Wang J Z, Williamson S J, Kaufman L
Department of Physics, New York University, New York, USA.
Brain Topogr. 1995 Spring;7(3):193-200. doi: 10.1007/BF01202378.
Prior work proved that it is possible to find a unique solution to the problem of defining the configuration of electric current underlying observed extracranial magnetic fields, if sufficient priori knowledge of the source configuration is available. This minimum-norm least-squares (MNLS) inverse solution for a magnetic source image (MSI) is extended here to include temporal as well as spatial parameters of the underlying current pattern. This capitalizes on the temporal resolution of magnetoencephalography (MEG), which is on the order of milliseconds. Other forms of functional brain imaging are far less sensitive to the rate of change of states of the brain. Influences on the quality of the resulting MSI by measurement noise and errors in determining the image surface are characterized. A new technique for reducing noise in the inverse problem is developed by taking into consideration the spatial and time-dependence of the noise detected by the sensors. This new approach to regularization reduces the contribution from noisy measurements to the inverse calculation, and therefore improves the stability of the inverse.
先前的研究证明，如果有足够的源配置先验知识，就有可能找到一个唯一的解决方案，来确定观察到的颅外磁场背后的电流配置问题。这里将这种用于磁源成像（MSI）的最小范数最小二乘（MNLS）逆解进行扩展，以纳入潜在电流模式的时间以及空间参数。这利用了脑磁图（MEG）的时间分辨率，其时间分辨率在毫秒量级。其他形式的功能性脑成像对大脑状态变化速率的敏感度要低得多。研究了测量噪声和确定图像表面时的误差对所得MSI质量的影响。通过考虑传感器检测到的噪声的空间和时间依赖性，开发了一种用于减少逆问题中噪声的新技术。这种新的正则化方法减少了噪声测量对逆计算的贡献，从而提高了逆解的稳定性。
