N.P. Bechtereva Institute of the Human Brain, Russian Academy of Sciences, St. Petersburg, Russia.
Commun Biol. 2024 Oct 26;7(1):1402. doi: 10.1038/s42003-024-07088-3.
Higher brain functions require flexible integration of information across widely distributed brain regions depending on the task context. Resting-state functional magnetic resonance imaging (fMRI) has provided substantial insight into large-scale intrinsic brain network organisation, yet the principles of rapid context-dependent reconfiguration of that intrinsic network organisation are much less understood. A major challenge for task connectome mapping is the absence of a gold standard for deriving whole-brain task-modulated functional connectivity matrices. Here, we perform biophysically realistic simulations to control the ground-truth task-modulated functional connectivity over a wide range of experimental settings. We reveal the best-performing methods for different types of task designs and their fundamental limitations. Importantly, we demonstrate that rapid (100 ms) modulations of oscillatory neuronal synchronisation can be recovered from sluggish haemodynamic fluctuations even at typically low fMRI temporal resolution (2 s). Finally, we provide practical recommendations on task design and statistical analysis to foster task connectome mapping.
高级脑功能需要根据任务上下文灵活整合来自广泛分布的脑区的信息。静息态功能磁共振成像(fMRI)为理解大脑内在网络组织的大规模提供了重要的见解,但内在网络组织的快速上下文相关重新配置的原理却知之甚少。任务连接组映射的一个主要挑战是缺乏用于得出全脑任务调制功能连接矩阵的黄金标准。在这里,我们进行了生物物理上逼真的模拟,以控制在广泛的实验设置下的真实任务调制功能连接。我们揭示了不同类型的任务设计及其基本限制下表现最佳的方法。重要的是,我们证明即使在通常较低的 fMRI 时间分辨率(2 秒)下,也可以从缓慢的血液动力学波动中恢复出振荡神经元同步的快速(100 毫秒)调制。最后,我们提供了关于任务设计和统计分析的实用建议,以促进任务连接组映射。