【作者】 邝慧；

【导师】 钱卓；

【作者基本信息】 华东师范大学 ， 生理学， 2011， 博士

【摘要】 记忆是如何形成的?这是神经科学的基本问题,也是最终的目的之一。近几十年来,科学家们致力于研究大脑是如何形成记忆的,而其中海马是最受关注的脑区之一。在体多神经记录技术的发展,结合巧妙设计的行为学实验,加上强大的神经计算方法,使得这个领域的研究取得了显著的成果,初步发现了海马CA1区对外部情景事件编码并形成记忆的基本机制。海马神经元的种类并不是单一的,除了主要的兴奋性细胞之外,还有种类繁多的中间神经元。组织学研究已经发现的海马的中间神经元至少有20多种。各种各样的神经元在海马组成复杂的微电路,通过放电活动相互协调,从而实现信息的提取和整合,因此在体同时监测多个锥体神经元和中间神经元的放电活动,研究他们之间的互相作用就变得十分必要。至今对于海马不同种类神经元的电生理研究还局限于在离体脑片和在体麻醉动物上记录一到几个神经元。而在体电生理记录技术可以实现网络水平的研究,但是现在对海马不同种类神经元的在体放电的动态模式研究还很少。未解决的重要的问题还有,锥体神经元和中间神经元在海马对情境事件的编码中,功能是否相同?各自有什么特征?不同的中间神经元之间又有什么差异?这些问题的解决将对进一步了解大脑神经网络编码的机制有重要的作用。本论文第一章和第二章分别分析了小鼠在正常行为活动下和在氯胺酮麻醉状态下神经元的基本放电特征,对海马CA1区神经元进行分类,并讨论了在氯胺酮作用下神经网络的动态变化和神经元之间的相互关系；第三章我们讨论了在惊吓刺激事件中,不同神经元类型的反应放电模式特点；在第四章,利用MDA方法(Multiple Discriminate Analysis)研究海马神经元网络惊吓刺激事件的编码,进而探讨各种神经元在情景记忆编码中的功能。一、小鼠海马CA1区神经元的基本放电特征及神经元分类我们应用多通道微电极记录技术在小鼠海马CA1区同时记录了大量神经元的放电活动和位置场电位,并对小鼠海马神经元的基本放电特征进行分析。结果显示,海马神经元可以根据放电波形、放电时程、放电频率、和自相关直方图的特征主要分为两大类：锥体神经元和中间神经元。通过进一步对神经元在动物不同行为状态及大脑局部场电位的Theta节律振荡和Ripple节律振荡中特征的观察和计算,我们发现所记录到的中间神经元可以进一步细分为以下几类：其中第一到四种根据离体脑片和麻醉动物的实验结果,分别可以判断为篮细胞(Basket cells)、双层细胞(Bistratified cells)、轴突-轴突细胞(Axo-axonic cells)也叫做灯形细胞(Chandelier cells)、和O-LM细胞,此外还有第五种‘’Bursty"细胞和其他类型中间神经元。中间神经元的多样性反映了大脑神经网络组成的高度复杂性。二、氯胺酮诱导的麻醉状态下海马CA1脑区各种细胞群的时序动态特征氯胺酮(Ketamine,也译作克它明)是一种常用的分离麻醉药(Dissociative anesthetic),一部分病人在麻醉恢复期会出现一些精神症状,如精神错乱、幻觉等,并且可以导致记忆的缺失。我们同步记录了大量的的锥体神经元和多种中间神经元,对它们在氯胺酮引导的无意识状态下的动态变化进行分析,并且与正常意识状态下,如清醒休息、奔跑和睡眠等状态下的放电模式相比较。分析结果发现,氯胺酮可以诱导海马锥体神经元呈现出一种显著的同步放电模式,同时不同的中间神经元的放电也呈现出不同节律的动态特性。我们再用交叉相关性方法分析中间神经元放电与神经元群放电(Joint activity)的关系,结果发现在氯胺酮作用下,其中两类神经元,篮细胞(Basket cells)和双层细胞(Bistratified cells),与锥体神经元群放电呈现同步化,而另几类中间神经元,包括轴突-轴突细胞(Axo-axonic cells)也叫做灯形细胞(Chandelier cells)、O-LM细胞和其他类型的中间神经元,则与锥体神经元群放电呈现不同的时序关系。我们的结果提示在氯胺酮引起的无意识麻醉状态中,海马CAl区的主要神经元(锥体神经元)在不同种类的中间神经元的协同作用下进行同步放电。这些节律性的动态放电模式可能反映了海马CA1微电路的组成特性及内在的时序关系。这为研究非正常的认知状态甚至精神分裂症提供了一个途径。三、小鼠海马CA1区不同种类神经元群对惊吓刺激反应的差异为了在网络水平上研究在大脑编码外界环境情景信息中CA1锥体神经元和不同种类中间神经元的作用规律,我们设计了一系列简单有效的惊吓刺激行为学实验,可以诱发大量神经元的反应活动。实验结果显示,锥体神经元和中间神经元在对惊吓刺激的反应上存在显著差异。大部分锥体神经元对惊吓刺激没有反应,而绝大多数中间神经元对惊吓刺激有反应。有反应的锥体神经元大多数只对单一的惊吓刺激有反应,而中间神经元倾向于对多个不同的事件都有反应。并且锥体神经元对事件反应的平均潜伏期长于中间神经元,而细胞的反应时程却比中间神经元短。在中间神经元的不同种类中,所有篮细胞和双层细胞都是惊吓刺激反应细胞,并且大多对两个以上事件有反应,与其他种类的中间神经元相比,对刺激事件反应的潜伏期较短,反应时程较长。这些结果提示,海马CA1区的锥体神经元和中间神经元都参与大脑对惊吓刺激事件的编码过程,并且不同种类的CA1神经元群在这个过程中的的作用具有差异性。四、海马CA1区不同神经元群在编码惊吓刺激事件中的不同作用科学家们公认神经的编码是群体神经元共同协调的结果,那么仅仅对单个或者两两神经元对之间的放电规律的分析方法就不足以研究神经网络水平的编码规律。因此,我们采用MDA方法,将同时记录到的大量海马CA1区神经元在惊吓刺激时的放电频率改变,投射到低维的解码空间,成功的将不同的事件聚类分离,模拟了海马神经元群对不同事件的模式识别功能。我们发现,海马神经元群以神经元簇(Neural clique)为功能单位,呈现层级式结构,其中Specific responsive clique(只对一种惊吓刺激有选择性反应的神经元群)对具体情景事件的在MDA空间中的聚类分离效果贡献最大,而General clique(对四种惊吓刺激时间都有反应的神经元群)最弱。而锥体神经元与中间神经元相比使情景事件在MDA空间中的聚类分离效果较好,中间神经元中篮细胞和双层细胞较差。这与锥体神经元大多属于Specific responsive clique,而中间神经元多为sub-general或general clique的结果相一致。这些结果提示锥体神经元在提取不同事件的差异性特征中起重要作用,而中间神经元则可能主要负责编码事件之间的共同特征。本实验使用在体多通道微电极记录技术,在体记录自由活动小鼠海马CA1区神经元活动,分析各种不同神经元的放电特征及对惊吓事件的反应特征,并运用MDA方法研究海马神经网络对惊吓事件的编码,探讨了各种神经元在情景记忆编码中的功能和大脑微电路信息编码的机制。更多还原

【Abstract】 How do memories form? This is one of the principle goals in neuroscience. For decades, neuroscientists have attempted to unravel how the brain makes memories. The hippocampus is one of the brain regions has attracted considerable interest among neuroscientists. By combining a set of novel experiments with sophisticated mathematical analyses and an ability to record simultaneously the activity of hundreds of neurons in free behaving mice, scientists have discovered some basic mechanisms the brain uses to draw vital information from experiences and turn that information into memories.The hippocampus has not only principle excitatory neurons, but also varies inhibitory interneurons. There are more than 20 types of interneurons were indentified in hippocampus. Given the fact that pyramidal cells and diverse interneurons compose the intricate hippocampal circuits and work together to produce cooperative network properties during the information exaction and integration, it would be highly useful to study the firing patterns of both pyramidal cells and interneurons and their possible interactions in the simultaneously recorded population. Much of current knowledge has been obtained from the studies of in vitro brain slices or anesthesia animals. While with large scale in vivo recording techniques, network level studies can be performed, but little has been done regarding the differential roles of distinct neuron types.Important questions remain as to whether and how various interneurons interact with pyramidal cells and contribute to the dynamic patterns of CA1 network during episodic events. The answers to these questions will contribute to further understanding of the mechanisms underlying brain coding. There are four main topics of this thesis:1, Discharge properties of distinct hippocampal CA1 cell populations; 2, Temporal dynamics of distinct CA1 cell populations during unconscious state induced by Ketamine; 3, Diverse responses of distinct CA1 cell populations to episodic startle stimuli; 4, Differential roles of diverse CA1 cell populations in encoding real-time representation of episodic experiences.1. Discharge properties of distinct hippocampal CA1 cell populations Using large-scale in vivo neural recording techniques, we simultaneously recorded the spike activities of multiple neurons as well as local field potentials from the CA1 region of the mouse hippocampus. Our analyses revealed the basic firing patterns of CA1 neural ensembles. Principal excitatory units (putative pyramidal cells) and inhibitory units (putative interneurons) were discriminated based on spike durations, firing rates, and autocorrelation functions. To further define interneurons, we not only used the action potential waveform but also the timing of the spike activities of inhibitory units during theta oscillations and sharp-wave associate ripples. We classified interneurons into five types, namely, Basket cells, Bistratified cells, Axo-axonic cells (also called Chandelier cells), O-LM cells and Type 5 ("Bursty") cells. The neural diversity of hippocampal cells indicates the complexity of neural network in the brain.2. Temporal dynamics of distinct CA1 cell populations during unconscious state induced by KetamineKetamine is a widely used dissociative anesthetic which can induce some psychotic-like symptoms and memory deficits in some patients during the post-operative period. To understand its effects on neural population dynamics in the brain, we employed large-scale in vivo ensemble recording techniques to monitor the activity patterns of simultaneously recorded hippocampal CA1 pyramidal cells and various interneurons during several conscious and unconscious states such as awake rest, running, slow wave sleep, and ketamine-induced anesthesia. Our analyses reveal that ketamine induces distinct oscillatory dynamics not only in pyramidal cells but also in at least seven different types of CAl interneurons including putative basket cells, Chandelier cells, bistratified cells, and O-LM cells. These emergent unique oscillatory dynamics may very well reflect the intrinsic temporal relationships within the CA1 circuit. It is conceivable that systematic characterization of network dynamics may eventually lead to better understanding of how ketamine induces unconsciousness and consequently alters the conscious mind.3. Diverse responses of distinct CA1 cell populations to episodic startle stimuliTo characterize the firing patterns of distinct CA1 neural populations during hippocampal network-encoding episodic information, we used a set of simple but effective startling episodic stimuli, which were able to evoke robust neural response in hippocampus. Our results show diverse responses of distinct CAl neural populations to startling episodic stimuli. More than half of recorded pyramidal cells are not responsive to any of the startle events. And most of the responsive pyramidal cells are specific responsive to only one of the stimuli. Unlike pyramidal cells, most interneurons are sub-general and general episodic units, that is, they usually respond to more than one startle episodic stimuli. On the other hand, the average response latencies of pyramidal cells are longer than interneurons, while the response durations are shorter than interneurons. There is diversity among varies interneurons on the response selectivity. All of the basket cells and bistratified cells are responsive to at least one of the startling episodes. Our results suggest that both pyramidal cells and interneurons are evolved in the brain representations of episodic events, and the responses to the episodic stimuli are diverse among distinct neural types.4. Differential roles of diverse CA1 cell populations in encoding real-time representation of episodic experiencesThe analyses based on one neuron or pair-wise analyses are not efficient to deal with the network level neural data set. To provide an intuitive solution that would facilitate a search for the relevant network-encoding patterns, we employed MDA (Multiple Discriminate Analysis) to compute a highly informative low-dimensional subspace among the firing patterns of simultaneously recorded neurons. We identified that neural cliques, act as network-level functional coding units, and are organized in a categorical and hierarchical manner. The specific responsive clique contributes the most to the clustering and separation of event ellipsoids in the MDA subspace. Most significantly, the clustering and separation of distinct startling episodic stimuli in the MDA subspace trained by the pyramidal cell population are better than using interneurons. This fits well with the fact that most responsive pyramidal cells are event-specific units, and interneurons are likely to be in sub-general and general clique. These result indicates that pyramidal cells are more engaged in encoding the specific episodic event, while the interneurons are likely contribute more in the generalization of similar events.By taking the advantage of our large-scale in-vivo neural recording technique, we are allowed to monitor many pyramidal cells and interneurons at the same time. We analyzed the characteristics patterns of distinct neural populations during startling episodic stimuli. Then we performed MDA to decode the hippocampal network-encoding patterns, and find the differential roles of pyramidal cells and diverse interneurons in encoding real-time representation of episodic experiences.更多还原