Name
Title | ||
|---|---|---|
A Neural Net Model for Adaptive Control of Saccadic Accuracy by Primate Cerebellum and Brainstem |
Abstract | ||
|---|---|---|
Accurate saccades require interaction between brainstem circuitry and the cerebeJJum. A model of this interaction is described, based on Kawato's principle of feedback-error-Iearning. In the model a part of the brainstem (the superior colliculus) acts as a simple feedback controJJer with no knowledge of initial eye position, and provides an error signal for the cerebeJJum to correct for eye-muscle nonIinearities. This teaches the cerebeJJum, modelled as a CMAC, to adjust appropriately the gain on the brainstem burst-generator's internal feedback loop and so alter the size of burst sent to the motoneurons. With direction-only errors the system rapidly learns to make accurate horizontal eye movements from any starting position, and adapts realistically to subsequent simulated eye-muscle weakening or displacement of the saccadic target. |
Year | Venue | Keywords |
|---|---|---|
1991 | NIPS | neural net,adaptive control |
Field | DocType | Citations |
Superior colliculus,Neuroscience,Computer science,Eye movement,Artificial intelligence,Adaptive control,Saccadic masking,Artificial neural network,Internal feedback,Brainstem,Cerebellum,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Dean | 1 | 0 | 0.68 |
| John E. W. Mayhew | 2 | 233 | 322.10 |
| Pat Langdon | 3 | 18 | 5.12 |