使用詹森和里特神经质量模型比较个人和小组级模拟的神经生理学大脑连接
S D Kulik1,2,3, L Douw1,2, E van Dellen4
1Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Anatomy & Neuroscience, Amsterdam Neuroscience, Amsterdam The Netherlands.
Network neuroscience (Cambridge, Mass.)
|October 2, 2023
概括
这项研究表明,使用个体大脑连接数据可以比使用平均数据更改大脑活动的计算模型. 这有助于理解个人的大脑网络模式.
科学领域:
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
- 脑部成像 脑部成像
背景情况:
- 功能连接 (FC) 模式通常使用基于神经元动态和大脑解剖学的计算模型进行研究.
- 目前尚不清楚群体平均数据是否可以准确预测单个FC模式.
研究的目的:
- 评估单个FC模式的计算模型的预测能力.
- 为了比较个人与群体平均结构连接 (SC) 在预测实证FC的有效性.
- 评估用于估计FC的不同指标及其适用于个人预测的适用性.
主要方法:
- 采用了詹森和里特的神经质量模型与个人结构连接 (SC) 相结合.
- 相关的模拟FC与个体磁脑学衍生的经验FC.
- 使用基于相位 (相位滞后指数 (PLI),相位锁定值 (PLV)) 和基于振幅 (振幅封面相关性 (AEC)) 的指标进行FC估计.
主要成果:
- 与基于阶段的指标相比,振幅包相关性 (AEC) 在模拟和实证FC之间显示出更好的匹配.
- 个体SC导致模拟和实证FC之间的相关性高于组平均SC.
- 来自其他参与者的SC产生了与使用参与者自己的SC相似的预测相关性.
结论:
- 对于 FC 模拟,使用单个 SC 而不是 Jansen 和 Rit 模型的组平均 SC 具有好处.
- 这种方法增强了对驱动个人功能网络轨迹的机制的理解.
- 这些发现强调了个性化数据在计算神经科学模型中的重要性.
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