Simons Samantha, Abasolo Daniel, Sauseng Paul
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:7414-7. doi: 10.1109/EMBC.2015.7320105.
The spurious increase in coherence of electroencephalogram (EEG) signals between distant electrode points has long been understood to be due to volume conduction of the EEG signal. Reducing the volume conduction components of EEG recordings in pre-processing attenuates this. However, the effect of volume conduction on non-linear signal processing of EEG signals is yet to be fully described. This pilot study aimed to investigate the impact of volume conduction on results calculated with a distance based, bivariate form of Lempel-Ziv Complexity (dLZC) by analyzing EEG signals from Alzheimer's disease (AD) patients and healthy age-matched controls with and without pre-processing with Current Source Density (CSD) transformation. Spurious statistically significant differences between AD patients and control's EEG signals seen without CSD pre-processing were not seen with CSD volume conduction mitigation. There was, however, overlap in the region of electrodes which were seen to hold this statistically significant information. These results show that, while previously published findings are still valid, volume conduction mitigation is required to ensure non-linear signal processing methods identify changes in signals only due to the purely local signal alone.
长期以来,人们一直认为,遥远电极点之间脑电图(EEG)信号相干性的虚假增加是由于EEG信号的容积传导所致。在预处理过程中减少EEG记录的容积传导成分可减弱这种情况。然而,容积传导对EEG信号非线性信号处理的影响尚未得到充分描述。这项初步研究旨在通过分析来自阿尔茨海默病(AD)患者和年龄匹配的健康对照的EEG信号,研究容积传导对基于距离的双变量形式的莱姆尔-齐夫复杂度(dLZC)计算结果的影响,这些信号经过和未经过电流源密度(CSD)变换预处理。在未进行CSD预处理时,AD患者和对照的EEG信号之间出现的虚假统计学显著差异,在减轻CSD容积传导后未再出现。然而,在被认为包含这种统计学显著信息的电极区域存在重叠。这些结果表明,虽然先前发表的研究结果仍然有效,但需要减轻容积传导,以确保非线性信号处理方法仅识别仅由纯局部信号引起的信号变化。