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.
Highlights
Memory formation has two stages: memory acquisition and memory consolidation (Dudai, 2004)
Using only 1 graphics processing units (GPUs), we found that computer simulation of the cerebellar activity for 6 s, corresponding to 1 cycle of simulated optokinetic stimulus, spends 17.7 s
A theoretical model is a mathematical description of a specific phenomenon
Summary
Memory formation has two stages: memory acquisition and memory consolidation (Dudai, 2004). Repeated training with a sufficient rest between training sessions gradually form another type of memory, a long-term memory, which is robust and persists for days and weeks Owing to the parallel computing on GPUs, we were able to conduct the computer simulation fast enough to complete a very long computer simulation in a practical time, Eventually, we achieved realtime simulation, which means that computer simulation of the cerebellar activity for 1 s completes within 1 s in the real-world time (Igarashi et al, 2011; Yamazaki and Igarashi, 2013) This is essential for computer simulation of the cerebellar posttraining memory consolidation, because the memory consolidation takes days or even weeks. We examined the detailed spike patterns of neurons, which was abstracted and ignored in our theory
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