004;61:1844–1848. doi: 10.1001/archneur.61.12.1844. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Ward NS, Newton JM, Swayne OB, Lee L, Thompson AJ, Greenwood RJ, Rothwell JC, Frackowiak RS. Motor system activation after subcortical stroke depends on corticospinal system integrity. Brain. 2006;129:809–819. doi: 10.1093/brain/awl002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Wolpaw JR. Acquisition and maintenance of the simplest motor skill: investigation of CNS mechanisms. Med Sci Sports Exerc. 1994;26:1475–1479. [PubMed] [Google Scholar]
  54. Yousry TA, Schmid UD, Alkadhi H, Schmidt D, Peraud A, Buettner A, Winkler P. Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain. 1997;120:141–157. doi: 10.1093/brain/120.1.141. [DOI] [PubMed] [Google Scholar]
  55. Ziemann U, Hallett M, Cohen LG. Mechanisms of deafferentation-induced short-term plasticity in human motor cortex. J Neurosci. 1998;18:7000–7007. doi: 10.1523/JNEUROSCI.18-17-07000.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Ziemann U, Wittenberg GF, Cohen LG. Stimulation-induced within-representation and across-representation plasticity in human motor cortex. J Neurosci. 2002;22:5563–5571. doi: 10.1523/JNEUROSCI.22-13-05563.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Nielsen JB. Sensorimotor integration at spinal level as a basis for muscle coordination during voluntary movement in humans. J Appl Physiol. 2004;96:1961–1967. doi: 10.1152/japplphysiol.01073.2003. [DOI] [PubMed] [Google Scholar]
  58. Nielsen J, Kagamihara Y. The regulation of presynaptic inhibition during co-contraction of antagonistic muscles in man. J Physiol. 1993b;464:575–593. doi: 10.1113/jphysiol.1993.sp019652. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Nudo R, Jenkin W, Merzernich M. Repetitive microstimulation alters the cortical representation of movements in adult rats. Somatosensory Motor Res. 1990;7:463–483. doi: 10.3109/08990229009144720. [DOI] [PubMed] [Google Scholar]

Articles from The Journal of Physiology are provided here courtesy of The Physiological Society

RESOURCES