在人类连接体中,结构能预测个人层面的功能吗?
Lars Smolders1,2, Wouter De Baene3, Geert-Jan Rutten4
1Eindhoven University of Technology , Department of Mathematics and Computer Science, PO Box 513, Eindhoven, 5600 MB, Netherlands. l.smolders@etz.nl.
Brain structure & function
|April 24, 2024
概括
使用当前模型从结构连接 (SC) 预测个体大脑功能连接 (FC) 是有问题的. 集团平均FC通常表现与个人级预测模型一样好或更好.
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.
- 脑部成像 脑部成像
背景情况:
- 最近的研究旨在从结构连接 (SC) 预测个体大脑的功能连接 (FC).
- 这些预测模型为个人级别的大脑映射提供了增强的性能和实用性的承诺.
- 这些个人级别的SC-to-FC映射预测的有效性需要严格的调查.
研究的目的:
- 批判性地评估现有的预测模型是否真正实现了从SC到FC的有意义的个人级别映射.
- 为了比较三个著名的SC-to-FC预测模型与一个简单的组平均预测器的性能.
- 评估支持预测模型实用性的额外分析的稳定性.
主要方法:
- 利用了人类结合体项目的数据,在三个相关研究中共享.
- 通过从训练数据中平均功能连接 (FC) 来构建基线预测器.
- 分析了三个选定的预测模型和个人水平FC预测中的组平均预测器的表现.
主要成果:
- 与研究的个人级别模型相比,组平均FC预测器显示了同等或更高的原始预测性能.
- 最初的研究作者进行的额外分析,旨在显示超出原始预测的价值,可以使用组平均预测器重现.
- 这些发现引发了对通过评估方法实现的个人级别SC-to-FC映射的意义的问题.
结论:
- 目前的方法可能不适合数据,样本大小小,或缺乏足够的信息来进行可靠的SC-FC映射.
- 未来的个人水平研究必须报告与组平均值相比的表现,并证明真正的个人水平预测信息.
- 建议探索SC和FC的替代构造,以改善个人级别的映射.
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