使用体外神经网络对自由能量原理的实验验证
Takuya Isomura1, Kiyoshi Kotani2, Yasuhiko Jimbo3
1Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan. takuya.isomura@riken.jp.
Nature communications
|August 7, 2023
概括
这项研究表明,自由能量原理可以从数量上预测神经元网络的自我组织. 在实验室中进行因果推理的神经网络表明,最小化变量的自由能量解释了它们的反应和可塑性.
科学领域:
- 计算神经科学是一种神经科学.
- 理论神经科学 理论神经科学
- 系统神经科学 系统神经科学
背景情况:
- 自由能量原理的经验验证具有挑战性,特别是在细胞和突触层面.
- 自由能量原理为理解大脑功能提供了一个统一的框架,但需要特定的过程理论来应用.
- 神经网络表现出自我组织,并执行复杂的计算,如因果推理.
研究的目的:
- 在体外实验上验证自由能量原理的定量预测.
- 研究变量自由能量最小化在神经元网络自我组织和因果推理中的作用.
- 评估网络刺激性和突触可塑性与自由能量原理的关系.
主要方法:
- 利用逆向工程技术在实验室中分析大鼠皮层神经元网络.
- 应用了由混合隐藏源组成的电刺激来探测网络响应.
- 从药理上操纵网络兴奋性并改变有效的突触连接.
主要成果:
- 在体外神经网络自我组织,选择性地编码来自混合刺激的隐藏源.
- 药理学调节网络刺激性改变了因果推断,与先前信念的变化一致.
- 突触连接的调整导致了变量的自由能量减少,连接强度编码生成模型参数.
结论:
- 变量自由能量最小化量化预测神经元网络的自我组织,包括它们的反应和突触可塑性.
- 该研究证实了 in vitro神经网络模型中自由能量原理的适用性和预测有效性.
- 研究结果支持自由能量原理作为控制神经计算和网络动态的基本机制.
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