ArticleFrontiers in neuroinformatics2020
Simulation of a Human-Scale Cerebellar Network Model on the K Computer.
Article in Frontiers in neuroinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Article
- Advancing neuroengineering with Neuromorphic Twins.Nature communications · 2026Review
- Container-based framework for large-scale spiking network simulation.Frontiers in neuroscience · 2026Article
- Digital twin brain simulator for real-time consciousness monitoring and virtual intervention using primate electrocorticogram data.NPJ digital medicine · 2025Article
- Decoupling model descriptions from execution: a modular paradigm for extensible neurosimulation with EDEN.Frontiers in neuroinformatics · 2025Article
- Multi-scale spiking network model of human cerebral cortex.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Imitating and exploring the human brain's resting and task-performing states via brain computing: scaling and architecture.National science review · 2024Article
- Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders.Frontiers in neuroscience · 2024Review
- Artificial cerebellum on FPGA: realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control.Frontiers in neuroscience · 2024Article
- Accelerated preprocessing of large numbers of brain images by parallel computing on supercomputers.Scientific reports · 2023Article
- Simulations of cortical networks using spatially extended conductance-based neuronal models.The Journal of physiology · 2023Review
- Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST.Frontiers in neuroinformatics · 2023Article
- A MinireviewFrontiers in bioengineering and biotechnology · 2022Review
- A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction.Frontiers in neuroscience · 2022Article
- Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure.Frontiers in neuroinformatics · 2022Article
- Real-Time Simulation of a Cerebellar Scaffold Model on Graphics Processing Units.Frontiers in cellular neuroscience · 2021Article
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3 authors.
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Abstract
Computer simulation of the human brain at an individual neuron resolution is an ultimate goal of computational neuroscience. The Japanese flagship supercomputer, K, provides unprecedented computational capability toward this goal. The cerebellum contains 80% of the neurons in the whole brain. Therefore, computer simulation of the human-scale cerebellum will be a challenge for modern supercomputers. In this study, we built a human-scale spiking network model of the cerebellum, composed of 68 billion spiking neurons, on the K computer. As a benchmark, we performed a computer simulation of a cerebellum-dependent eye movement task known as the optokinetic response. We succeeded in reproducing plausible neuronal activity patterns that are observed experimentally in animals. The model was built on dedicated neural network simulation software called MONET (Millefeuille-like Organization NEural neTwork), which calculates layered sheet types of neural networks with parallelization by tile partitioning. To examine the scalability of the MONET simulator, we repeatedly performed simulations while changing the number of compute nodes from 1,024 to 82,944 and measured the computational time. We observed a good weak-scaling property for our cerebellar network model. Using all 82,944 nodes, we succeeded in simulating a human-scale cerebellum for the first time, although the simulation was 578 times slower than the wall clock time. These results suggest that the K computer is already capable of creating a simulation of a human-scale cerebellar model with the aid of the MONET simulator.
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