Filligoi G C, Fattorini L
CISB, Centro Interdip. Sistemi Biomedici, Dipartimento INFOCOM, Faculty Engineering, Università La Sapienza, Rome, Italy.
Comput Biomed Res. 1999 Jun;32(3):198-208. doi: 10.1006/cbmr.1998.1501.
Conventional brain maps suffer from severe limitations due to both the spatial blur of potential distributions and the dependence on electrical reference. The surface Laplacian (SL) has been used to deblur movement-related brain macropotentials (MRBM) since it acts as a high-pass spatial filter that reduces the head volume conductor effects. Moreover, the method usually employed to improve the signal-to-noise ratio (SNR) is the well-known synchronized average. However, this method is no longer valid when the object of the study is the sweep-by-sweep variability. In this case, the SNR of original and Laplacian-transformed single-sweep MRBM can be improved by autoregressive with exogenous input (ARX) filtering. In our study, isolated or combined ARX and SL are applied to enhance the spatial distributions of single-sweep MRBM associated with unilateral voluntary self-paced finger movements in humans. It shows that single-sweep brain mappings are more coherent to physiological findings when ARX is first used followed by SL.
由于电位分布的空间模糊以及对电参考的依赖，传统脑图谱存在严重局限性。表面拉普拉斯算子（SL）已被用于对与运动相关的脑宏观电位（MRBM）进行去模糊处理，因为它作为一种高通空间滤波器，可减少头部容积导体效应。此外，通常用于提高信噪比（SNR）的方法是众所周知的同步平均法。然而，当研究对象是逐次扫描的可变性时，这种方法就不再有效了。在这种情况下，可以通过带外生输入的自回归（ARX）滤波来提高原始和拉普拉斯变换后的单次扫描MRBM的SNR。在我们的研究中，应用孤立的或组合的ARX和SL来增强与人类单侧自主自定节奏手指运动相关的单次扫描MRBM的空间分布。结果表明，当先使用ARX然后使用SL时，单次扫描脑图谱与生理学发现更具一致性。
