Department of Orthopaedics and Traumatology, The University of Hong Kong, Hong Kong, China.
Clin Neurophysiol. 2011 Jul;122(7):1429-39. doi: 10.1016/j.clinph.2010.12.052. Epub 2011 Feb 4.
To develop an effective approach for enhancing the signal-to-noise ratio (SNR) and identifying single-trial short-latency somatosensory evoked potentials (SEPs) from multi-channel electroencephalography (EEG).
128-channel SEPs elicited by electrical stimuli of the left posterior tibial nerve were recorded from 11 healthy subjects. Probabilistic independent component analysis (PICA) was used as a spatial filter to isolate SEP-related independent components (ICs), and wavelet filtering was used as a time-frequency filter to further enhance the SNR of single-trial SEPs.
SEP-related ICs, identified using PICA, showed typical patterns of cortical SEP complex (P39-N50-P60) and scalp topography (centrally distributed with the spatial peak located near vertex). In addition, wavelet filtering significantly enhanced the SNR of single-trial SEPs (p=0.001).
Combining PICA and wavelet filtering offers a space-time-frequency filter that can be used to enhance the SNR of single-trial SEPs greatly, thus providing a reliable estimation of single-trial SEPs.
This method can be used to detect single-trial SEPs and other types of evoked potentials (EPs) in various sensory modalities, thus facilitating the exploration of single-trial dynamics between EPs, behavioural variables (e.g., intensity of perception), as well as abnormalities in intraoperative neurophysiological monitoring.
开发一种有效的方法，以提高信噪比（SNR）并从多通道脑电图（EEG）中识别单次短潜伏期体感诱发电位（SEP）。
从 11 名健康受试者记录了由左后胫神经电刺激引发的 128 通道 SEP。概率独立成分分析（PICA）用作空间滤波器以分离 SEP 相关的独立成分（ICs），并且小波滤波用作时频滤波器以进一步提高单次 SEP 的 SNR。
使用 PICA 识别的 SEP 相关 IC 显示出皮质 SEP 复合波（P39-N50-P60）和头皮地形图（中央分布，空间峰值位于顶点附近）的典型模式。此外，小波滤波显著提高了单次 SEP 的 SNR（p=0.001）。
组合使用 PICA 和小波滤波提供了一种时空滤波器，可大大提高单次 SEP 的 SNR，从而提供对单次 SEP 的可靠估计。
该方法可用于检测各种感觉模式中的单次 SEP 和其他类型的诱发电位（EP），从而促进 EP 之间、行为变量（例如感知强度）以及术中神经生理监测中的异常之间的单次动态的研究。
