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Motor Adaptation Deficits in Ideomotor Apraxia

Published online by Cambridge University Press:  16 February 2017

Pratik K. Mutha ,
Lee H. Stapp ,
Robert L. Sainburg  and
Kathleen Y. Haaland
Pratik K. Mutha*
Affiliation:
Department of Biological Engineering and Center for Cognitive Science, Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, Gujarat, India
Lee H. Stapp
Affiliation:
New Mexico VA Healthcare System, Albuquerque, New Mexico
Robert L. Sainburg
Affiliation:
Department of Kinesiology, Pennsylvania State University, University Park, Pennsylvania Department of Neurology, Pennsylvania State University, Hershey, Pennsylvania
Kathleen Y. Haaland
Affiliation:
Departments of Psychiatry & Behavioral Sciences and Neurology, University of New Mexico, Albuquerque, New Mexico
*
Correspondence and reprint requests to: Pratik K. Mutha, Indian Institute of Technology Gandhinagar, Block 5, Room 316A, Palaj, Gandhinagar, Gujarat, India – 382355. E-mail: pm@iitgn.ac.in
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Abstract

Objectives: The cardinal motor deficits seen in ideomotor limb apraxia are thought to arise from damage to internal representations for actions developed through learning and experience. However, whether apraxic patients learn to develop new representations with training is not well understood. We studied the capacity of apraxic patients for motor adaptation, a process associated with the development of a new internal representation of the relationship between movements and their sensory effects. Methods: Thirteen healthy adults and 23 patients with left hemisphere stroke (12 apraxic, 11 nonapraxic) adapted to a 30-degree visuomotor rotation. Results: While healthy and nonapraxic participants successfully adapted, apraxics did not. Rather, they showed a rapid decrease in error early but no further improvement thereafter, suggesting a deficit in the slow, but not the fast component of a dual-process model of adaptation. The magnitude of this late learning deficit was predicted by the degree of apraxia, and was correlated with the volume of damage in parietal cortex. Apraxics also demonstrated an initial after-effect similar to the other groups likely reflecting the early learning, but this after-effect was not sustained and performance returned to baseline levels more rapidly, consistent with a disrupted slow learning process. Conclusions: These findings suggest that the early phase of learning may be intact in apraxia, but this leads to the development of a fragile representation that is rapidly forgotten. The association between this deficit and left parietal damage points to a key role for this region in learning to form stable internal representations. (JINS, 2017, 23, 139–149)

Keywords

ReachingMovementLearningInternal representationStrokeParietal cortex
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 23 , Special Issue 2: Special Issue: Motor Cognition , February 2017 , pp. 139 - 149
Copyright
Copyright © The International Neuropsychological Society 2017 

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References

Ashburner, J., & Friston, K.J. (2005). Unified segmentation. Neuroimage, 26(3), 839–851.CrossRefGoogle ScholarPubMed
Buxbaum, L.J. (2014). Moving the gesture engram into the 21st century. Cortex, 57, 286–289. discussion 306–308.CrossRefGoogle Scholar
Buxbaum, L.J., Haaland, K.Y., Hallett, M., Wheaton, L., Heilman, K.M., Rodriguez, A., & Rothi, L.J. (2008). Treatment of limb apraxia: Moving forward to improved action. American Journal of Physical Medicine & Rehabilitation, 87(2), 149–161.Google Scholar
Buxbaum, L.J., Johnson-Frey, S.H., & Bartlett-Williams, M. (2005). Deficient internal models for planning hand-object interactions in apraxia. Neuropsychologia, 43(6), 917–929.CrossRefGoogle ScholarPubMed
Buxbaum, L.J., & Kalenine, S. (2010). Action knowledge, visuomotor activation, and embodiment in the two action systems. Annals of the New York Academy of Sciences, 1191, 201–218.CrossRefGoogle ScholarPubMed
Buxbaum, L.J., Kyle, K., Grossman, M., & Coslett, B. (2007). Left inferior parietal representations for skilled hand-object interactions: Evidence from stroke and corticobasal degeneration. Cortex, 43(3), 411–423.CrossRefGoogle ScholarPubMed
Canessa, N., Borgo, F., Cappa, S.F., Perani, D., Falini, A., Buccino, G., & Shallice, T. (2008). The different neural correlates of action and functional knowledge in semantic memory: An fMRI Study. Cerebral Cortex, 18(4), 740–751.Google Scholar
Clark, M., Merians, A.S., Kothari, A., Poizner, H., Macauley, B., Rothi, L.,& Heilman, K. (1994). Spatial planning deficits in limb apraxia. Brain, 117, 1093–1106.Google Scholar
Criscimagna-Hemminger, S.E., Bastian, A.J., & Shadmehr, R. (2010). Size of error affects cerebellar contributions to motor learning. Journal of Neurophysiology, 103(4), 2275–2284.Google Scholar
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. Journal of Neuroscience, 24(44), 9971–9976.CrossRefGoogle ScholarPubMed
Dovern, A., Fink, G.R., Saliger, J., Karbe, H., Koch, I., & Weiss, P.H. (2011). Apraxia impairs intentional retrieval of incidentally acquired motor knowledge. Journal of Neuroscience, 31(22), 8102–8108.CrossRefGoogle ScholarPubMed
Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K., & Zilles, K. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage, 25(4), 1325–1335.CrossRefGoogle ScholarPubMed
Fugl-Meyer, A.R., Jaasko, L., Leyman, I., Olsson, S., & Steglind, S. (1975). The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scandinavian Journal of Rehabilitation Medicine, 7(1), 13–31.CrossRefGoogle ScholarPubMed
Galea, J.M., Vazquez, A., Pasricha, N., Orban de Xivry, J.J., & Celnik, P. (2011). Dissociating the roles of the cerebellum and motor cortex during adaptive learning: The motor cortex retains what the cerebellum learns. Cerebral Cortex, 21, 1761–1770.CrossRefGoogle ScholarPubMed
Goldenberg, G. (1999). Matching and imitation of hand and finger postures in patients with damage in the left or right hemispheres. Neuropsychologia, 37(5), 559–566.Google Scholar
Goldenberg, G. (2009). Apraxia and the parietal lobes. Neuropsychologia, 47(6), 1449–1459.Google Scholar
Goldenberg, G. (2013). Apraxia: The cognitive side of motor control. Oxford: Oxford University Press.Google Scholar
Goldenberg, G., Daumuller, M., & Hagmann, S. (2001). Assessment and therapy of complex activities of daily living in apraxia. Neuropsychological Rehabilitation, 11(2), 147–169.Google Scholar
Haaland, K.Y., & Flaherty, D. (1984). The different types of limb apraxia errors made by patients with left vs. right hemisphere damage. The Brain and Cognition, 3(4), 370–384.Google Scholar
Haaland, K.Y., Harrington, D.L., & Knight, R.T. (2000). Neural representations of skilled movement. Brain, 123(Pt 11), 2306–2313.CrossRefGoogle ScholarPubMed
Hadipour-Niktarash, A., Lee, C.K., Desmond, J.E., & Shadmehr, R. (2007). Impairment of Retention But Not Acquisition of a Visuomotor Skill Through Time-Dependent Disruption of Primary Motor Cortex. Journal of Neuroscience, 27(49), 13413–13419.Google Scholar
Hanna-Pladdy, B., Heilman, K.M., & Foundas, A.L. (2003). Ecological implications of ideomotor apraxia: Evidence from physical activities of daily living. Neurology, 60(3), 487–490.CrossRefGoogle ScholarPubMed
Harrington, D.L., & Haaland, K.Y. (1992). Motor sequencing with left hemisphere damage. Are some cognitive deficits specific to limb apraxia? Brain, 115(Pt 3), 857–874.CrossRefGoogle ScholarPubMed
Heilman, K.M., Rothi, L.J., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 342–346.CrossRefGoogle ScholarPubMed
Heilman, K.M., & Rothi, L.J.G. (1993). Apraxia. In K.M. Heilman & E. Valenstein (Eds.), Clinical neuropsychology (pp. 141–164). New York: Oxford University Press.CrossRefGoogle Scholar
Heilman, K.M., Schwartz, H.D., & Geschwind, N. (1975). Defective motor learning in ideomotor apraxia. Neurology, 25(11), 1018–1020.Google Scholar
Huang, V.S., Haith, A., Mazzoni, P., & Krakauer, J.W. (2011). Rethinking motor learning and savings in adaptation paradigms: Model-free memory for successful actions combines with internal models. Neuron, 70(4), 787–801.Google Scholar
Kertesz, A. (1982). Western aphasia battery. New York: The Psychological Corporation.Google Scholar
Krakauer, J.W., Mazzoni, P., Ghazizadeh, A., Ravindran, R. & Shadmehr, R. (2006). Generalization of motor learning depends on the history of prior action. PLoS Biology, 4(10): e316.Google Scholar
Kumar, N., & Mutha, P.K. (2016). Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli. Journal of Neurophysiology, 115, 1654–1663.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.CrossRefGoogle ScholarPubMed
Moll, J., Oliveira-Souza, R., Passman, L.J., Cimini Cunha, F., Souze-Lima, F., & Ardreiuolo, P.A. (2000). Functional MRI correlates of real and imagined tool-use pantomimes. Neurology, 54, 1331–1336.Google Scholar
Motomura, N., Seo, T., Asaba, H., & Sakai, T. (1989). Motor learning in ideomotor apraxia. The International Journal of Neuroscience, 47(1-2), 125–129.CrossRefGoogle ScholarPubMed
Mozaz, M., Rothi, L.J., Anderson, J.M., Crucian, G.P., & Heilman, K.M. (2002). Postural knowledge of transitive pantomimes and intransitive gestures. Journal of the International Neuropsychological Society, 8(7), 958–962.CrossRefGoogle ScholarPubMed
Muhlau, M., Hermsdorfer, J., Goldenberg, G., Wohlschlager, A.M., Castrop, F., Stahl, R., & Boecker, H. (2005). Left inferior parietal dominance in gesture imitation: An fMRI study. Neuropsychologia, 43(7), 1086–1098.Google Scholar
Mutha, P.K., Sainburg, R.L., & Haaland, K.Y. (2010). Coordination deficits in ideomotor apraxia during visually targeted reaching reflect impaired visuomotor transformations. Neuropsychologia, 48(13), 3855–3867.Google Scholar
Mutha, P.K., Sainburg, R.L., & Haaland, K.Y. (2011a). Critical neural substrates for correcting unexpected trajectory errors and learning from them. Brain, 134(Pt 12), 3647–3661.Google Scholar
Mutha, P.K., Sainburg, R.L., & Haaland, K.Y. (2011b). Left parietal regions are critical for adaptive visuomotor control. Journal of Neuroscience, 31(19), 6972–6981.Google Scholar
Oldfield, R.C. (1971). The assessment and analysis of handedness: The Edinburgh Inventory. Neuropsychologia, 9, 97–113.Google Scholar
Pazzaglia, M., Smania, N., Corato, E., & Aglioti, S.M. (2008). Neural underpinnings of gesture discrimination in patients with limb apraxia. Journal of Neuroscience, 28(12), 3030–3041.Google Scholar
Rorden, C., & Brett, M. (2000). Stereotaxic display of brain lesions. Behavioral Neurology, 12(4), 191–200.Google Scholar
Rothi, L.J.G., & Hielman, K.M. (1984). Acquisition and retention of gestures by apraxic patients. Brain and Cognition, 3, 426–437.Google Scholar
Rothi, L.J.G., Ochipa, C., & Heilman, K.M. (1991). A Cognitive Neuropsychological Model of Limb Praxis. Cognitive Neuropsychology, 8(6), 443–458.CrossRefGoogle Scholar
Schluter, N.D., Rushworth, M.F., 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(Pt 5), 785–799.Google Scholar
Serino, A., De Filippo, L., Casavecchia, C., Coccia, M., Shiffrar, M., & Ladavas, E. (2010). Lesions to the motor system affect action perception. Journal of Cognitive Neuroscience, 22(3), 413–426.Google Scholar
Shadmehr, R., & Mussa-Ivaldi, F.A. (1994). Adaptive representation of dynamics during learning of a motor task. Journal of Neuroscience, 14(5 Pt 2), 3208–3224.Google Scholar
Shadmehr, R., & Mussa-Ivaldi, F.A. (2012). Biological learning and control: How the brain builds representations, predicts events and makes decisions. Cambridge, MA: MIT Press.Google Scholar
Shadmehr, R., Smith, M.A., & Krakauer, J.W. (2010). Error correction, sensory prediction, and adaptation in motor control. Annual Review of Neuroscience, 33, 89–108.Google Scholar
Sirigu, A., Duhamel, J.R., & Poncet, M. (1991). The role of sensorimotor experience in object recognition. A case of multimodal agnosia. Brain, 114(Pt 6), 2555–2573.Google Scholar
Smith, M.A., Ghazizadeh, A., & Shadmehr, R. (2006). Interacting adaptive processes with different timescales underlie short-term motor learning. PLoS Biology, 4(6), e179.Google Scholar
Tarhan, L.Y., Watson, C.E., & Buxbaum, L.J. (2015). Shared and distinct neuroanatomic regions critical for tool-related action production and recognition: Evidence from 131 left-hemisphere stroke patients. Journal of Cognitive Neuroscience, 27(12), 2491–2511.Google Scholar
Thach, W.T., & Bastian, A.J. (2004). Role of the cerebellum in the control and adaptation of gait in health and disease. Progress in Brain Research, 143, 353–366.Google Scholar
Toraldo, A., Reverberi, C., & Rumiati, R.I. (2001). Critical dimensions affecting imitation performance of patients with ideomotor apraxia. Cortex, 37(5), 737–740.Google Scholar
Tranel, D., Manzel, K., Asp, E., & Kemmerer, D. (2008). Naming dynamic and static actions: Neuropsychological evidence. Journal of Physiology, Paris, 102(1-3), 80–94.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
Vingerhoets, G. (2014). Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools. Frontiers in Psychology, 5, 151.Google Scholar
Wolpert, D.M., & Ghahramani, Z. (2000). Computational principles of movement neuroscience. Nature Neuroscience, 3(Suppl), 1212–1217.Google Scholar
Wolpert, D.M., & Kowato, M. (1998). Multiple paired forward and inverse models for motor control. Neural Networks, 11(7-8), 1317–1329.CrossRefGoogle ScholarPubMed