Computer Simulation for Cerebellar Learning Using Climbing Fiber Spikes as the Error Signal

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 poss...

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Bibliographic Details
Main Authors: Shaobai Zhang, Xiaogang Ran
Format: Conference Proceeding
Language:English
Subjects:
Biological system modeling
Brain modeling
Computational modeling
Computer errors
Computer simulation
Control engineering
Encoding
Neurons
Optical fiber sensors
Personal communication networks
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Summary: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
DOI:10.1109/ICNNB.2005.1614943