A cerebellar model of timing and prediction in the control of reaching

Andrew G. Barto*, Andrew H. Fagg, Nathan Sitkoff, James C. Houk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

86 Scopus citations

Abstract

A simplified model of the cerebellum was developed to explore its potential for adaptive, predictive control based on delayed feedback information. An abstract representation of a single Purkinje cell with multistable properties was interfaced, using a formalized premotor network, with a simulated single degree-of-freedom limb. The limb actuator was a nonlinear spring-mass system based on the nonlinear velocity dependence of the stretch reflex. By including realistic mossy fiber signals, as well as realistic conduction delays in afferent and efferent pathways, the model allowed the investigation of timing and predictive processes relevant to cerebellar involvement in the control of movement. The model regulates movement by learning to react in an anticipatory fashion to sensory feedback. Learning depends on training information generated from corrective movements and uses a temporally asymmetric form of plasticity for the parallel fiber synapses on Purkinje cells.

Original languageEnglish (US)
Pages (from-to)565-594
Number of pages30
JournalNeural Computation
Volume11
Issue number3
DOIs
StatePublished - Apr 1 1999

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Cognitive Neuroscience

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