Sielużycki Cezary, Kordowski Paweł
Special Lab Non-invasive Brain Imaging, Leibniz Institute for Neurobiology, Brenneckestr, 6, 39118 Magdeburg, Germany.
Biomed Eng Online. 2014 Jun 16;13:75. doi: 10.1186/1475-925X-13-75.
We propose a mathematical model for multichannel assessment of the trial-to-trial variability of auditory evoked brain responses in magnetoencephalography (MEG).
Following the work of de Munck et al., our approach is based on the maximum likelihood estimation and involves an approximation of the spatio-temporal covariance of the contaminating background noise by means of the Kronecker product of its spatial and temporal covariance matrices. Extending the work of de Munck et al., where the trial-to-trial variability of the responses was considered identical to all channels, we evaluate it for each individual channel.
Simulations with two equivalent current dipoles (ECDs) with different trial-to-trial variability, one seeded in each of the auditory cortices, were used to study the applicability of the proposed methodology on the sensor level and revealed spatial selectivity of the trial-to-trial estimates. In addition, we simulated a scenario with neighboring ECDs, to show limitations of the method. We also present an illustrative example of the application of this methodology to real MEG data taken from an auditory experimental paradigm, where we found hemispheric lateralization of the habituation effect to multiple stimulus presentation.
The proposed algorithm is capable of reconstructing lateralization effects of the trial-to-trial variability of evoked responses, i.e. when an ECD of only one hemisphere habituates, whereas the activity of the other hemisphere is not subject to habituation. Hence, it may be a useful tool in paradigms that assume lateralization effects, like, e.g., those involving language processing.
我们提出了一种用于多通道评估脑磁图（MEG）中听觉诱发脑反应逐次试验变异性的数学模型。
遵循德蒙克等人的工作，我们的方法基于最大似然估计，通过污染背景噪声的空间和时间协方差矩阵的克罗内克积来近似其时空协方差。扩展德蒙克等人的工作，其中反应的逐次试验变异性被认为对所有通道都是相同的，我们对每个单独的通道进行评估。
使用两个具有不同逐次试验变异性的等效电流偶极子（ECD）进行模拟，每个听觉皮层中植入一个，以研究所提出方法在传感器层面的适用性，并揭示逐次试验估计的空间选择性。此外，我们模拟了相邻ECD的场景，以展示该方法的局限性。我们还给出了该方法应用于从听觉实验范式获取的真实MEG数据的示例，在该示例中我们发现对多个刺激呈现的习惯化效应存在半球侧化。
所提出的算法能够重建诱发反应逐次试验变异性的侧化效应，即当只有一个半球的ECD发生习惯化，而另一个半球的活动未发生习惯化时。因此，它可能是在假设侧化效应的范式中，例如涉及语言处理的范式中，一种有用的工具。
