NDLI: A cerebellar model for predictive motor control tested in a brain-based device

Content Provider	PubMed Central
Author	Mckinstry, Jeffrey L. Edelman, Gerald M. Krichmar, Jeffrey L.
Copyright Year	2006
Abstract	The cerebellum is known to be critical for accurate adaptive control and motor learning. We propose here a mechanism by which the cerebellum may replace reflex control with predictive control. This mechanism is embedded in a learning rule (the delayed eligibility trace rule) in which synapses onto a Purkinje cell or onto a cell in the deep cerebellar nuclei become eligible for plasticity only after a fixed delay from the onset of suprathreshold presynaptic activity. To investigate the proposal that the cerebellum is a general-purpose predictive controller guided by a delayed eligibility trace rule, a computer model based on the anatomy and dynamics of the cerebellum was constructed. It contained components simulating cerebellar cortex and deep cerebellar nuclei, and it received input from a middle temporal visual area and the inferior olive. The model was incorporated in a real-world brain-based device (BBD) built on a Segway robotic platform that learned to traverse curved paths. The BBD learned which visual motion cues predicted impending collisions and used this experience to avoid path boundaries. During learning, the BBD adapted its velocity and turning rate to successfully traverse various curved paths. By examining neuronal activity and synaptic changes during this behavior, we found that the cerebellar circuit selectively responded to motion cues in specific receptive fields of simulated middle temporal visual areas. The system described here prompts several hypotheses about the relationship between perception and motor control and may be useful in the development of general-purpose motor learning systems for machines.
Related Links	http://dx.doi.org/10.1073/pnas.0511281103
Ending Page	3392
Page Count	6
Starting Page	3387
File Format	PDF
ISSN	00278424
e-ISSN	10916490
Journal	Proceedings of the National Academy of Sciences of the United States of America
Issue Number	9
Volume Number	103
Language	English
Publisher	National Academy of Sciences
Publisher Date	2006-02-28
Access Restriction	Open
Rights Holder	National Academy of Sciences
Subject Keyword	General Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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