University of Illinois, Department of Bioengineering, Medical Scientist Training Program, Chicago, IL, USA.
J Neurosci Methods. 2010 Jan 30;186(1):42-51. doi: 10.1016/j.jneumeth.2009.10.023. Epub 2009 Nov 10.
Neuronal populations throughout the brain achieve levels of synchronous electrophysiological activity as a consequence of both normal brain function as well as during pathological states such as in epileptic seizures. Understanding this synchrony and being able to quantitatively assess the dynamics with which neuronal oscillators across the brain couple their activity is a critical component toward decoding such complex behavior. Commonly applied techniques to resolve relationships between oscillators typically make assumptions of linearity and stationarity that are likely not to be valid for complex neural signals. In this study, intracranial electroencephalographic activity was recorded bilaterally in both hippocampi and in anteromedial thalamus of rat under normal conditions and during hypersynchronous seizure activity induced by focal injection of the epileptogenic agent kainic acid. Nonlinear oscillators were first extracted using empirical mode decomposition. The technique of eigenvalue decomposition was used to assess global phase synchrony of the highest energy oscillators. The Hilbert analytical technique was then used to measure instantaneous phase synchrony of these oscillators as they evolved in time. To test the reliability of this method, we first applied it to a system of two coupled Rössler attractors under varying levels of coupling with small frequency mismatch. The application of these analytical techniques to intracranially recorded brain signals provides a means for assessing how complex oscillatory behavior in the brain evolves and changes during both normal activity and as a consequence of diseased states without making restrictive and possibly erroneous assumptions of the linearity and stationarity of the underlying oscillatory activity.
整个大脑中的神经元群体由于正常的大脑功能以及在病理性状态（如癫痫发作）下，都会达到同步电生理活动的水平。理解这种同步性，并能够定量评估大脑中神经元振荡器之间耦合其活动的动态，是解码这种复杂行为的关键组成部分。通常用于解析振荡器之间关系的技术通常假设线性和稳定性，而对于复杂的神经信号来说，这些假设可能不成立。在这项研究中，在正常条件下和通过局部注射致痫剂海人酸诱导的超同步癫痫发作期间，在双侧海马体和大鼠前内侧丘脑记录了颅内脑电图活动。首先使用经验模态分解提取非线性振荡器。特征值分解技术用于评估最高能量振荡器的全局相位同步。然后，使用希尔伯特分析技术测量这些振荡器随时间演变的瞬时相位同步。为了测试这种方法的可靠性，我们首先将其应用于两个耦合的 Rössler 吸引子系统，在不同的耦合水平下，频率略有不匹配。将这些分析技术应用于颅内记录的脑信号提供了一种评估大脑中复杂振荡行为如何在正常活动期间以及在疾病状态下演变和变化的方法，而无需对潜在的振荡活动的线性和稳定性做出限制性和可能错误的假设。
