title: Real-World-Time Simulation of Memory Consolidation in a Large-Scale Cerebellar Model.
abstract: We report development of a large-scale spiking network model of the cerebellum composed of more than 1 million neurons. The model is implemented on graphics processing units (GPUs), which are dedicated hardware for parallel computing. Using 4 GPUs simultaneously, we achieve realtime simulation, in which computer simulation of cerebellar activity for 1 s completes within 1 s in the real-world time, with temporal resolution of 1 ms. This allows us to carry out a very long-term computer simulation of cerebellar activity in a practical time with millisecond temporal resolution. Using the model, we carry out computer simulation of long-term gain adaptation of optokinetic response (OKR) eye movements for 5 days aimed to study the neural mechanisms of posttraining memory consolidation. The simulation results are consistent with animal experiments and our theory of posttraining memory consolidation. These results suggest that realtime computing provides a useful means to study a very slow neural process such as memory consolidation in the brain.
authors.affiliation: Department of Communication Engineering and Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications Tokyo, Japan.
authors.forename: Masato
authors.initials: M
authors.lastname: Gosui
authors.affiliation: Department of Communication Engineering and Informatics, Graduate School of Informatics and Engineering, The University of Electro-CommunicationsTokyo, Japan; Neuroinformatics Japan Center, RIKEN Brain Science InstituteSaitama, Japan; Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and TechnologyIbaraki, Japan.
authors.forename: Tadashi
authors.initials: T
authors.lastname: Yamazaki
keywords: cerebellum; graphics processing unit; memory consolidation; model; optokinetic response; realtime simulation