Testable predictions from recurrent backpropagation models of the vestibulo-ocular reflex

Research output: Contribution to journalArticlepeer-review

Abstract

Previous, feedforward (static) backpropagation models of the vestibulo-oculomotor system were able to capture the distributed aspects of eye-movement command representation by brainstem neurons. However, the highly distributed nature of the static networks makes them difficult to test using standard lesion and single-unit neurophysiological techniques. More recently, feedback (recurrent) backpropagation models have been used to study the dynamic and nonlinear features of the vestibulo-ocular reflex (VOR). Recurrent connections in dynamic networks are modeled on actual vestibular commissural fibers, which are surgically accessible. This anatomical feature enables clear, experimentally testable predictions to be derived from the dynamic models, involving the behavior of VOR neurons following lesions of the vestibular commissures. The testability of the recurrent models encourages a continued dialog between theory and experiment.

Original languageEnglish (US)
Pages (from-to)237-255
Number of pages19
JournalNeurocomputing
Volume6
Issue number2
DOIs
StatePublished - Apr 1994

Keywords

  • distributed processing
  • neurobiology
  • nonlinear behavior
  • recurrent backpropagation
  • testable predictions
  • velocity storage
  • vestibulo-ocular reflex

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

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