Masharipov Ruslan, Knyazeva Irina, Korotkov Alexander, Cherednichenko Denis, Kireev Maxim
N.P. Bechtereva Institute of the Human Brain, Russian Academy of Sciences, St. Petersburg, Russia.
bioRxiv. 2024 Oct 14:2024.01.22.576622. doi: 10.1101/2024.01.22.576622.
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背景,在广泛分布的脑区之间灵活整合信息。静息态功能磁共振成像(fMRI)为大规模内在脑网络组织提供了大量见解,但对于该内在网络组织快速的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推导全脑任务调制功能连接矩阵的金标准。在此,我们进行生物物理逼真模拟,以在广泛的实验设置中控制真实的任务调制功能连接。我们揭示了不同类型任务设计的最佳执行方法及其基本局限性。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,振荡神经元同步的快速(100毫秒)调制也可以从缓慢的血液动力学波动中恢复。最后,我们就任务设计和统计分析提供实用建议,以促进任务连接组映射。