Spiking neural network model of the cerebellum with 5,000 neurons in Go/No-go tasks.

Spiking neural network model of the cerebellum with 5,000 neurons in Go/No-go tasks.

<p>A: The model consists of two groups of neurons in the PC–CN–IO circuitry, each corresponding to TC1 & TC3 (TC<sub>Go</sub>: PC<sub>Go</sub>–CN<sub>Go</sub>–IO<sub>Go</sub>) and TC2 & TC4 (TC<sub>Nogo</sub>: PC<sub>Nog...

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Bibliographic Details
Main Author:	Huu Hoang (9188747) (author)
Other Authors:	Shinichiro Tsutsumi (20890138) (author), Masanori Matsuzaki (347555) (author), Masanobu Kano (170471) (author), Keisuke Toyama (371727) (author), Kazuo Kitamura (90252) (author), Mitsuo Kawato (37377) (author)
Published:	2025
Subjects:	Neuroscience Sociology Biological Sciences not elsewhere classified Information Systems not elsewhere classified tensor component analysis inferior olive neurons cell synaptic plasticity assuming bidirectional parallel 000 spiking neurons fiber firing rates supervised learning algorithms reinforcement learning variables modular reinforcement learning cerebellar nuclei neurons discrimination learning separately two distinct components respective auditory cues div >< p 2 +</ sup 000 purkinje cells climbing fiber inputs fiber purkinje purkinje cells learning trial learning process learning model discrimination task cerebellar neural granule cells go cues go auditory typically associated specifically activated specific actors results indicate prediction errors photon ca particular emphasis network model method enabled licking responses licking behaviors inverse relationship imaging data accurately reproduce
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