神经振荡在认知功能与分子机制之间桥梁作用的研究

Our previous studies showed that the synchronization of neural oscillation could facilitate neuronal synaptic plasticity and neural communication, and futher elucidated the underlying molecular biological basis for such an phenomenon. It is well known that the mechanism underlying the generation of neuronal oscillations is closely associated with excitatory or inhibitory neurotransmitters and receptors at the molecular level. Meanwhile, there have been lots of molecular biological mechanism studies, which are realted to cognitive dysfuntions or impairments. Therefore, an issue has been raised if the changes of cognitive function and underlying molecular biological basis are closely associated with the pattern of neural oscillations. In other wors, could neural oscillations be as a bridge between cognition and its molecular biological mechanisms? Accordingly, several key steps are going to be peformed, which include establishing a rat or mouse model of cognitive impairment, recording the electrophysiological signals of neural activities in both awake and anesthetized states, analyzing the molecular biological mechanisms (micro level) of cognitive dysfunctions (macro level), examining the pattern of neural oscillations (mesoscopic level), and then exploring deeply on the potential relationships between any pair of them. It needs to clarify how and what the alterartions of neural oscillatory pattern are induced by cognitive dysfunctions, which are in connect with certain molecular mechanisms. Furthermore, the novel algorithms for analyzing the patterns of neural oscillatory need to be developed, especially for measuring phase-amplitude coupling (PAC) and phase-phase coupling (PPC). We certainly believe that the analysis of neural oscillation could be serves as the interface between cognition and its molecular mechanisms. The resarch results can be applied in the various aspects of, brain-computer interface, aerospace human factors engineering, brain-inspired computing, neurological inhabilitation and so on.

我们前期研究报道神经振荡同步增强突触可塑性，提高脑内信息交流水平，并阐明了其分子机理。神经振荡的产生机制与其分子层面的兴奋性/抑制性神经递质及受体密切相关，而大脑认知功能障碍或损伤的分子机制研究也有报道。那么，通过揭示神经振荡活动模式来表征认知功能并阐明其分子机理，能否使神经振荡成为认知功能与分子机制之间的桥梁呢？为此，建立不同的认知功能障碍的大（小）鼠模型；记录麻醉与清醒状态的神经活动；分析认知功能（宏观）变化的分子生物学机制（微观）并进行神经振荡计算（介观），深入探究三者之间的相关性，厘清认知功能异常导致的振荡模式改变，后者又对应那些分子层面的响应。继续发展神经振荡模式的分析算法，如相位-幅值与相位-相位耦合新算法，及各算法之间相关性的探讨。神经振荡计算将成为探讨分子层面的改变如何影响认知功能的重要中间环节，研究成果可直接应用于脑机接口、航天人因工程、类脑计算、神经康复等领域。

神经振荡的产生机制与其分子层面的兴奋性/抑制性神经递质及受体密切相关，而大脑认知功能障碍或损伤的分子机制研究也有报道。那么，通过揭示神经振荡活动模式来编码认知功能并阐明其分子机理，能否使神经振荡成为认知功能与分子机制之间的桥梁呢？为此，我们建立了多种类型动物模型，如Notch1基因敲低小鼠模型、U1snRNA过表的模型小鼠、精氨酸加压素（AVP）主要受体V1a调控的2VO大鼠、产前应激（PS）模型鼠和模拟微重力模型小鼠；在海马脑区的不同神经通路采集了局部场电位并进行神经振荡分析。进一步结合认知行为学实验和相关分子生物学实验。计算与实验结果均指向一点，即认知功能-神经振荡-分子机理之间存在密切的相关性，从而为我们提出的神经振荡是认知功能与分子生物学机制之间的桥梁的学术观点提供了关键实验证据。同时还提出了一种新的用于检测神经元相位幅值耦合的算法，即排列互信息熵（PMI），并与其它两个常用的PAC算法，即平均向量长度法（MVL）和调节指数法（MI）进行了比较。初步建立了基于EEG/LFP的集各种神经振荡分析算法的脑电信号计算平台。此外，研究结果还可以为深度神经网络新结构提供思路和灵感。