Loo Sandra K, Lenartowicz Agatha, Makeig Scott
Semel Neuropsychiatric Institute, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Swartz Center for Computational Neuroscience, UCSD, San Diego, CA, USA.
J Child Psychol Psychiatry. 2016 Jan;57(1):4-17. doi: 10.1111/jcpp.12435. Epub 2015 Jun 23.
Electroencephalography (EEG) and related measures have a long and productive history in child psychopathology research and are currently experiencing a renaissance in interest, particularly for use as putative biomarkers.
First, the recent history leading to the use of EEG measures as endophenotypes and biomarkers for disease and treatment response are reviewed. Two key controversies within the area of noninvasive human electrophysiology research are discussed, and problems that currently either function as barriers or provide gateways to progress. First, the differences between the main types of EEG measurements (event-related potentials, quantitative EEG, and time-frequency measures) and how they can contribute collectively to better understanding of cortical dynamics underlying cognition and behavior are highlighted. Second, we focus on the ongoing shift in analytic focus to specific cortical sources and source networks whose dynamics are relevant to the clinical and experimental focus of the study, and the effective increase in source signal-to-noise ratio (SNR) that may be obtained in the process.
Understanding of these issues informs any discussion of current trends in EEG research. We highlight possible ways to evolve our understanding of brain dynamics beyond the apparent contradictions in understanding and modeling EEG activity highlighted by these controversies. Finally, we summarize some promising future directions of EEG biomarker research in child psychopathology.
脑电图(EEG)及相关测量方法在儿童精神病理学研究中有着悠久且卓有成效的历史,目前正经历着兴趣的复兴,特别是作为假定生物标志物的应用。
首先,回顾了脑电图测量作为疾病和治疗反应的内表型及生物标志物的近期发展历程。讨论了无创人类电生理研究领域内的两个关键争议点,以及目前作为进展障碍或进步途径的问题。第一,强调了脑电图测量主要类型(事件相关电位、定量脑电图和时频测量)之间的差异,以及它们如何共同有助于更好地理解认知和行为背后的皮层动力学。第二,我们关注分析重点正在向特定皮层源和源网络的转变,其动力学与研究的临床和实验重点相关,以及在此过程中可能实现的源信号噪声比(SNR)的有效提高。
对这些问题的理解为脑电图研究当前趋势的任何讨论提供了信息。我们强调了一些可能的方法,以超越这些争议所凸显的脑电图活动理解和建模中的明显矛盾,来深化我们对脑动力学的理解。最后,我们总结了儿童精神病理学中脑电图生物标志物研究一些有前景的未来方向。