Using input minimization to train a cerebellar model to simulate regulation of smooth pursuit

DOI10.1007/S00422-009-0340-7zbMath1344.92040OpenAlexW2093957966WikidataQ43236061 ScholiaQ43236061MaRDI QIDQ309490

Thomas J. Anastasio, Fredrick H. Rothganger

Publication date: 7 September 2016

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00422-009-0340-7

zbMATH Keywords

learningcomputational modelcerebellumsmooth pursuit

Mathematics Subject Classification ID

Neural biology (92C20)

Cites Work

• Adaptive filter model of the cerebellum
• A mathematical model of the cerebellar-olivary system. I: Self-regulating equilibrium of climbing fiber activity
• Directed drift: A new linear threshold algorithm for learning binary weights on-line
• Self-organizing maps.

This page was built for publication: Using input minimization to train a cerebellar model to simulate regulation of smooth pursuit