The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Models of the cerebellum and motor learning
Abstract
This article reviews models of the cerebellum and motor learning, from the landmark papers by Marr and Albus through those of the present time. The unique architecture of the cerebellar cortex is ideally suited for pattern recognition, but how is pattern recognition incorporated into motor control and learning systems? The present analysis begins with a discussion of exactly what the cerebellar cortex needs to regulate through its anatomically defined projections to premotor networks. Next, we examine various models showing how the microcircuitry in the cerebellar cortex could be used to achieve its regulatory functions. Having thus defined what it is that Purkinje cells in the cerebellar cortex must learn, we then evaluate theories of motor learning. We examine current models of synaptic plasticity, credit assignment, and the generation of training information, indicating how they could function cooperatively to guide the processes of motor learning.
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Citations
Cites
A synaptic model of memory: long-term potentiation in the hippocampus
Bliss, T. V. P., & Collingridge, G. L. (1993) · Nature · doi:10.1038/361031a0 · Cited by 11,566
Marr, D. (1969) · The Journal of Physiology · doi:10.1113/jphysiol.1969.sp008820 · Cited by 3,253
A theory of cerebellar function
Albus, J. S. (1971) · Mathematical Biosciences · doi:10.1016/0025-5564(71)90051-4 · Cited by 2,539
A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
Albus, J. S. (1975) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3426922 · Cited by 2,177
A Closed-Loop Theory of Motor Learning
Adams, J. A. (1971) · Journal of Motor Behavior · doi:10.1080/00222895.1971.10734898 · Cited by 1,636
Practice-related Changes in Human Brain Functional Anatomy during Nonmotor Learning
Raichle, M. E., Fiez, J. A., Videen, T. O., MacLeod, A.-M. K., Pardo, J. V., Fox, P. T., & Petersen, S. E. (1994) · Cerebral Cortex · doi:10.1093/cercor/4.1.8 · Cited by 1,593
Toward a modern theory of adaptive networks: Expectation and prediction.
Sutton, R. S., & Barto, A. G. (1981) · Psychological Review · doi:10.1037/0033-295x.88.2.135 · Cited by 1,450
Self-citationAnatomical evidence for cerebellar and basal ganglia involvement in higher cognitive function
Middleton, F. A., & Strick, P. L. (1994) · Science · doi:10.1126/science.7939688 · Cited by 1,356
Black, J. E., Isaacs, K. R., Anderson, B. J., Alcantara, A. A., & Greenough, W. T. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.14.5568 · Cited by 1,161
Is the cerebellum a Smith predictor?
Miall, R. C., Weir, D. J., Wolpert, D. M., & Stein, J. F. (1993) · Journal of Motor Behavior · doi:10.1080/00222895.1993.9942050 · Cited by 1,071
Cited by
Predictive reward signal of dopamine neurons
Schultz, W. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.1 · Cited by 4,564
Getting formal with dopamine and reward
Schultz, W. (2002) · Neuron · doi:10.1016/s0896-6273(02)00967-4 · Cited by 2,574
Neuronal Coding of Prediction Errors
Schultz, W., & Dickinson, A. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.473 · Cited by 1,427
Cerebellar complex spikes encode both destinations and errors in arm movements
Kitazawa, S., Kimura, T., & Yin, P.-B. (1998) · Nature · doi:10.1038/33141 · Cited by 401
Effects of Lesions of the Oculomotor Vermis on Eye Movements in Primate: Saccades
Takagi, M., Zee, D. S., & Tamargo, R. J. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.4.1911 · Cited by 373
Metadata
- Authors
- Houk, J. C., Buckingham, J. T., & Barto, A. G.
- Venue
- Behavioral and Brain Sciences
- Publisher
- Cambridge University Press (CUP)
- Published
- 1996-09
- Volume
- 19
- Issue
- 3
- Pages
- 368-383
- ISSN
- 0140-525X (ISSN-L)
- 1469-1825
- OpenAlex
- W2064566192
- Cited by
- 212
- References
- 12
- FWCI
- 6.17
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.