Motor learning and memory in health and disease

Summary

Principal Investigator: Reza Shadmehr
Abstract: DESCRIPTION: Our long term goal is to construct a unifying framework that explains the roles of the basal ganglia and the cerebellum in control of saccades and reaching. We suggest that a fundamental assumption regarding control of movements, the idea that variability is mostly because of noise, is incorrect. We show that there is systematic variability in the motor commands that initiate a movement to a target, and propose that this variability is a reflection of a systematic reduction in the internal value that the brain associates with a repeating stimulus. We hypothesize that this internal value is computed in the striatum. If this variability was uncompensated, that is, if movements like saccades were "open loop", then the variability would affect saccade endpoints. In healthy people, however, saccade endpoints are immune to this variability. We suggest that this is because control of movements is strongly dependent on internal models through the cerebellum, monitoring the outgoing motor commands and effectively "steering" to compensate for variability in the outgoing motor command that would lead to unacceptable inaccuracy, i.e., dysmetria. The compensation is effective only if this internal model is calibrated, which links the problem of control with adaptation. We propose a single principle of control and adaptation for both the saccadic and reaching systems: each is supported by a fast adaptive system with poor retention, and a slow adaptive system with strong retention. Expected costs and rewards of a movement are evaluated by the basal ganglia, resulting in an internal value that affects the motor commands that initiate the movement. As the motor commands are generated, the cerebellum monitors them and predicts their sensory consequences, producing adjustments that "steer" the movement to the goal. We propose that adaptation is faster in the mechanism that steers the movement (cerebellum for both reaching and saccades) than the mechanism that initiates the movement (motor cortex for reaching, superior colliculus for saccades). PUBLIC HEALTH RELEVANCE Our hypothesis is a new, coherent theory of how various brain structures like the basal ganglia and the cerebellum contribute to control of voluntary movements like saccades and reaching. While cerebellar patients have been consistently impaired in motor learning, our hypothesis presents a potential solution to how rehabilitation may proceed in these patients to help their recovery. The role of basal ganglia in control of movements has remained a deep puzzle. Our hypothesized link between this structure and the internal value of action may help early diagnosis of diseases of the basal ganglia through experiments that quantify changes in trajectories of the eyes and the arm in response to changes in value of the stimulus that affords these movements.
Funding Period: ----------------1999 - ---------------2011-
more information: NIH RePORT

Top Publications

  1. pmc Consolidation of motor memory
    John W Krakauer
    The Neurological Institute, Columbia University College of Physicians and Surgeons, 710 West 168th Street, New York, NY 10032, USA
    Trends Neurosci 29:58-64. 2006
  2. pmc Preparing to reach: selecting an adaptive long-latency feedback controller
    Mohammad Ali Ahmadi-Pajouh
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, The Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 32:9537-45. 2012
  3. pmc Motor learning relies on integrated sensory inputs in ADHD, but over-selectively on proprioception in autism spectrum conditions
    Jun Izawa
    Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, USA
    Autism Res 5:124-36. 2012
  4. pmc A shared resource between declarative memory and motor memory
    Aysha Keisler
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 30:14817-23. 2010
  5. pmc Temporal discounting of reward and the cost of time in motor control
    Reza Shadmehr
    Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 30:10507-16. 2010
  6. pmc Cerebellar contributions to adaptive control of saccades in humans
    Minnan Xu-Wilson
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 29:12930-9. 2009
  7. pmc Changes in control of saccades during gain adaptation
    Vincent Ethier
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 28:13929-37. 2008
  8. pmc Acquisition of internal models of motor tasks in children with autism
    Jennifer C Gidley Larson
    Developmental Cognitive Neurology, Kennedy Krieger Institute, Baltimore, MD 21205, USA
    Brain 131:2894-903. 2008
  9. pmc Neural correlates of internal models
    Jean Jacques Orban de Xivry
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205 2195, UAS
    J Neurosci 28:7931-2. 2008
  10. pmc Sequential neural changes during motor learning in schizophrenia
    Laura M Rowland
    Maryland Psychiatric Research Center and Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA
    Psychiatry Res 163:1-12. 2008

Scientific Experts

  • Reza Shadmehr
  • Vincent S Huang
  • Minnan Xu-Wilson
  • Sarah E Pekny
  • Vincent Ethier
  • Jun Izawa
  • John W Krakauer
  • Courtney C Haswell
  • Stewart H Mostofsky
  • David S Zee
  • Mohammad Ali Ahmadi-Pajouh
  • Adrian M Haith
  • Aysha Keisler
  • Sarah E Criscimagna-Hemminger
  • Amy J Bastian
  • Joseph T Francis
  • Haiyin Chen-Harris
  • Laura M Rowland
  • Opher Donchin
  • Jennifer C Gidley Larson
  • Jean Jacques Orban de Xivry
  • Siavash Vaziri
  • Eun Jung Hwang
  • Thomas R Reppert
  • Mollie K Marko
  • Farzad Towhidkhah
  • Lauren R Dowell
  • Dwight Kravitz
  • Henry H Holcomb
  • Tushar Rane
  • Wilsaan M Joiner
  • Maurice A Smith
  • Jorn Diedrichsen

Detail Information

Publications25

  1. pmc Consolidation of motor memory
    John W Krakauer
    The Neurological Institute, Columbia University College of Physicians and Surgeons, 710 West 168th Street, New York, NY 10032, USA
    Trends Neurosci 29:58-64. 2006
    ..We also review evidence for and against a consolidation process for adaptation of arm movements. We propose that contradictions have arisen because consolidation can be masked by inhibition of memory retrieval...
  2. pmc Preparing to reach: selecting an adaptive long-latency feedback controller
    Mohammad Ali Ahmadi-Pajouh
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, The Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 32:9537-45. 2012
    ..Therefore, as the brain prepares for a reach, it loads a feedback controller specific to the upcoming reach. With adaptation, this feedback controller undergoes a change, increasing the gains for the expected sensory feedback...
  3. pmc Motor learning relies on integrated sensory inputs in ADHD, but over-selectively on proprioception in autism spectrum conditions
    Jun Izawa
    Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, USA
    Autism Res 5:124-36. 2012
    ..The results suggest that slower rate of adaptation and anomalous bias towards proprioceptive feedback during motor learning are characteristics of autism, whereas increased variability in execution is a characteristic of ADHD...
  4. pmc A shared resource between declarative memory and motor memory
    Aysha Keisler
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 30:14817-23. 2010
    ..Therefore, the fast process that supports formation of motor memory is not only neurally distinct from the slow process, but it shares critical resources with the declarative memory system...
  5. pmc Temporal discounting of reward and the cost of time in motor control
    Reza Shadmehr
    Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 30:10507-16. 2010
    ..The cost depends on the value that the brain assigns to stimuli, and the rate at which it discounts this value in time. The motor commands that move our eyes reflect this cost of time...
  6. pmc Cerebellar contributions to adaptive control of saccades in humans
    Minnan Xu-Wilson
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 29:12930-9. 2009
    ....
  7. pmc Changes in control of saccades during gain adaptation
    Vincent Ethier
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 28:13929-37. 2008
    ..Our simulations explained that, for each condition, the specific adaptation produced a saccade that brought the eyes to the target with the smallest motor costs...
  8. pmc Acquisition of internal models of motor tasks in children with autism
    Jennifer C Gidley Larson
    Developmental Cognitive Neurology, Kennedy Krieger Institute, Baltimore, MD 21205, USA
    Brain 131:2894-903. 2008
    ..Furthermore, the findings may have therapeutic implications, highlighting a reliable mechanism by which children with autism can most effectively alter their behaviour...
  9. pmc Neural correlates of internal models
    Jean Jacques Orban de Xivry
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205 2195, UAS
    J Neurosci 28:7931-2. 2008
  10. pmc Sequential neural changes during motor learning in schizophrenia
    Laura M Rowland
    Maryland Psychiatric Research Center and Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21228, USA
    Psychiatry Res 163:1-12. 2008
    ..The visual system, however, appears to be highly compensated in schizophrenia and the inability to rapidly modulate the motor cortex may be substantially corrected by the schizophrenic group's visuomotor adaptations...
  11. pmc Spontaneous recovery of motor memory during saccade adaptation
    Vincent Ethier
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, 720 Rutland Avenue, Baltimore, MD 21205, USA
    J Neurophysiol 99:2577-83. 2008
    ..Therefore short-term adaptive mechanisms that maintain accuracy of saccades rely on a memory system that has characteristics of a multistate process with a logarithmic distribution of timescales...
  12. pmc Adaptation and generalization in acceleration-dependent force fields
    Eun Jung Hwang
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, 416 Traylor Building, 720 Rutland Ave, Baltimore, MD 21205, USA
    Exp Brain Res 169:496-506. 2006
    ....
  13. pmc Why does the brain predict sensory consequences of oculomotor commands? Optimal integration of the predicted and the actual sensory feedback
    Siavash Vaziri
    Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205, USA
    J Neurosci 26:4188-97. 2006
    ....
  14. pmc Towards a computational neuropsychology of action
    John W Krakauer
    The Motor Performance Laboratory, Department of Neurology, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA
    Prog Brain Res 165:383-94. 2007
    ..When viewed from a computational perspective, the capabilities and deficits of these patients provide insights into the neural basis of our ability to willfully move our limbs and interact with the objects around us...
  15. ncbi Error generalization as a function of velocity and duration: human reaching movements
    Joseph T Francis
    Department of Physiology and Pharmacology, State University of New York Downstate School of Medicine, 450 Clarkson Ave, Brooklyn, NY 11203, USA
    Exp Brain Res 186:23-37. 2008
    ..Thus, the human internal model may employ such a population code...
  16. pmc Evidence for hyperbolic temporal discounting of reward in control of movements
    Adrian M Haith
    Departments of Biomedical Engineering and Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland 21287, USA
    J Neurosci 32:11727-36. 2012
    ..We suggest that there exists a single cost, rate of reward, which provides a unifying principle that may govern control of movements in timescales of milliseconds, as well as decision making in timescales of seconds to years...
  17. pmc A computational neuroanatomy for motor control
    Reza Shadmehr
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, 410 Traylor Building, 720 Rutland Ave, Baltimore, MD 21205, USA
    Exp Brain Res 185:359-81. 2008
    ..Finally, functions of the primary and the premotor cortices are related to implementing the optimal control policy by transforming beliefs about proprioceptive and visual states, respectively, into motor commands...
  18. pmc Adaptive control of saccades via internal feedback
    Haiyin Chen-Harris
    Departments of Biomedical Engineering and Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 28:2804-13. 2008
    ..It appears that in controlling saccades, the brain relies on an internal feedback that has the characteristics of a fast-adapting forward model...
  19. pmc Motor adaptation as a process of reoptimization
    Jun Izawa
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 28:2883-91. 2008
    ..Through reward-based optimization, we use the internal model to search for a better movement plan to minimize implicit motor costs and maximize rewards...
  20. pmc Representation of internal models of action in the autistic brain
    Courtney C Haswell
    Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
    Nat Neurosci 12:970-2. 2009
    ....
  21. ncbi Error correction, sensory prediction, and adaptation in motor control
    Reza Shadmehr
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    Annu Rev Neurosci 33:89-108. 2010
    ..Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors...
  22. pmc The intrinsic value of visual information affects saccade velocities
    Minnan Xu-Wilson
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, 416 Traylor Bldg, 720 Rutland Ave, Baltimore, MD, 21205, USA
    Exp Brain Res 196:475-81. 2009
    ..The intrinsic value of visual information appears to have a small but significant influence on the motor commands that guide saccades...
  23. pmc Persistence of motor memories reflects statistics of the learning event
    Vincent S Huang
    Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
    J Neurophysiol 102:931-40. 2009
    ..During motor learning, prior statistics that suggest changes are likely to be permanent result in slowly decaying memories, whereas prior statistics that suggest changes are transient result in rapidly decaying memories...
  24. pmc Protection and expression of human motor memories
    Sarah E Pekny
    Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205, USA
    J Neurosci 31:13829-39. 2011
    ..Rather, reinforcement appears to be a critical signal that affords protection to motor memories, and lack of reinforcement encourages retrieval of a competing memory...
  25. pmc Size of error affects cerebellar contributions to motor learning
    Sarah E Criscimagna-Hemminger
    Johns Hopkins University School of Medicine, 720 Rutland Ave, 416 Traylor Building, Baltimore, MD 21205, USA
    J Neurophysiol 103:2275-84. 2010
    ..The neural basis of motor learning in response to small and large errors appears to be distinct...