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虚拟大脑推理 (VBI) 是一套灵活和整合性的工具包,用于在全脑模型上高效的概率推理

Abolfazl Ziaeemehr¹, Marmaduke Woodman¹, Lia Domide²

¹Aix Marseille University, INSERM, INS, Inst Neurosci System, Marseille, France.

|December 12, 2025

概括

一个新的工具包,虚拟大脑推理 (VBI),使虚拟大脑模型的自动参数估计. 这通过改善大脑功能理解来推进网络神经科学和精准医学.

科学领域:

神经科学是一个神经科学.
计算神经科学是一种神经科学.
系统神经科学系统神经科学

背景情况:

网络神经科学利用全脑网络建模来了解大脑功能和认知.
虚拟大脑建模整合了计算大脑动态与个体神经成像数据.
需要自动化工具来估计这些模型的大规模控制参数.

研究的目的:

介绍虚拟大脑推理 (VBI),这是一个开源工具包,用于对虚拟大脑模型的贝叶斯推理.
解决大规模大脑网络分析的自动化模型反转的差距.
从各种神经成像数据中进行生物物理解释的推断.

主要方法:

开发了VBI工具包,提供快速模拟,特征提取,数据处理和概率机器学习.
在虚拟大脑模型中使用贝叶斯推理进行参数估计.
进行了in-silico测试,以验证推断的准确性和可靠性.

主要成果:

证明了VBI对常见的全脑网络模型和神经成像数据的准确性和可靠性.
VBI 能够从非侵入性和侵入性记录中进行高效和可解释的推断.
该工具包支持用于评估假设的不确定性量化.

结论:

VBI为虚拟大脑模型推理提供了灵活和整合性的解决方案.
该工具包有可能在网络神经科学中推进假设测试.
通过增强大脑功能的预测模型,VBI可以为精准医学做出贡献.

关键词:

贝叶斯人的推理.大脑动力学大脑动力学控制参数的控制参数人类人类人类人类人类人类人类神经成像是一种神经成像.神经科学神经科学机器学习的概率学.虚拟大脑建模虚拟大脑建模

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