Computational model
Cerebellar Model for the Optokinetic Response (Kim and Lim 2021)
Woochang Lim
OKR [11007]
We consider a cerebellar spiking neural network for the optokinetic response (OKR). Individual granule (GR) cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of ‘‘effective’’ depression at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates.
  • Cerebellum interneuron granule GLU cell Show Other
  • Cerebellum interneuron Golgi GABA cell Show Other
  • Cerebellum Purkinje GABA cell Show Other
Kim SY, Lim W (2021) Effect of Diverse Recoding of Granule Cells on Optokinetic Response in A Cerebellar Ring Network with Synaptic Plasticity. Neural Networks 134: 173-204
Other categories referring to Cerebellar Model for the Optokinetic Response (Kim and Lim 2021)
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Last Time: 4/2/2022 12:37:11 PM
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