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Simulation and assimilation of the digital human brain
Wenlian Lu1,2,3, Xin Du1,2,4,5, Jiexiang Wang1,2
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Nature Computational Science
|December 20, 2024
Summary
Scientists created a Digital Brain (DB) simulation platform to model the human brain
Area of Science:
- Computational Neuroscience
- Neuroscience
- Artificial Intelligence
Background:
- The human brain's complexity presents significant challenges for large-scale neural simulations.
- Previous models have been limited in scale and biological realism.
Purpose of the Study:
- To develop a scalable platform, the Digital Brain (DB), for simulating human-scale spiking neuronal networks.
- To reproduce resting-state activity and perceptual interactions of the human brain.
Main Methods:
- Utilized personalized magnetic resonance imaging data and biological constraints.
- Implemented a large-scale architecture with 86 billion neurons and 14,012 GPUs.
- Employed a two-level routing scheme for accelerated spike transmission across 47.8 trillion synapses.
Main Results:
- The Digital Brain accurately reproduced blood-oxygen-level-dependent (BOLD) signals during resting state with high correlation.
- The platform demonstrated interaction with perceptual input, validated through a visual task simulation.
Conclusions:
- The Digital Brain platform demonstrates the feasibility of creating a digital human brain representation.
- This achievement opens avenues for diverse applications in neuroscience and beyond.
