Title :
Computer Simulation for Cerebellar Learning Using Climbing Fiber Spikes as the Error Signal
Author :
Zhang, Shaobai ; Ran, Xiaogang
Abstract :
Cerebellar motor learning, including an acquisition of ocular following response (OFR), can be reproduced using mean firing rates (MFRs) as the error signal of climbing fibers (CFs). But real neurons transmit the signal by spikes, which are discrete events. It is not obvious whether learning is possible with discrete spike trains. To address this issue we performed a computer simulation of cerebellar learning using CF spikes - instead of MFR as the error signal for Purkinje cells (PCs). To generate the spikes we used four spike generation models. And we found that in an OFR task with a constant visual velocity, learning was successful with stochastic models, but not in the deterministic models
Keywords :
cerebellar model arithmetic computers; learning (artificial intelligence); Purkinje cells; cerebellar motor learning; climbing fibers; constant visual velocity; error signal; fiber spikes; mean firing rates; ocular following response; spike generation models; Biological system modeling; Brain modeling; Computational modeling; Computer errors; Computer simulation; Control engineering; Encoding; Neurons; Optical fiber sensors; Personal communication networks;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614943