人工智能作为替代大脑:桥梁神经动态模型和数据
Yinuo Zhang1, Demao Liu2,3,4, Zhichao Liang1
1Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
National science review
|February 5, 2026
概括
人工智能 (AI) 正在帮助人们创造新技术.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 计算神经科学是一种神经科学.
背景情况:
- 传统的生物物理模型用于脑模拟是以假设为导向的.
- 人工智能提供数据驱动的方法来解决神经科学中的反向问题.
- 从历史数据中预测整个大脑动态是一个关键的挑战.
研究的目的:
- 引入一个统一的框架来构建基于人工智能的代孕大脑.
- 整合前向建模,反向问题解决和模型评估.
- 利用人工智能和大规模的大脑数据进行神经系统解码和动态预测.
主要方法:
- 利用先进的人工智能模型来表达他们的表达力.
- 使用大规模的大脑数据集进行培训和验证.
- 在统一的框架内整合前建模,反向问题解决和模型评估.
主要成果:
- 开发基于人工智能的代孕大脑,能够预测复杂的大脑动态.
- 用代孕大脑作为动态系统分析平台的演示.
- 突出代理大脑对于虚拟扰动和神经刺激的有用性.
结论:
- 基于人工智能的代孕大脑为理解神经系统提供了一种新的方法.
- 这些模型有助于解码复杂,高维和非线性大脑动态.
- 人工智能替代大脑是理论神经科学和翻译神经工程应用之间的桥梁.
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