Simulation and assimilation of the digital human brain | Nature Computational Science
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Here we present the Digital Brain (DB)—a platform for simulating spiking neuronal networks at the large neuron scale of the human brain on the basis of personalized magnetic resonance imaging data and biological constraints. The DB aims to reproduce both the resting state and certain aspects of the action of the human brain. An architecture with up to 86 billion neurons and 14,012 GPUs—including a two-level routing scheme between GPUs to accelerate spike transmission in up to 47.8 trillion neuronal synapses—was implemented as part of the simulations. We show that the DB can reproduce blood-oxygen-level-dependent signals of the resting state of the human brain with a high correlation coefficient, as well as interact with its perceptual input, as demonstrated in a visual task. These results indicate the feasibility of implementing a digital representation of the human brain, which can open the door to a broad range of potential applications. The Digital Brain platform is capable of simulating spiking neuronal networks at the neuronal scale of the human brain. The platform is used to reproduce blood-oxygen-level-dependent signals in both the resting state and action, thereby predicting the visual evaluation scores.
  • ☆ Yσɠƚԋσʂ ☆@lemmygrad.mlOP
    8·
    29 days ago

    Chinese researchers have simulated a human brain using 86 billion neurons and trillions of synapses. Despite U.S. chip sanctions, their team innovated with distributed learning using domestic GPUs. The model achieved 93% correlation with real human brain activity, enabling groundbreaking medical research without real brain testing. This breakthrough has been made freely available, fostering global collaboration. In China, partnerships between hospitals, companies, and universities drive rapid innovation, contrasting with slower progress in the West.