Hostname: page-component-8448b6f56d-gtxcr Total loading time: 0 Render date: 2024-04-23T10:22:03.871Z Has data issue: false hasContentIssue false
  • English
  • Français

The Neuropsychology of Movement and Movement Disorders: Neuroanatomical and Cognitive Considerations

Published online by Cambridge University Press:  04 December 2017

Kathleen Y. Haaland ,
Richard P. Dum ,
Pratik K. Mutha ,
Peter L. Strick  and
Alexander I. Tröster
Kathleen Y. Haaland*
Affiliation:
Departments of Psychiatry & Behavioral Sciences and Neurology, University of New Mexico, Albuquerque, New Mexico
Richard P. Dum
Affiliation:
University of Pittsburgh Brain Institute, Systems Neuroscience Institute, Center for the Neural Basis of Cognition, and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
Pratik K. Mutha
Affiliation:
Department of Biological Engineering and Center for Cognitive Science, Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, Gujarat, India
Peter L. Strick
Affiliation:
University of Pittsburgh Brain Institute, Systems Neuroscience Institute, Center for the Neural Basis of Cognition, and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
Alexander I. Tröster
Affiliation:
Department of Clinical Neuropsychology and Center for Neuromodulation, Barrow Neurological Institute, Phoenix, Arizona
*
Correspondence and reprint requests to: Kathleen Y. Haaland, Department of Psychiatry & Behavioral Sciences MSC09 5030, 1 University of New Mexico, Albuquerque, NM 87131-0001. E-mail: khaaland@unm.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper highlights major developments over the past two to three decades in the neuropsychology of movement and its disorders. We focus on studies in healthy individuals and patients, which have identified cognitive contributions to movement control and animal work that has delineated the neural circuitry that makes these interactions possible. We cover advances in three major areas: (1) the neuroanatomical aspects of the “motor” system with an emphasis on multiple parallel circuits that include cortical, corticostriate, and corticocerebellar connections; (2) behavioral paradigms that have enabled an appreciation of the cognitive influences on the preparation and execution of movement; and (3) hemispheric differences (exemplified by limb praxis, motor sequencing, and motor learning). Finally, we discuss the clinical implications of this work, and make suggestions for future research in this area. (JINS, 2017, 23, 768–777)

Keywords

Motor cortexPremotor cortexParietal lobeBasal gangliaCerebellumIdeomotor limb apraxiaLearningParkinson’s diseaseHuntington’s disease
Type
Section 1 – Brain Systems and Assessment
Information
Journal of the International Neuropsychological Society , Volume 23 , Special Issue 9-10: Special Issue: Commemoration of the 50th Anniversary of the International Neuropsychological Society , October 2017 , pp. 768 - 777
Copyright
Copyright © The International Neuropsychological Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aflalo, T., Kellis, S., Klaes, C., Lee, B., Shi, Y., Pejsa, K., & Andersen, R.A. (2015). Decoding motor imagery from the posterior parietal cortex of a tetraplegic human. Science, 348, 906–910.CrossRefGoogle ScholarPubMed
Amiez, C., & Petrides, M. (2014). Neuroimaging evidence of the anatomo-functional organization of the human cingulate motor areas. Cerebral Cortex, 24(3), 563–578.Google Scholar
Ashby, F.G., Alfonso-Reese, L.A., Turken, A.U., & Waldron, E.M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105(3), 442–481.Google Scholar
Bi, Y., Han, Z., Zhong, S., Ma, Y., Gong, G., Huang, R., & Caramazza, A. (2015). The white matter structural network underlying human tool use and tool understanding. Journal of Neuroscience, 35(17), 6822–6835. doi: 10.1523/JNEUROSCI.3709-14.2015 CrossRefGoogle ScholarPubMed
Boecker, H., Jankowski, J., Ditter, P., & Scheef, L. (2008). A role of the basal ganglia and midbrain nuclei for initiation of motor sequences, NeuroImage, 39, 1356–1369. doi: 10.1016/j.neuroimage.2007.09.069 Google Scholar
Borchert, R.J., Rittman, T., Passamonti, L., Ye, Z., Sarni, S., Jones, S.P., & Rowe, J.B. (2016). Atomoxetine enhances connectivity of prefrontal networks in Parkinson’s Disease. Neuropsychopharmacology, 41, 2171–2177.Google Scholar
Buccino, G., Vogt, S., Ritzl, A., Fink, G.R., Zilles, K., Freund, H.J., & Rizzolatti, G. (2004). Neural circuits underlying imitation learning of hand actions: An event-related fMRI study. Neuron, 42(2), 323–334.Google Scholar
Buneo, C.A., & Andersen, R.A. (2006). The posterior parietal cortex: Sensorimotor interface for the planning and online control of visually guided movements. Neuropsychologia, 44, 2594–2606.Google Scholar
Buxbaum, L.J., Haaland, K.Y., Hallett, M., Wheaton, L., Heilman, K.M., Rodriguez, A., & Gonzalez Rothi, L.J. (2008). Treatment of limb apraxia: Moving forward to improved action. American Journal of Physical Medicine & Rehabilitation, 87, 149–161. doi: 10.1097/PHM.0b013e31815e6727 CrossRefGoogle ScholarPubMed
Buxbaum, L.J., Johnson-Frey, S.H., & Bartlett-Willians, M. (2005). Deficient internal models for planning hand-object interactions in apraxia. Neuropsychologia, 43(6), 917–929. doi: 10.1016/j.neuropsychologia.2004.09.006 Google Scholar
Buxbaum, L.J., & Solenine, L. (2010). Action knowledge, visuomotor activation, and embodiment n the two action systems. Annals of the New York Academy of Sciences, 1191, 201–218. doi: 10.1111/j.1749-6632.2010.05447.x CrossRefGoogle ScholarPubMed
Canessa, N., Borgo, F., Cappa, S.F., Perani, D., Falini, A., Buccino, G., & Shallice, T. The different neural correlates of action and functional knowledge in semantic memory: An fMRI study. 2008). Cerebral Cortex, 18, 740–751. doi: 10.1093/cercor/bhm110 Google Scholar
Caspers, S., Zilles, K., Laird, A.R., & Eickhoff, S.B. (2009). ALE meta-analysis of action observation and imitation in the human brain. Neuroimage, 50(3), 1148–1167.Google Scholar
Celnik, P. (2015). Understanding and modulating motor learning with cerebellar stimulation. Cerebellum, 14(2), 171–174.CrossRefGoogle ScholarPubMed
Della-Maggiore, V., Malfait, N., Ostry, D.J., & Paus, T. (2004). Stimulation of the Posterior Parietal Cortex Interferes with Arm Trajectory Adjustments during the Learning of New Dynamics. The Journal of Neuroscience, 24(44), 9971–9976. doi: 10.1523/JNEUROSCI.2833-04.2004 Google Scholar
Delong, M.R., & Wichmann, T. Basal Ganglia Circuits as Targets for Neuromodulation in Parkinson Disease. (2015). JAMA Neurology, 72(11), 1354–1360. doi: 10.1001/jamaneurol.2015.2397 Google Scholar
DiRienzo, F., Debarnot, U., Daligault, S., Saruco, E., Delpuech, C., Doyon, J., & Guillot, A. (2016). Online and offline performance gains following motor imagery practice: A comprehensive review of behavioral and neuroimaging studies. Frontiers in Human Neuroscience, 10, 1–15. doi: 10.3389/fnhum.2016.00315 Google Scholar
Doyon, J. (2008). Motor sequence learning and movement disorders. Current Opinion in Neurology, 21, 478–483.Google Scholar
Doyon, J., & Benali, H. (2005). Reorganization and plasticity in the adult brain during learning of motor skills. Current Opinion in Neurobiology, 15, 161–167.Google Scholar
Dum, R.P., & Strick, P.L. (1991). The origin of corticospinal projections from the premotor areas in the frontal lobe. Journal of Neuroscience, 11, 667–689.CrossRefGoogle ScholarPubMed
Dum, R.P., & Strick, P.L. (2005). Motor areas in the frontal lobe: The anatomical substrate for the central control of movement. In A. Riehle & E. Vaadia (Eds.), Motor cortex in voluntary movements (pp. 3–47). Boca Raton, FL: CRC Press LLC.Google Scholar
Dum, R.P., Leventhal, D.J., & Strick, P.L. (2016). Motor, cognitive, and affective areas of the cerebral cortex influence the adrenal medulla. Proceedings of the National Academy of Sciences of the United States of America, 113, 9922–9927.Google Scholar
Elsinger, C.L., Harrington, D.L., & Rao, S.M. (2006). Reappraisal of neural circuitry mediating internally generated and externally guided actions. NeuroImage, 31, 1177–1187.Google Scholar
Foerde, K., & Shohamy, D. (2011). The role of the basal ganglia in learning and memory: Insight from Parkinson’s disease. Neurobiology of Learning and Memory, 96(4), 624–636. doi: 10.1016/j.nlm.2011.08.006 Google Scholar
Frank, M.J., Seeberger, L.C., & O’Reilly, R.C. (2004). By carrot or by stick: Cognitive reinforcement learning in parkinsonism. Science, 306, 1940–1943. doi: 10.1126/science.1102941 Google Scholar
Fridman, E.A., Immisch, I., Hanakawa, T., Bohlhalter, S., Waldvogel, D., Kasaku, K., & Hallett, M. (2006). The role of the dorsal stream for gesture production. NeuroImage, 29, 417–428.Google Scholar
Genon, S., Li, H., Fan, L., Müller, V.I., Cieslik, E.C., Hoffstaedter, F., & Eickhoff, S.B. (2017). The right dorsal premotor mosaic: Organization, functions, and connectivity. Cerebral Cortex, 27, 2095–2110.Google ScholarPubMed
Glover, S., Wall, M.B., & Smith, A.T. (2012). Distinct cortical networks support the planning and online control of reaching-to-grasp in humans. European Journal of Neuroscience, 35, 909–915.Google Scholar
Goldenberg, G. (2009). Apraxia and the parietal lobes. Neuropsychologia, 47(6), 1449–1459.Google Scholar
Griffin, D.M., Hoffman, D.S., & Strick, P.L. (2015). Corticomotoneuronal cells are “functionally tuned”. Science, 350(6261), 667–670.Google Scholar
Haaland, K.Y. (2006). Left hemisphere dominance for movement. The Clinical Neuropsychologist, 20, 609–622.Google Scholar
Haaland, K.Y., Elsinger, C., Mayer, A., Durgerian, S., & Rao, S. (2004). Motor sequence complexity and performing hand produce differential patterns of hemispheric lateralization. Journal of Cognitive Neuroscience, 16, 621–636.Google Scholar
Haaland, K.Y., Harrington, D.L., & Knight, R.T. (2000). Neural representations of skilled movement. Brain, 123, 2306–2313.Google Scholar
Haber, S.N. (2014). The place of dopamine in the cortico-basal ganglia circuit. Neuroscience, 282, 248–257.Google Scholar
Haith, A.M., Huberdeau, D.M., & Krakauer, J.W. (2015). The influence of movement preparation time on the expression of visuomotor learning and savings. The Journal of Neuroscience, 35(13), 5109–5117. doi: 10.1523/JNEUROSCI.3869-14.2015 Google Scholar
Hamilton, J.M., Haaland, K.Y., Adair, J.C., & Brandt, J. (2003). Ideomotor limb apraxia in Huntington’s Disease: Implications for corticostriate involvement. Neuropsychologia, 41, 1–8.Google Scholar
Harrington, D.L., & Haaland, K.Y. (1991b). Sequencing in Parkinson’s disease: Abnormalities in programming and controlling movement. Brain, 114, 99–115.Google Scholar
Harrington, D.L., & Haaland, K.Y. (1991a). Hemispheric specialization: Abnormalities of motor programming. Neuropsychologia, 29, 147–163.Google Scholar
Harrington, D.L., Rao, S.M., Haaland, K.Y., Bobholz, J.A., Mayer, A.R., Binder, J.R., & Cox, R.W. (2000). Specialized neural systems underlying representations of motor sequencing. Journal of Cognitive Neuroscience, 12, 56–77.Google Scholar
Harrington, D.L., & Haaland, K.Y. (1992). Motor sequencing deficits with left hemisphere damage: Are some cognitive deficits specific to limb apraxia? Brain, 115, 857–874.CrossRefGoogle ScholarPubMed
Haslinger, B., Erhard, P., Weilke, F., Ceballos-Baumann, A.O., Bartenstein, P., Gräfin von Einsiedel, H., & Boecker, H. (2002). The role of lateral premotor–cerebellar–parietal circuits in motor sequence control: A parametric fMRI study. Cognitive Brain Research, 13, 159–168.CrossRefGoogle ScholarPubMed
Hauert, C.A. (1986). The relationship between motor function and cognition in the developmental perspective. Italian Journal of Neurological Sciences, 5, 101–107.Google Scholar
Heilman, K.M., Rothi, L.J., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 342–346.Google Scholar
Hetu, S., Gregoire, M., Saimpont, A., Coll, M.-P., Eugene, F., Michon, P.-E., & Jackson, P.L. (2013). The neural network of motor imagery: An ALE meta-analysis. Neuroscience and Biobehavioral Reviews, 37, 930–949. http://dx.doi.org/10.1016/j.neubiorev.2013.03.017 Google Scholar
Hickok, G. (2009). Eight problems for the mirror neuron theory of action understanding in monkeys and humans. Journal of Cognitive Neuroscience, 21, 1229–1243.Google Scholar
Holl, A.K., Wilkinson, L., Tabrizi, S.J., Painold, A., & Jahanshahi, M. (2012). Probabilistic classification learning with corrective feedback is selectively impaired in early Huntington’s disease--evidence for the role of the striatum in learning with feedback. Neuropsychologia, 50(9), 2176–2186. doi: 10.1016/j.neuropsychologia.2012.05.021 Google Scholar
Hosp, J.A., Pekanovic, A., Rioult-Pedotti, M.S., & Luft, A.R. (2011). Dopaminergic projections from midbrain to primary motor cortex mediate motor skill learning. Journal of Neuroscience, 31(7), 2481–2487.CrossRefGoogle ScholarPubMed
Huang, V.S., Haith, A., Mazzoni, P, Krakauer, J.W. (2011). Motor Learning and Savings in Adaptation Paradigms: Model-Free Memory for Successful Actions Combines with Internal Models. Neuron, 70, 787–801.Google Scholar
Kalenine, S., Buxbaum, L.P., & Coslett, H.B. (2010). Critical brain regions for action recognition: Lesion symptom mapping in left hemisphere stroke. Brain, 133, 3269–3280. doi: 10.1093/brain/awq210 Google Scholar
Kelly, R.M., & Strick, P.L. (2004). Macro-architecture of basal ganglia loops with the cerebral cortex: Use of rabies virus to reveal multisynaptic circuits. Progress in Brain Research, 143, 449–459.Google ScholarPubMed
Kimura, D., & Archibald, Y. (1974). Motor functions of the left hemisphere. Brain, 97, 337–350.Google Scholar
Kincses, Z.T., Johansen-Berg, H., Tomassini, V., Bosnell, R., Matthews, P.M., & Beckmann, C.F. (2008). Model-free characterization of brain functional networks for motor sequence learning using fMRI. NeuroImage, 39, 1950–1958.Google Scholar
Knowlton, B.J., Mangels, J.A., & Squire, L.R. (1996). A neostriatal habit learning system in humans. Science, 273(5280), 1399–1402.Google Scholar
Kolb, B., & Milner, B. (1981). Performance of complex arm and facial movements after focal brain lesions. Neuropsychologia, 19, 491–503.Google Scholar
Kraeutner, S.N., Keeler, L.T., & Boe, S.G. (2015). Motor imagery-based skill acquisition disrupted following rTMS of the inferior parietal lobule. Experimental Brain Research, 234, 397–407. doi: 10.1007/s00221-015-4472-9 Google Scholar
Krakauer, J.W., Ghazanfar, A.A., Gomez-Marin, A., Maciver, M.A., & Poeppe, D. (2017). Neuroscience needs behavior: Correcting a reductionist bias. Neuron, 93, 480–488.Google Scholar
Lefebvre, S., Dricot, L., Laloux, P., Gradkowski, W., Desfontaines, P., Evrard, F., & Vandermeeren, Y. (2015). Neural substrates underlying motor skill learning in chronic hemiparetic stroke patients. Frontiers in Human Neuroscience, 9, 1–18. doi: 10.3389/fnhum.2015.00320 Google Scholar
Lefebvre, S., Dricot, L., Laloux, P., Desfountaines, P., Evrard, F., Peeters, A., & Vandermeeren, Y. (2017). Increased functional connectivity one week after motor learning and tDCS in stroke patients. Neuroscience, 340, 424–435.Google Scholar
Leiguarda, R. (2001). Limb apraxia: Cortical or subcortical. NeuroImage, 14, S137–S141.Google Scholar
Lemon, R.N. (2008). Descending pathways in motor control. Annual Review of Neuroscience, 31, 195–218.Google Scholar
Lerner, T.N., Shilyansky, C., Davidson, T.J., Evans, K.E., Beier, K.T., Zalocusky, K.A., & Deisseroth, K. (2015). Intact-brain analyses reveal distinct information carried by SNc dopamine subcircuits. Cell, 162(3), 635–647.CrossRefGoogle ScholarPubMed
Luria, A.R. (1973). The working brain: An introduction to neuropsychology. New York: Basic Books.Google Scholar
MacDonald, A.A., Seergobin, K.N., Owen, A.M., Tamjeedi, R., Monchi, O., Ganjavi, H., & MacDonald, P.A. (2013). Differential effects of Parkinson’s disease and dopamine replacement on memory encoding and retrieval. PLoS One, 8(9), e74044. doi: 10.1371/journal.pone.0074044 Google Scholar
MacDonald, P.A., MacDonald, A.A., Seergobin, K.N., Tamjeedi, R., Ganjavi, H., Provost, J.S., & Monchi, O. (2011). The effect of dopamine therapy on ventral and dorsal striatum-mediated cognition in Parkinson’s disease: Support from functional MRI. Brain, 134(Pt 5), 1447–1463. doi: 10.1093/brain/awr075 Google Scholar
Martin, T.A., Keating, J.G., Goodkin, H.P., Bastian, A.J., & Thach, W.T. (1996). Throwing while looking through prisms. I. Focal olivocerebellar lesions impair adaptation. Brain, 119(Pt 4), 1183–1198.Google Scholar
Mathar, D., Wilkinson, L., Holl, A.K., Neumann, J., Deserno, L., Villringer, A., & Horstmann, A. (2017). The role of dopamine in positive and negative prediction error utilization during incidental learning - Insights from Positron Emission Tomography, Parkinson’s disease and Huntington’ disease. Cortex, 90, 149–162. doi: 10.1016/j.cortex.2016.09.004 Google Scholar
McInnes, K., Friesen, C., & Boe, S. (2015). Specific brain lesions impair explicit motor imagery agility: A systematic review of the evidence. Archives of Physical Medicine and Rehabilitation, 97, 478–489. http://dx.doi.org/10.1016/j.apmr.2015.07.012 Google Scholar
Merchant, H., Harrington, D.L., & Meck, W.H. (2013). Neural basis of the perception and estimation of time. Annual Review of Neuroscience, 36, 313–336. doi: 10.1146/annurev-neuro-062012-170349 Google Scholar
Middleton, F.A., & Strick, P.L. (2000). Basal ganglia and cerebellar loops: Motor and cognitive circuits. Brain Research. Brain Research Reviews, 31(2–3), 236–250.CrossRefGoogle ScholarPubMed
Michely, J., Volz, L.J., Barbe, M.T., Hoffstaedter, F., Viswanathan, S., Timmermann, L., & Grefkes, C. (2015). Dopaminergic modulation of motor network dynamics in Parkinson’s disease. Brain, 138, 664–678.Google Scholar
Muslimovic, D., Post, B., Speelman, J.D., & Schmand, B. (2007). Motor procedural learning in Parkinson’s disease. Brain, 130, 2887–2897. doi: 10.1093/brain/awm211 Google Scholar
Mutha, P.K., Sainburg, R.L., & Haaland, K.Y. (2010). Deficits in ideomotor apraxia reflect impaired visuomotor transformations. Neuropsychologia, 48, 3855–3867. doi: 10.1016/j.neuropsychologia.2010.09.018 Google Scholar
Mutha, P.K., Sainburg, P.I., & Haaland, K.Y. (2011). Left parietal regions are critical for adaptive visuomotor control. Journal of Neuroscience, 31(19), 6972–6981. doi: 10.1523/JNEUROSCI.6432-10.2011 Google Scholar
Mutha, P.K., Stapp, L.H., Sainburg, R.L., & Haaland, K.Y. (2014). Posterior parietal and prefrontal cortex contributions to action modification. Cortex, 57, 38–50. doi: doi.org/10.1016/j.cortex.2014.03.005 Google Scholar
Mutha, P.K., Stapp, L.H., Sainburg, R.L., & Haaland, K.Y. (2017). Motor adaptation deficits in ideomotor limb apraxia. Journal of the International Neuropsychological Society, 23, 139–149. doi: 10.1017/S135561771600120X Google Scholar
Nissen, M.J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive Psychology, 19, 1–32.Google Scholar
Orban de Xivry, J.J., Criscimagna-Hemminger, S.E., & Shadmehr, R. (2011). Contributions of the motor cortex to adaptive control of reaching depend on the perturbation schedule. Cerebral Cortex, 21(7), 1475–1484. doi: 10.1093/cercor/bhq192 Google Scholar
Osuriak, F., Jarry, C., & LeGall, D. (2011). Re-examining the gesture engram hypothesis. New perspectives on apraxia of tool use. Neuropsychologia, 49, 299–312.Google Scholar
Pammi, V.S.C., Miyapuram, K.P., Ahmed, S.K., Bapi, R.S., & Doya, K. (2012). Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network. NeuroImage, 59, 1180–1189.Google Scholar
Perry, A., Stiso, J., Channge, E.F., Lin, J.J., Parvizi, J., & Knight, R.T. (2017). Mirroring in the human brain: Deciphering the spatial-temporal patterns of the human mirror neuron system. Cerebral Cortex, doi: 10.1093/cercor/bhx013 Google Scholar
Picard, N., & Strick, P.L. (2001). Imaging the premotor areas. Current Opinion in Neurobiology, 11(6), 663–672.Google Scholar
Poldrack, R.A., Clark, J., Pare-Blagoev, E.J., Shohamy, D., Creso Moyano, J., Myers, C., &Gluck, M.A. (2001). Interactive memory systems in the human brain. Nature, 414, 546–550.Google Scholar
Rathelot, J.A., & Strick, P.L. (2006). Muscle representation in the macaque motor cortex: An anatomical perspective. Proceedings of the National Academy of Sciences of the United States of America, 103(21), 8257–8262.Google Scholar
Rathelot, J.A., & Strick, P.L. (2009). Subdivisions of primary motor cortex based on cortico-motoneuronal cells. Proceedings of the National Academy of Sciences of the United States of America, 106(3), 918–923.Google Scholar
Rizzolatti, G., & Fogassi, L. (2014). The mirror mechanism: Recent findings and perspectives. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 369, 20130420. http://dx.doi.org/10.1098/rstb.2013.0420 Google Scholar
Rowe, J.B., & Siebner, H.R. (2012). The motor system and its disorders. NeuroImage, 61, 464–477.Google Scholar
Schendan, H.E., Searl, M.M., Melrose, R.J., & Stern, C.E. (2003). An FMRI study of the role of the medial temporal lobe in implicit and explicit sequence learning. Neuron, 37, 1013–1025. doi: 10.1016/S0896-6273(03)00123-5 Google Scholar
Schluter, N.D., Rushworth, M.F.S., Passingham, R.E., & Mills, K.R. (1998). Temporary interference in human lateral premotor cortex suggests dominance for the selection of movements: A study using transcranial magnetic stimulation. Brain, 121, 785–799.Google Scholar
Serrien, D.J., Ivry, R.B., & Swinnen, S.P. (2006). Dynamics of hemispheric specialization and integration in the context of motor control. Nature Reviews Neuroscience, 7, 160–167.Google Scholar
Serrien, D.J., & Sovijarvi-Spape, M.M. (2016). Manual dexterity: Functional lateralization patterns and motor efficience. Brain and Cognition, 108, 42–46. doi: 10.1016/j.bandc.2016.07.005 Google Scholar
Shackman, A.J., Salomons, T.V., Slagter, H.A., Fox, A.S., Winter, J.J., & Davidson, R.J. (2011). The integration of negative affect, pain and cognitive control in the cingulate cortex. Nature Reviews. Neuroscience, 12(3), 154–167.Google Scholar
Shohamy, D., Myers, C.E., Onlaor, S., & Gluck, M.A. (2004). Role of the basal ganglia in category learning: How do patients with Parkinson’s disease learn? Behavioral Neuroscience, 118(4), 676–686. doi: 10.1037/0735-7044.118.4.676 Google Scholar
Siegert, R.J., Taylor, K.D., Weatherall, M., & Abernethy, D.A. (2006). Is Implicit Sequence Learning Impaired in Parkinson’s Disease? A meta-analysis. Neuropsychology, 20(4), 490–495. DOI: 10.1037/0894-4105.20.4.490 Google Scholar
Sirigu, A., Duhamel, J.-R., Cohen, L., Pillon, B., Duboisand, B., & Agid, Y. (1996). The mental representation of hand movements after parietal cortex damage. Science, 273(5281), 1564–1568.Google Scholar
Smith, J.G., & McDowall, J. (2006). When artificial grammar acquisition in Parkinson’s disease is impaired: The case of learning via trial-by-trial feedback. Brain Research, 1067(1), 216–228. doi: 10.1016/j.brainres.2005.10.025 Google Scholar
Smith, J., Siegert, R.J., McDowall, J., & Abernethy, D. (2001). Preserved implicit learning on both the serial reaction time task and artificial grammar in patients with Parkinson’s disease. Brain and Cognition, 45, 378–391. doi: 10.1006/brcg.2001.1286 Google Scholar
Smith, M.A., & Shadmehr, R. (2005). Intact ability to learn internal models of arm dynamics in Huntington’s disease but not cerebellar degeneration. Journal of Neurophysiology, 93(5), 2809–2821.Google Scholar
Strick, P.L., Dum, R., & Fiez, J.A. (2009). Cerebellum and non-motor function. In S.E. Hyman, T.M. Jessel, C.J. Shatz & C.F. Stevens (Eds.), Annual review of neuroscience, (Vol. 32., pp. 413–434). Palo Alto, CA: Annual Reviews.Google Scholar
Taylor, J.A., Krakauer, J.W., & Ivry, R.B. (2014). Explicit and implicit contributions to learning in a sensorimotor adaptation task. Journal of Neuroscience, 34(8), 3023–3032. doi: 10.1523/JNEUROSCI.3619-13 Google Scholar
Tseng, Y.W., Diedrichsen, J., Krakauer, J.W., Shadmehr, R., & Bastian, A.J. (2007). Sensory prediction errors drive cerebellum-dependent adaptation of reaching. Journal of Neurophysiology, 98(1), 54–62.Google Scholar
Verstynen, T., & Sabes, P.N. (2011). How each movement changes the next: An experimental and theoretical study of fast adaptive priors in reaching. Journal of Neuroscience, 31(27), 10050–10059. doi: 10.1523/JNEUROSCI.6525-10 Google Scholar
Vingerhoets, G. (2014). Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools. Frontiers in Psychology, 5, 1–17. doi: 10.3389/fpsyg.2014.00151 Google Scholar
Wilkinson, L., Khan, Z., & Jahanshahi, M. (2009). The role of the basal ganglia and its cortical connections in sequence learning: Evidence from implicit and explicit sequence learning in Parkinson’s disease. Neuropsychologia, 47(12), 2564–2573. doi: 10.1016/j.neuropsychologia.2009.05.003 Google Scholar
Willingham, D.B., & Koroshetz, W.J. (1993). Evidence for dissociable motor skills Huntington’s disease patients. Psychobiology, 21(3), 173–182.Google Scholar
Willingham, D.B., Salidis, J., & Gabrieli, J.D. (2002). Direct comparison of neural systems mediating conscious and unconscious skill learning. Learning and Memory, 1, 217–229.Google Scholar
Wolpert, D.M., Goodbody, S.J., & Husain, M. (1998). Maintaining internal representations: The role of the human superior parietal lobe. Nature Neuroscience, 1(6), 529–533.Google Scholar
Wu, T., Wang, L., Hallett, M., Chen, Y., Li, K., & Chan, P. (2011). Effective connectivity of brain networks during self-initiated movement in Parkinson’s disease. NeuroImage, 55, 204–215.Google Scholar