Generalization and multirate models of motor adaptation

Neural Computation

Volumn 24, Issue 4, 2012, Pages 939-966

  Tanaka, Hirokazu ^a   Krakauer, John W ^b   Sejnowski, Terrence J ^a,c  

^a HOWARD HUGHES MEDICAL INSTITUTE   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTATION; ARTICLE; BIOLOGICAL MODEL; COMPUTER SIMULATION; HUMAN; LEARNING; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY;

ADAPTATION, PHYSIOLOGICAL; COMPUTER SIMULATION; GENERALIZATION (PSYCHOLOGY); HUMANS; LEARNING; MODELS, NEUROLOGICAL; MOVEMENT;

FAST PROCESS; GENERALISATION; MOTOR ADAPTATION; MULTI-RATE MODEL; PROCESS-MODELS; PSYCHOPHYSICAL STUDIES; REACHING MOVEMENTS; TWO WAYS; TWO-STATE MODEL; WORK SPACE;

LEARNING SYSTEMS;

EID: 84861171288     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/NECO_a_00262     Document Type: Article

References (37)

1. Akaike, H. (1969). Fitting autoregressive models for prediction. Annals of the Institute of Statistical Mathematics, 21, 243-247.
2. Akaike, H. (1974). A new look at the statistical model identification. IEEE Trans. Automatic Control, 19, 716-723.
3. Baddeley, R. J., Ingram, H. A., & Miall, R. C. (2003). System identification applied to a visuomotor task: Near-optimal human performance in a noisy changing task. J. Neurosci., 23, 3066-3075.
4. Cheng, S., & Sabes, P. N. (2007). Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics. J. Neurophysiol., 97, 3057-3069.
5. Criscimagna-Hemminger, S. E., Bastian, A. J., & Shadmehr, R. (2010). Size of error affects cerebellar contributions to motor learning. J. Neurophysiol., 103, 2275-2284.
6. Criscimagna-Hemminger, S. E., & Shadmehr, R. (2008). Consolidation patterns of human motor memory. J. Neurosci., 28, 9610-9618.
7. Donchin, O., Francis, J. T., & Shadmehr, R. (2003). Quantifying generalization from trial-by-trial behavior of adaptive systems that learn with basis functions: Theory and experiments in human motor control. J. Neurosci., 23, 9032-9045.
8. Efron, B. (1982). The jackknife, the bootstrap and other resampling Plans. Philadelphia: Society for Industrial and Applied Mathematics.
9. Ethier, V., Zee, D. S.,&Shadmehr, R. (2008). Spontaneous recovery ofmotor memory during saccade adaptation. J. Neurophysiol., 99, 2577-2583.
10. Fine, M. S., & Thoroughman, K. A. (2006). Motor adaptation to single force pulses: Sensitive to direction but insenstive to within movement pulse placement and magnitude. J. Neurophysiol., 96, 710-720.
11. Francis, J. T. (2008). Error generalization as a function of velocity and duration: Human reaching movements. Exp. Brain Res., 186, 23-37.
12. Gandolfo, F., Mussa-Ivaldi, F. A., & Bizzi, E. (1996). Motor learning by field approximation. Proc. Natl. Acad. Sci. USA, 93, 3843-3846.
13. Goodwin, G. C.,&Sin, K. S. (1984). Adaptive filtering prediction and control. Englewood Cliffs, NJ: Prentice-Hall.
14. Gupta, N., & Mehra, R. (1974). Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculations. IEEE Trans. Automatic Control, 19, 774-783.
15. 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, 787-801.
16. Imamizu, H., Uno, Y., & Kawato, M. (1995). Internal representations of themotor apparatus: Implications from generalization in visuomotor learning. J. Exp. Psychol. Hum. Percept. Perform., 21, 1174-1198.
17. Joiner, W. M., & Smith, M. A. (2008). Long-term retention explained by a model of short-term learning in the adaptive control of reaching. J. Neurophysiol., 100, 2948-2955.
18. Kalman, R. E. (1960). A new approach to linear filtering and prediction problems. J. Basic Eng., 82, 35-45.
19. Keisler, A., & Shadmehr, R. (2010). A shared resource between declarative memory and motor memory. J. Neurosci., 30, 14817-14823.
20. K̈ording, K. P., Tenenbaum, J. B., & Shadmehr, R. (2007). The dynamics of memory as a consequence of optimal adaptation to a changing body. Nat. Neurosci., 10, 779-786.
21. Krakauer, J. W., Ghez, C., & Ghilardi, M. F. (2005). Adaptation to visuomotor transformations: Consolidation, interference, and forgetting. J. Neurosci., 25, 473-478.
22. Krakauer, J. W., Ghilardi, M. F., & Ghez, C. (1999). Independent learning of internal models for kinematic and dynamic control of reaching. Nat. Neurosci., 2, 1026-1031.
23. Krakauer, J.W., Pine, Z.M., Ghilardi, M. F.,&Ghez, C. (2000). Learning of visuomotor transformations for vectorial planning of reaching trajectories. J. Neurosci., 20, 8916-8924.
24. Lee, J. Y.,&Schweighofer, N. (2009).Dual adaptation supports a parallel architecture of motor memory. J. Neurosci., 29, 10396-10404.
25. Ljung, L., & Ljung, E. J. (1987). System identification: Theory for the user. Englewood Cliffs, NJ: Prentice-Hall.
26. Mattar, A. A., & Ostry, D. J. (2007). Modifiability of generalization in dynamics learning. J. Neurophysiol., 98, 3321-3329.
27. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (2007). Numerical recipes: The art of scientific computing. Cambridge: Cambridge University Press.
28. Shadmehr, R. (2004). Generalization as a behavioral window to the neural mechanisms of learning internal models. Hum. Mov. Sci., 23, 543-568.
29. Shumway, R. H., & Stoffer, D. S. (1982). An approach to time series smoothing and forecasting using the EM algorithm. J. Time Series Analysis, 3, 253-264.
30. Shumway, R. H., & Stoffer, D. S. (2000). Time series analysis and its applications. Berlin: Springer-Verlag.
31. Sing, G. C., & Smith, M. A. (2010). Reduction in learning rates associated with anterograde interference results from interactions between different timescales in motor adaptation. PLoS Comput. Biol., 6.
32. Smith, M. A., Ghazizadeh, A., & Shadmehr, R. (2006). Interacting adaptive processes with different timescales underlie short-term motor learning. PLoS Biol., 4, e179.
33. Tanaka, H., Sejnowski, T. J., & Krakauer, J. W. (2009). Adaptation to visuomotor rotation through interaction between posterior parietal and motor cortical areas. J. Neurophysiol., 102, 2921-2932.
34. Taylor, J. A., & Ivry, R. B. (2011). Flexible cognitive strategies duringmotor learning. PLoS Comput. Biol., 7, e1001096.
35. Thoroughman, K. A., & Shadmehr, R. (2000). Learning of action through adaptive combination of motor primitives. Nature, 407, 742-747.
36. Tseng, Y. W., Diedrichsen, J., Krakauer, J. W., Shadmehr, R., & Bastian, A. J. (2007). Sensory prediction errors drive cerebellum-dependent adaptation of reaching. J. Neurophysiol., 98, 54-62.
37. Zarahn, E., Weston, G. D., Liang, J., Mazzoni, P., & Krakauer, J.W. (2008). Explaining savings for visuomotor adaptation: Linear time-invariant state-space models are not sufficient. J. Neurophysiol., 100, 2537-2548.