An electrophysiological validation of stochastic DCM for fMRI.
An electrophysiological validation of stochastic DCM for fMRI.
复制标题
DOI：
10.3389/fncom.2012.00103
复制
发表时间：
2012
影响因子：
3.2
通讯作者：
Stephan KE
中科院分区：
文献类型：
--
作者：
Daunizeau J;Lemieux L;Vaudano AE;Friston KJ;Stephan KE
在这篇文章中，我们评估了随机动态因果模型（sDCM）的功能磁共振成像（fMRI）数据的预测有效性，在其解释同时采集的脑电图（EEG）信号的频谱变化的能力。我们首先回顾Kilner等人提出的启发式模型，这表明fMRI激活与EEG信号的频率调制（而不是频带内的幅度调制）相关。我们提出了一个定量推导的基本思想，基于神经领域制定的皮层活动。简而言之，密集的横向连接引起时间尺度的分离，由此快（和高空间频率）模式被慢（低空间频率）模式奴役。这种从属效应使得快模式（主导EEG信号）的频谱由慢模式（主导fMRI信号）的振幅控制。然后，我们使用联合经验脑电图功能磁共振成像数据，获得癫痫患者，以证明电生理基础的神经波动推断sDCM功能磁共振成像。
In this note, we assess the predictive validity of stochastic dynamic causal modeling (sDCM) of functional magnetic resonance imaging (fMRI) data, in terms of its ability to explain changes in the frequency spectrum of concurrently acquired electroencephalography (EEG) signal. We first revisit the heuristic model proposed in Kilner et al., which suggests that fMRI activation is associated with a frequency modulation of the EEG signal (rather than an amplitude modulation within frequency bands). We propose a quantitative derivation of the underlying idea, based upon a neural field formulation of cortical activity. In brief, dense lateral connections induce a separation of time scales, whereby fast (and high spatial frequency) modes are enslaved by slow (low spatial frequency) modes. This slaving effect is such that the frequency spectrum of fast modes (which dominate EEG signals) is controlled by the amplitude of slow modes (which dominate fMRI signals). We then use conjoint empirical EEG-fMRI data—acquired in epilepsy patients—to demonstrate the electrophysiological underpinning of neural fluctuations inferred from sDCM for fMRI.