海马CA1区锥体神经元和多种中间神经元在情景事件编码中的作用
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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。
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 Ketamine
Ketamine 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 stimuli
To 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 experiences
The 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.
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。
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 Ketamine
Ketamine 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 stimuli
To 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 experiences
The 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.
引文
1. Buzsaki G, Grastyan E, Kellenyi L, Czopf J (1979) Dynamic phase-shifts between theta generators in the rat hippocampus. Acta Physiol Acad Sci Hung 53:41-45.
2. Buzsaki G, Haubenreiser J, Grastyan E, Czopf J, Kellenyi L (1981) Hippocampal slow wave activity during appetitive and aversive conditioning in the cat. Electroencephalogr Clin Neurophysiol 51:276-290.
3. Buzsaki G, Leung LW, Vanderwolf CH (1983) Cellular bases of hippocampal EEG in the behaving rat. Brain Res 287:139-171.
4. Wilson MA, McNaughton BL (1994) Reactivation of hippocampal ensemble memories during sleep. Science 265:676-679.
5. Skaggs WE, McNaughton BL (1996) Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience. Science 271:1870-1873.
6. Kudrimoti HS, Barnes CA, McNaughton BL (1999) Reactivation of hippocampal cell assemblies:effects of behavioral state, experience, and EEG dynamics. J Neurosci 19:4090-4101.
7. Louie K, Wilson MA (2001) Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep. Neuron 29:145-156.
8. Lee AK, Wilson MA (2002) Memory of sequential experience in the hippocampus during slow wave sleep. Neuron 36:1183-1194.
9. Csicsvari J, Hirase H, Czurko A, Mamiya A, Buzsaki G (1999) Oscillatory coupling of hippocampal pyramidal cells and interneurons in the behaving Rat. J Neurosci 19:274-287.
10. Schmidt EM (1999) Electrodes for many single neuron recordings. In:Nicolelis MA, editor. Methods for neural ensemble recordings:CRC Press. pp.1-23.
11. McNaughton BL, O'Keefe J, Barnes CA (1983) The stereotrode:a new technique for simultaneous isolation of several single units in the central nervous system from multiple unit records. J Neurosci Methods 8:391-397.
12. Gray CM, Maldonado PE, Wilson M, McNaughton B (1995) Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. J Neurosci Methods 63:43-54.
13. Wilson MA, McNaughton BL (1993) Dynamics of the hippocampal ensemble code for space. Science 261:1055-1058.
14. Hoffman KL, McNaughton BL (2002) Coordinated reactivation of distributed memory traces in primate neocortex. Science 297:2070-2073.
15. Wills TJ, Lever C, Cacucci F, Burgess N, O'Keefe J (2005) Attractor dynamics in the hippocampal representation of the local environment. Science 308:873-876.
16. Lin L, Osan R, Shoham S, Jin W, Zuo W, et al. (2005) Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus. Proc Natl Acad Sci U S A 102:6125-6130.
17. Lin L, Chen G, Xie K, Zaia KA, Zhang S, et al. (2006) Large-scale neural ensemble recording in the brains of freely behaving mice. J Neurosci Methods 155:28-38.
18. Scoville WB, Milner B (1957) Loss of recent memory after bilateral hippocampal lesions. J Neurol Neurosurg Psychiatry 20:11-21.
19. Squire LR (1987) Memory and brain. New York; Oxford:Oxford University Press. xii,315 p. p.
20. Tsien JZ, Huerta PT, Tonegawa S (1996) The essential role of hippocampal CA1 NMDA receptor-dependent synaptic plasticity in spatial memory. Cell 87:1327-1338.
21. Sara SJ (2000) Retrieval and reconsolidation:toward a neurobiology of remembering. Learn Mem 7:73-84.
22. Cohen NJ, Eichenbaum H (1993) Memory, amnesia, and the hippocampal system. Cambridge, Mass.:MIT Press. xii,330 p. p.
23. O'Keefe JM, Nadel L (1978) The hippocampus as a cognitive map. Oxford
New York:Clarendon Press;
Oxford University Press. xiv,570 p. p.
24. Disterhoft JF, Coulter DA, Alkon DL (1986) Conditioning-specific membrane changes of rabbit hippocampal neurons measured in vitro. Proc Natl Acad Sci U S A 83: 2733-2737.
25. Fenton AA, Muller RU (1998) Place cell discharge is extremely variable during individual passes of the rat through the firing field. Proc Natl Acad Sci U S A 95:3182-3187.
26. Eichenbaum H, Dudchenko P, Wood E, Shapiro M, Tanila H (1999) The hippocampus, memory, and place cells:is it spatial memory or a memory space? Neuron 23: 209-226.
27. Leutgeb S, Mizumori SJ (1999) Excitotoxic septal lesions result in spatial memory deficits and altered flexibility of hippocampal single-unit representations. J Neurosci 19: 6661-6672.
28. Wirth S, Yanike M, Frank LM, Smith AC, Brown EN, et al. (2003) Single neurons in the monkey hippocampus and learning of new associations. Science 300:1578-1581.
29. Thompson RF (2005) In search of memory traces. Annu Rev Psychol 56:1-23.
30. Klausberger T, Magill PJ, Marton LF, Roberts JD, Cobden PM, et al. (2003) Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421:844-848.
31. Klausberger T, Marton LF, Baude A, Roberts JD, Magill PJ, et al. (2004) Spike timing of dendrite-targeting bistratified cells during hippocampal network oscillations in vivo. Nat Neurosci 7:41-47.
32. Klausberger T, Marton LF, O'Neill J, Huck JH, Dalezios Y, et al. (2005) Complementary roles of cholecystokinin- and parvalbumin-expressing GABAergic neurons in hippocampal network oscillations. J Neurosci 25:9782-9793.
33. Somogyi P, Klausberger T (2005) Defined types of cortical interneurone structure space and spike timing in the hippocampus. J Physiol 562:9-26.
34. Jinno S, Klausberger T, Marton LF, Dalezios Y, Roberts JD, et al. (2007) Neuronal diversity in GABAergic long-range projections from the hippocampus. J Neurosci 27:8790-8804.
35. Tukker JJ, Fuentealba P, Hartwich K, Somogyi P, Klausberger T (2007) Cell type-specific tuning of hippocampal interneuron firing during gamma oscillations in vivo. J Neurosci 27:8184-8189.
36. Fuentealba P, Begum R, Capogna M, Jinno S, Marton LF, et al. (2008) Ivy cells:a population of nitric-oxide-producing, slow-spiking GABAergic neurons and their involvement in hippocampal network activity. Neuron 57:917-929.
37. Klausberger T, Somogyi P (2008) Neuronal diversity and temporal dynamics:the unity of hippocampal circuit operations. Science 321:53-57.
38. Sirota A, Montgomery S, Fujisawa S, Isomura Y, Zugaro M, et al. (2008) Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 60:683-697.
39. Hafting T, Fyhn M, Molden S, Moser MB, Moser El (2005) Microstructure of a spatial map in the entorhinal cortex. Nature 436:801-806.
40. Middleton S, Jalics J, Kispersky T, Lebeau FE, Roopun AK, et al. (2008) NMDA receptor-dependent switching between different gamma rhythm-generating microcircuits in entorhinal cortex. Proc Natl Acad Sci U S A 105:18572-18577.
41. Moser EI, Moser MB (2008) A metric for space. Hippocampus 18:1142-1156.
42. Cutsuridis V, Wennekers T (2009) Hippocampus, microcircuits and associative memory. Neural Netw 22:1120-1128.
43. Fox SE, Ranck JB, Jr. (1981) Electrophysiological characteristics of hippocampal complex-spike cells and theta cells. Exp Brain Res 41:399-410.
44. Ranck JB, Jr. (1973) Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. Ⅰ. Behavioral correlates and firing repertoires. Exp Neurol 41: 461-531.
45. Buzsaki G, Rappelsberger P, Kellenyi L (1985) Depth profiles of hippocampal rhythmic slow activity ('theta rhythm') depend on behaviour. Electroencephalogr Clin Neurophysiol 61:77-88.
46. Alonso A, Garcia-Austt E (1987) Neuronal sources of theta rhythm in the entorhinal cortex of the rat. Ⅰ. Laminar distribution of theta field potentials. Exp Brain Res 67:493-501.
47. Buzsaki G, Buhl DL, Harris KD, Csicsvari J, Czeh B, et al. (2003) Hippocampal network patterns of activity in the mouse. Neuroscience 116:201-211.
48. Chen G, Wang LP, Tsien JZ (2009) Neural population-level memory traces in the mouse hippocampus. PLoS One 4:e8256.
49. Buzsaki G, Horvath Z, Urioste R, Hetke J, Wise K (1992) High-frequency network oscillation in the hippocampus. Science 256:1025-1027.
50. Lin L, Osan R, Tsien JZ (2006) Organizing principles of real-time memory encoding: neural clique assemblies and universal neural codes. Trends Neurosci 29:48-57.
51. Tsien JZ (2007) The memory code. Researchers are closing in on the rules that the brain uses to lay down memories. Discovery of this memory code could lead to the design of smarter computers and robots and even to new ways to peer into the human mind. Sci Am 297:52-59.
52. Wang H, Hu Y, Tsien JZ (2006) Molecular and systems mechanisms of memory consolidation and storage. Prog Neurobiol 79:123-135.
53. Wang H, Feng R, Phillip Wang L, Li F, Cao X, et al. (2008) CaMKII activation state underlies synaptic labile phase of LTP and short-term memory formation. Curr Biol 18: 1546-1554.
54. Cao X, Wang H, Mei B, An S, Yin L, et al. (2008) Inducible and selective erasure of memories in the mouse brain via chemical-genetic manipulation. Neuron 60:353-366.
55. McEchron MD, Weible AP, Disterhoft JF (2001) Aging and learning-specific changes in single-neuron activity in CA1 hippocampus during rabbit trace eyeblink conditioning. J Neurophysiol 86:1839-1857.
56. Moita MA, Rosis S, Zhou Y, LeDoux JE, Blair HT (2003) Hippocampal place cells acquire location-specific responses to the conditioned stimulus during auditory fear conditioning. Neuron 37:485-497.
57. Moita MA, Rosis S, Zhou Y, LeDoux JE, Blair HT (2004) Putting fear in its place: remapping of hippocampal place cells during fear conditioning. J Neurosci 24:7015-7023.
58. Chien CN, Jaw FS (2005) Miniature telemetry system for the recording of action and field potentials. J Neurosci Methods 147:68-73.
59. Domino EF, Chodoff P, Corssen G (1965) Pharmacologic Effects of Ci-581, a New Dissociative Anesthetic, in Man. Clin Pharmacol Ther 6:279-291.
60. Corssen G, Domino EF (1966) Dissociative anesthesia:further pharmacologic studies and first clinical experience with the phencyclidine derivative CI-581. Anesth Analg 45:29-40.
61. Sinner B, Graf BM (2008) Ketamine. Handb Exp Pharmacol:313-333.
62. Alkire MT, Hudetz AG, Tononi G (2008) Consciousness and anesthesia. Science 322:876-880.
63. Craven R (2007) Ketamine. Anaesthesia 62 Suppl 1:48-53.
64. Harborne G, Watson F, Healy D, Groves L (1996) The effects of sub-anaesthetic doses of ketamine on memory, cognitive performance and subjective experience in healthy volunteers Journal of Psychopharmacology 10:134-140.
65. Newcomer JW, Farber NB, Jevtovic-Todorovic V, Selke G, Melson AK, et al. (1999) Ketamine-induced NMDA receptor hypofunction as a model of memory impairment and psychosis. Neuropsychopharmacology 20:106-118.
66. Morgan CJ, Mofeez A, Brandner B, Bromley L, Curran HV (2004) Acute effects of ketamine on memory systems and psychotic symptoms in healthy volunteers. Neuropsychopharmacology 29:208-218.
67. Honey GD, Honey RA, O'Loughlin C, Sharar SR, Kumaran D, et al. (2005) Ketamine disrupts frontal and hippocampal contribution to encoding and retrieval of episodic memory:an fMRI study. Cereb Cortex 15:749-759.
68. Newcomer JW, Krystal JH (2001) NMDA receptor regulation of memory and behavior in humans. Hippocampus 11:529-542.
69. Ellison G (1995) The N-methyl-D-aspartate antagonists phencyclidine, ketamine and dizocilpine as both behavioral and anatomical models of the dementias. Brain Res Brain Res Rev 20:250-267.
70. Grunwald T, Beck H, Lehnertz K, Blumcke I, Pezer N, et al. (1999) Evidence relating human verbal memory to hippocampal N-methyl-D-aspartate receptors. Proc Natl Acad Sci U S A 96:12085-12089.
71. Squire LR, Stark CE, Clark RE (2004) The medial temporal lobe. Annu Rev Neurosci 27:279-306.
72. Tang YP, Shimizu E, Dube GR, Rampon C, Kerchner GA, et al. (1999) Genetic enhancement of learning and memory in mice. Nature 401:63-69.
73. Tulving E, Craik FIM (2000) The Oxford handbook of memory. Oxford:Oxford University Press. xiv,700 p. p.
74. Shimizu E, Tang YP, Rampon C, Tsien JZ (2000) NMDA receptor-dependent synaptic reinforcement as a crucial process for memory consolidation. Science 290:1170-1174.
75. Sara SJ, Hars B (2006) In memory of consolidation. Learn Mem 13:515-521.
76. O'Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171-175.
77. Greene R (2001) Circuit analysis of NMDAR hypofunction in the hippocampus, in vitro, and psychosis of schizophrenia. Hippocampus 11:569-577.
78. Hunt MJ, Falinska M, Leski S, Wojcik DK, Kasicki S (2010) Differential effects produced by ketamine on oscillatory activity recorded in the rat hippocampus, dorsal striatum and nucleus accumbens. J Psychopharmacol.
79. Hakami T, Jones NC, Tolmacheva EA, Gaudias J, Chaumont J, et al. (2009) NMDA receptor hypofunction leads to generalized and persistent aberrant gamma oscillations independent of hyperlocomotion and the state of consciousness. PLoS One 4:e6755.
80. Lazarewicz MT, Ehrlichman RS, Maxwell CR, Gandal MJ, Finkel LH, et al. (2009) Ketamine Modulates Theta and Gamma Oscillations. J Cogn Neurosci.
81. Monyer H, Burnashev N, Laurie DJ, Sakmann B, Seeburg PH (1994) Developmental and regional expression in the rat brain and functional properties of four NMDA receptors. Neuron 12:529-540.
82. Watanabe M, Inoue Y, Sakimura K, Mishina M (1992) Developmental changes in distribution of NMDA receptor channel subunit mRNAs. Neuroreport 3:1138-1140.
83. Kutsuwada T, Kashiwabuchi N, Mori H, Sakimura K, Kushiya E, et al. (1992) Molecular diversity of the NMDA receptor channel. Nature 358:36-41.
84. Sheng M, Cummings J, Roldan LA, Jan YN, Jan LY (1994) Changing subunit composition of heteromeric NMDA receptors during development of rat cortex. Nature 368: 144-147.
85. Durieux ME (1995) Inhibition by ketamine of muscarinic acetylcholine receptor function. Anesth Analg 81:57-62.
86. Buzsaki G, Eidelberg E (1983) Phase relations of hippocampal projection cells and interneurons to theta activity in the anesthetized rat. Brain Res 266:334-339.
87. Sik A, Penttonen M, Ylinen A, Buzsaki G (1995) Hippocampal CA1 interneurons: an in vivo intracellular labeling study. J Neurosci 15:6651-6665.
88. Freund TF, Buzsaki G (1996) Interneurons of the hippocampus. Hippocampus 6: 347-470.
89. Perry E, Walker M, Grace J, Perry R (1999) Acetylcholine in mind:a neurotransmitter correlate of consciousness? Trends Neurosci 22:273-280.
90. O'Keefe J, Nadel L (1978) The hippocampus as a cognitive map:Oxford University Press.
91. O'Keefe J, Recce ML (1993) Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3:317-330.
92. O'Keefe J, Burgess N (1996) Geometric determinants of the place fields of hippocampal neurons. Nature 381:425-428.
93. Foster DJ, Wilson MA (2006) Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature 440:680-683.
94. Diba K, Buzsaki G (2007) Forward and reverse hippocampal place-cell sequences during ripples. Nat Neurosci 10:1241-1242.
95. Ji D, Wilson MA (2007) Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat Neurosci 10:100-107.
96. Hebb DO (1949) The organization of behavior; a neuropsychological theory. New York,:Wiley. xix,335 p. p.
97. Berger TW, Alger B, Thompson RF (1976) Neuronal substrate of classical conditioning in the hippocampus. Science 192:483-485.
98. Deadwyler SA, Bunn T, Hampson RE (1996) Hippocampal ensemble activity during spatial delayed-nonmatch-to-sample performance in rats. J Neurosci 16:354-372.
99. Dragoi G, Harris KD, Buzsaki G (2003) Place representation within hippocampal networks is modified by long-term potentiation. Neuron 39:843-853.
100. Weiss C, Kronforst-Collins MA, Disterhoft JF (1996) Activity of hippocampal pyramidal neurons during trace eyeblink conditioning. Hippocampus 6:192-209.
101. Abbott LF, Dayan P (1999) The effect of correlated variability on the accuracy of a population code. Neural Comput 11:91-101.
102. Lestienne R (2001) Spike timing, synchronization and information processing on the sensory side of the central nervous system. Prog Neurobiol 65:545-591.
103. Koch M (1999) The neurobiology of startle. Prog Neurobiol 59:107-128.
104. LeDoux JE (1994) Emotion, memory and the brain. Sci Am 270:50-57.
105. Osan R, Zhu L, Shoham S, Tsien JZ (2007) Subspace projection approaches to classification and visualization of neural network-level encoding patterns. PLoS ONE 2:e404.
106. Nicolelis MA, Lin RC, Chapin JK (1997) Neonatal whisker removal reduces the discrimination of tactile stimuli by thalamic ensembles in adult rats. J Neurophysiol 78:1691-1706.
107. Tsien JZ (2007) Real-time neural coding of memory. Prog Brain Res 165:105-122.
108. Sperling G (1960) The information available in brief visual presentations. Psychological Monographs:General and Applied 74:1-30.
109. Weedon B, Kaminska Z (1999) Echoic memory in primitive auditory selective attention. Retrieved December 8,2006.
110. Miller GA (1956) The magical number seven plus or minus two:some limits on our capacity for processing information. Psychol Rev 63:81-97.
111. Baddeley AD (1966) The influence of acoustic and semantic similarity on long-term memory for word sequences. Q J Exp Psychol 18:302-309.
112. Costa-Mattioli M, Sonenberg N (2008) Translational control of gene expression:a molecular switch for memory storage. Prog Brain Res 169:81-95.
113. Atkinson RC, Shiffrin RM (1968) Human memory:A proposed system and its control processes.; In Spence KWS, J.T., editor. New York:Academic Press.
114. Tulving E, Schacter DL (1990) Priming and human memory systems. Science 247: 301-306.
115. Squire LR (2004) Memory systems of the brain:a brief history and current perspective. Neurobiol Learn Mem 82:171-177.
116. Tulving E (1983) Elements of episodic memory. London:Oxford University Press.
117. Tulving E (2002) Episodic memory:from mind to brain. Annu Rev Psychol 53:1-25.
118. Yonelinas AP, Kroll NE, Dobbins I, Lazzara M, Knight RT (1998) Recollection and familiarity deficits in amnesia:convergence of remember-know, process dissociation, and receiver operating characteristic data. Neuropsychology 12:323-339.
119. Clayton NS, Bussey TJ, Dickinson A (2003) Can animals recall the past and plan for the future? Nat Rev Neurosci 4:685-691.
120. Clayton NS, Yu KS, Dickinson A (2003) Interacting Cache memories:evidence for flexible memory use by Western Scrub-Jays (Aphelocoma californica). J Exp Psychol Anim Behav Process 29:14-22.
121. Suddendorf T, Busby J (2003) Mental time travel in animals? Trends Cogn Sci 7: 391-396.
122. Suddendorf T, Corballis MC (2007) The evolution of foresight:What is mental time travel, and is it unique to humans? Behav Brain Sci 30:299-313; discussion 313-251.
123. Eacott MJ, Easton A (2007) On familiarity and recall of events by rats. Hippocampus 17:890-897.
124. Aggleton JP, McMackin D, Carpenter K, Hornak J, Kapur N, et al. (2000) Differential cognitive effects of colloid cysts in the third ventricle that spare or compromise the fornix. Brain 123 (Pt 4):800-815.
125. Squire LR, Zola SM (1996) Ischemic brain damage and memory impairment:a commentary. Hippocampus 6:546-552.
126. Aggleton JP, Brown MW (1999) Episodic memory, amnesia, and the hippocampal-anterior thalamic axis. Behav Brain Sci 22:425-444; discussion 444-489.
127. Mitchell DB, Brown AS, Murphy DR (1990) Dissociations between procedural and episodic memory:effects of time and aging. Psychol Aging 5:264-276.
128. Graham NL, Emery T, Hodges JR (2004) Distinctive cognitive profiles in Alzheimer's disease and subcortical vascular dementia. J Neurol Neurosurg Psychiatry 75: 61-71.
129. Dudai Y (2004) The neurobiology of consolidations, or, how stable is the engram? Annu Rev Psychol 55:51-86.
130. Lee JL, Everitt BJ, Thomas KL (2004) Independent cellular processes for hippocampal memory consolidation and reconsolidation. Science 304:839-843.
131. Born J (2010) Slow-wave sleep and the consolidation of long-term memory. World J Biol Psychiatry 11 Suppl 1:16-21.
132. Wolansky T, Clement EA, Peters SR, Palczak MA, Dickson CT (2006) Hippocampal slow oscillation:a novel EEG state and its coordination with ongoing neocortical activity. J Neurosci 26:6213-6229.
133. Nazer F, Dickson CT (2009) Slow oscillation state facilitates epileptiform events in the hippocampus. J Neurophysiol 102:1880-1889.
134. Sirota A, Csicsvari J, Buhl D, Buzsaki G (2003) Communication between neocortex and hippocampus during sleep in rodents. Proc Natl Acad Sci U S A 100:2065-2069.
135. Eschenko O, Molle M, Born J, Sara SJ (2006) Elevated sleep spindle density after learning or after retrieval in rats. J Neurosci 26:12914-12920.
136. Draguhn A, Traub RD, Bibbig A, Schmitz D (2000) Ripple (approximately 200-Hz) oscillations in temporal structures. J Clin Neurophysiol 17:361-376.
137. O'Neill J, Pleydell-Bouverie B, Dupret D, Csicsvari J (2010) Play it again: reactivation of waking experience and memory. Trends Neurosci 33:220-229.
138. Molle M, Yeshenko O, Marshall L, Sara SJ, Born J (2006) Hippocampal sharp wave-ripples linked to slow oscillations in rat slow-wave sleep. J Neurophysiol 96:62-70.
139. Puig MV, Ushimaru M, Kawaguchi Y (2008) Two distinct activity patterns of fast-spiking interneurons during neocortical UP states. Proc Natl Acad Sci U S A 105:8428-8433.
140. Nadasdy Z, Hirase H, Czurko A, Csicsvari J, Buzsaki G (1999) Replay and time compression of recurring spike sequences in the hippocampus. J Neurosci 19:9497-9507.
141. Euston DR, Tatsuno M, McNaughton BL (2007) Fast-forward playback of recent memory sequences in prefrontal cortex during sleep. Science 318:1147-1150.
142. O'Neill J, Senior TJ, Allen K, Huxter JR, Csicsvari J (2008) Reactivation of experience-dependent cell assembly patterns in the hippocampus. Nat Neurosci 11:209-215.
143. O'Neill J, Senior T, Csicsvari J (2006) Place-selective firing of CA1 pyramidal cells during sharp wave/ripple network patterns in exploratory behavior. Neuron 49:143-155.
144. Nakashiba T, Buhl DL, McHugh TJ, Tonegawa S (2009) Hippocampal CA3 output is crucial for ripple-associated reactivation and consolidation of memory. Neuron 62:781-787.
145. Muller R (1996) A quarter of a century of place cells. Neuron 17:813-822.
146. O'Keefe J, Gaffan D (1971) Response properties of units in the dorsal column nuclei of the freely moving rat:changes as a function of behaviour. Brain Res 31:374-375.
147. O'Keefe J (1976) Place units in the hippocampus of the freely moving rat. Exp Neurol 51:78-109.
148. de Hoz L, Wood ER (2006) Dissociating the past from the present in the activity of place cells. Hippocampus 16:704-715.
149. Lin L, Chen G, Kuang H, Wang D, Tsien JZ (2007) Neural encoding of the concept of nest in the mouse brain. Proc Natl Acad Sci U S A 104:6066-6071.
150. Cao X, Cui Z, Feng R, Tang YP, Qin Z, et al. (2007) Maintenance of superior learning and memory function in NR2B transgenic mice during ageing. Eur J Neurosci 25: 1815-1822.
151. Kuang H, Mei B, Cui Z, Lin L, Tsien JZ (2010) A novel behavioral paradigm for assessing concept of nests in mice. J Neurosci Methods.
2. Buzsaki G, Haubenreiser J, Grastyan E, Czopf J, Kellenyi L (1981) Hippocampal slow wave activity during appetitive and aversive conditioning in the cat. Electroencephalogr Clin Neurophysiol 51:276-290.
3. Buzsaki G, Leung LW, Vanderwolf CH (1983) Cellular bases of hippocampal EEG in the behaving rat. Brain Res 287:139-171.
4. Wilson MA, McNaughton BL (1994) Reactivation of hippocampal ensemble memories during sleep. Science 265:676-679.
5. Skaggs WE, McNaughton BL (1996) Replay of neuronal firing sequences in rat hippocampus during sleep following spatial experience. Science 271:1870-1873.
6. Kudrimoti HS, Barnes CA, McNaughton BL (1999) Reactivation of hippocampal cell assemblies:effects of behavioral state, experience, and EEG dynamics. J Neurosci 19:4090-4101.
7. Louie K, Wilson MA (2001) Temporally structured replay of awake hippocampal ensemble activity during rapid eye movement sleep. Neuron 29:145-156.
8. Lee AK, Wilson MA (2002) Memory of sequential experience in the hippocampus during slow wave sleep. Neuron 36:1183-1194.
9. Csicsvari J, Hirase H, Czurko A, Mamiya A, Buzsaki G (1999) Oscillatory coupling of hippocampal pyramidal cells and interneurons in the behaving Rat. J Neurosci 19:274-287.
10. Schmidt EM (1999) Electrodes for many single neuron recordings. In:Nicolelis MA, editor. Methods for neural ensemble recordings:CRC Press. pp.1-23.
11. McNaughton BL, O'Keefe J, Barnes CA (1983) The stereotrode:a new technique for simultaneous isolation of several single units in the central nervous system from multiple unit records. J Neurosci Methods 8:391-397.
12. Gray CM, Maldonado PE, Wilson M, McNaughton B (1995) Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex. J Neurosci Methods 63:43-54.
13. Wilson MA, McNaughton BL (1993) Dynamics of the hippocampal ensemble code for space. Science 261:1055-1058.
14. Hoffman KL, McNaughton BL (2002) Coordinated reactivation of distributed memory traces in primate neocortex. Science 297:2070-2073.
15. Wills TJ, Lever C, Cacucci F, Burgess N, O'Keefe J (2005) Attractor dynamics in the hippocampal representation of the local environment. Science 308:873-876.
16. Lin L, Osan R, Shoham S, Jin W, Zuo W, et al. (2005) Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus. Proc Natl Acad Sci U S A 102:6125-6130.
17. Lin L, Chen G, Xie K, Zaia KA, Zhang S, et al. (2006) Large-scale neural ensemble recording in the brains of freely behaving mice. J Neurosci Methods 155:28-38.
18. Scoville WB, Milner B (1957) Loss of recent memory after bilateral hippocampal lesions. J Neurol Neurosurg Psychiatry 20:11-21.
19. Squire LR (1987) Memory and brain. New York; Oxford:Oxford University Press. xii,315 p. p.
20. Tsien JZ, Huerta PT, Tonegawa S (1996) The essential role of hippocampal CA1 NMDA receptor-dependent synaptic plasticity in spatial memory. Cell 87:1327-1338.
21. Sara SJ (2000) Retrieval and reconsolidation:toward a neurobiology of remembering. Learn Mem 7:73-84.
22. Cohen NJ, Eichenbaum H (1993) Memory, amnesia, and the hippocampal system. Cambridge, Mass.:MIT Press. xii,330 p. p.
23. O'Keefe JM, Nadel L (1978) The hippocampus as a cognitive map. Oxford
New York:Clarendon Press;
Oxford University Press. xiv,570 p. p.
24. Disterhoft JF, Coulter DA, Alkon DL (1986) Conditioning-specific membrane changes of rabbit hippocampal neurons measured in vitro. Proc Natl Acad Sci U S A 83: 2733-2737.
25. Fenton AA, Muller RU (1998) Place cell discharge is extremely variable during individual passes of the rat through the firing field. Proc Natl Acad Sci U S A 95:3182-3187.
26. Eichenbaum H, Dudchenko P, Wood E, Shapiro M, Tanila H (1999) The hippocampus, memory, and place cells:is it spatial memory or a memory space? Neuron 23: 209-226.
27. Leutgeb S, Mizumori SJ (1999) Excitotoxic septal lesions result in spatial memory deficits and altered flexibility of hippocampal single-unit representations. J Neurosci 19: 6661-6672.
28. Wirth S, Yanike M, Frank LM, Smith AC, Brown EN, et al. (2003) Single neurons in the monkey hippocampus and learning of new associations. Science 300:1578-1581.
29. Thompson RF (2005) In search of memory traces. Annu Rev Psychol 56:1-23.
30. Klausberger T, Magill PJ, Marton LF, Roberts JD, Cobden PM, et al. (2003) Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421:844-848.
31. Klausberger T, Marton LF, Baude A, Roberts JD, Magill PJ, et al. (2004) Spike timing of dendrite-targeting bistratified cells during hippocampal network oscillations in vivo. Nat Neurosci 7:41-47.
32. Klausberger T, Marton LF, O'Neill J, Huck JH, Dalezios Y, et al. (2005) Complementary roles of cholecystokinin- and parvalbumin-expressing GABAergic neurons in hippocampal network oscillations. J Neurosci 25:9782-9793.
33. Somogyi P, Klausberger T (2005) Defined types of cortical interneurone structure space and spike timing in the hippocampus. J Physiol 562:9-26.
34. Jinno S, Klausberger T, Marton LF, Dalezios Y, Roberts JD, et al. (2007) Neuronal diversity in GABAergic long-range projections from the hippocampus. J Neurosci 27:8790-8804.
35. Tukker JJ, Fuentealba P, Hartwich K, Somogyi P, Klausberger T (2007) Cell type-specific tuning of hippocampal interneuron firing during gamma oscillations in vivo. J Neurosci 27:8184-8189.
36. Fuentealba P, Begum R, Capogna M, Jinno S, Marton LF, et al. (2008) Ivy cells:a population of nitric-oxide-producing, slow-spiking GABAergic neurons and their involvement in hippocampal network activity. Neuron 57:917-929.
37. Klausberger T, Somogyi P (2008) Neuronal diversity and temporal dynamics:the unity of hippocampal circuit operations. Science 321:53-57.
38. Sirota A, Montgomery S, Fujisawa S, Isomura Y, Zugaro M, et al. (2008) Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 60:683-697.
39. Hafting T, Fyhn M, Molden S, Moser MB, Moser El (2005) Microstructure of a spatial map in the entorhinal cortex. Nature 436:801-806.
40. Middleton S, Jalics J, Kispersky T, Lebeau FE, Roopun AK, et al. (2008) NMDA receptor-dependent switching between different gamma rhythm-generating microcircuits in entorhinal cortex. Proc Natl Acad Sci U S A 105:18572-18577.
41. Moser EI, Moser MB (2008) A metric for space. Hippocampus 18:1142-1156.
42. Cutsuridis V, Wennekers T (2009) Hippocampus, microcircuits and associative memory. Neural Netw 22:1120-1128.
43. Fox SE, Ranck JB, Jr. (1981) Electrophysiological characteristics of hippocampal complex-spike cells and theta cells. Exp Brain Res 41:399-410.
44. Ranck JB, Jr. (1973) Studies on single neurons in dorsal hippocampal formation and septum in unrestrained rats. Ⅰ. Behavioral correlates and firing repertoires. Exp Neurol 41: 461-531.
45. Buzsaki G, Rappelsberger P, Kellenyi L (1985) Depth profiles of hippocampal rhythmic slow activity ('theta rhythm') depend on behaviour. Electroencephalogr Clin Neurophysiol 61:77-88.
46. Alonso A, Garcia-Austt E (1987) Neuronal sources of theta rhythm in the entorhinal cortex of the rat. Ⅰ. Laminar distribution of theta field potentials. Exp Brain Res 67:493-501.
47. Buzsaki G, Buhl DL, Harris KD, Csicsvari J, Czeh B, et al. (2003) Hippocampal network patterns of activity in the mouse. Neuroscience 116:201-211.
48. Chen G, Wang LP, Tsien JZ (2009) Neural population-level memory traces in the mouse hippocampus. PLoS One 4:e8256.
49. Buzsaki G, Horvath Z, Urioste R, Hetke J, Wise K (1992) High-frequency network oscillation in the hippocampus. Science 256:1025-1027.
50. Lin L, Osan R, Tsien JZ (2006) Organizing principles of real-time memory encoding: neural clique assemblies and universal neural codes. Trends Neurosci 29:48-57.
51. Tsien JZ (2007) The memory code. Researchers are closing in on the rules that the brain uses to lay down memories. Discovery of this memory code could lead to the design of smarter computers and robots and even to new ways to peer into the human mind. Sci Am 297:52-59.
52. Wang H, Hu Y, Tsien JZ (2006) Molecular and systems mechanisms of memory consolidation and storage. Prog Neurobiol 79:123-135.
53. Wang H, Feng R, Phillip Wang L, Li F, Cao X, et al. (2008) CaMKII activation state underlies synaptic labile phase of LTP and short-term memory formation. Curr Biol 18: 1546-1554.
54. Cao X, Wang H, Mei B, An S, Yin L, et al. (2008) Inducible and selective erasure of memories in the mouse brain via chemical-genetic manipulation. Neuron 60:353-366.
55. McEchron MD, Weible AP, Disterhoft JF (2001) Aging and learning-specific changes in single-neuron activity in CA1 hippocampus during rabbit trace eyeblink conditioning. J Neurophysiol 86:1839-1857.
56. Moita MA, Rosis S, Zhou Y, LeDoux JE, Blair HT (2003) Hippocampal place cells acquire location-specific responses to the conditioned stimulus during auditory fear conditioning. Neuron 37:485-497.
57. Moita MA, Rosis S, Zhou Y, LeDoux JE, Blair HT (2004) Putting fear in its place: remapping of hippocampal place cells during fear conditioning. J Neurosci 24:7015-7023.
58. Chien CN, Jaw FS (2005) Miniature telemetry system for the recording of action and field potentials. J Neurosci Methods 147:68-73.
59. Domino EF, Chodoff P, Corssen G (1965) Pharmacologic Effects of Ci-581, a New Dissociative Anesthetic, in Man. Clin Pharmacol Ther 6:279-291.
60. Corssen G, Domino EF (1966) Dissociative anesthesia:further pharmacologic studies and first clinical experience with the phencyclidine derivative CI-581. Anesth Analg 45:29-40.
61. Sinner B, Graf BM (2008) Ketamine. Handb Exp Pharmacol:313-333.
62. Alkire MT, Hudetz AG, Tononi G (2008) Consciousness and anesthesia. Science 322:876-880.
63. Craven R (2007) Ketamine. Anaesthesia 62 Suppl 1:48-53.
64. Harborne G, Watson F, Healy D, Groves L (1996) The effects of sub-anaesthetic doses of ketamine on memory, cognitive performance and subjective experience in healthy volunteers Journal of Psychopharmacology 10:134-140.
65. Newcomer JW, Farber NB, Jevtovic-Todorovic V, Selke G, Melson AK, et al. (1999) Ketamine-induced NMDA receptor hypofunction as a model of memory impairment and psychosis. Neuropsychopharmacology 20:106-118.
66. Morgan CJ, Mofeez A, Brandner B, Bromley L, Curran HV (2004) Acute effects of ketamine on memory systems and psychotic symptoms in healthy volunteers. Neuropsychopharmacology 29:208-218.
67. Honey GD, Honey RA, O'Loughlin C, Sharar SR, Kumaran D, et al. (2005) Ketamine disrupts frontal and hippocampal contribution to encoding and retrieval of episodic memory:an fMRI study. Cereb Cortex 15:749-759.
68. Newcomer JW, Krystal JH (2001) NMDA receptor regulation of memory and behavior in humans. Hippocampus 11:529-542.
69. Ellison G (1995) The N-methyl-D-aspartate antagonists phencyclidine, ketamine and dizocilpine as both behavioral and anatomical models of the dementias. Brain Res Brain Res Rev 20:250-267.
70. Grunwald T, Beck H, Lehnertz K, Blumcke I, Pezer N, et al. (1999) Evidence relating human verbal memory to hippocampal N-methyl-D-aspartate receptors. Proc Natl Acad Sci U S A 96:12085-12089.
71. Squire LR, Stark CE, Clark RE (2004) The medial temporal lobe. Annu Rev Neurosci 27:279-306.
72. Tang YP, Shimizu E, Dube GR, Rampon C, Kerchner GA, et al. (1999) Genetic enhancement of learning and memory in mice. Nature 401:63-69.
73. Tulving E, Craik FIM (2000) The Oxford handbook of memory. Oxford:Oxford University Press. xiv,700 p. p.
74. Shimizu E, Tang YP, Rampon C, Tsien JZ (2000) NMDA receptor-dependent synaptic reinforcement as a crucial process for memory consolidation. Science 290:1170-1174.
75. Sara SJ, Hars B (2006) In memory of consolidation. Learn Mem 13:515-521.
76. O'Keefe J, Dostrovsky J (1971) The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat. Brain Res 34:171-175.
77. Greene R (2001) Circuit analysis of NMDAR hypofunction in the hippocampus, in vitro, and psychosis of schizophrenia. Hippocampus 11:569-577.
78. Hunt MJ, Falinska M, Leski S, Wojcik DK, Kasicki S (2010) Differential effects produced by ketamine on oscillatory activity recorded in the rat hippocampus, dorsal striatum and nucleus accumbens. J Psychopharmacol.
79. Hakami T, Jones NC, Tolmacheva EA, Gaudias J, Chaumont J, et al. (2009) NMDA receptor hypofunction leads to generalized and persistent aberrant gamma oscillations independent of hyperlocomotion and the state of consciousness. PLoS One 4:e6755.
80. Lazarewicz MT, Ehrlichman RS, Maxwell CR, Gandal MJ, Finkel LH, et al. (2009) Ketamine Modulates Theta and Gamma Oscillations. J Cogn Neurosci.
81. Monyer H, Burnashev N, Laurie DJ, Sakmann B, Seeburg PH (1994) Developmental and regional expression in the rat brain and functional properties of four NMDA receptors. Neuron 12:529-540.
82. Watanabe M, Inoue Y, Sakimura K, Mishina M (1992) Developmental changes in distribution of NMDA receptor channel subunit mRNAs. Neuroreport 3:1138-1140.
83. Kutsuwada T, Kashiwabuchi N, Mori H, Sakimura K, Kushiya E, et al. (1992) Molecular diversity of the NMDA receptor channel. Nature 358:36-41.
84. Sheng M, Cummings J, Roldan LA, Jan YN, Jan LY (1994) Changing subunit composition of heteromeric NMDA receptors during development of rat cortex. Nature 368: 144-147.
85. Durieux ME (1995) Inhibition by ketamine of muscarinic acetylcholine receptor function. Anesth Analg 81:57-62.
86. Buzsaki G, Eidelberg E (1983) Phase relations of hippocampal projection cells and interneurons to theta activity in the anesthetized rat. Brain Res 266:334-339.
87. Sik A, Penttonen M, Ylinen A, Buzsaki G (1995) Hippocampal CA1 interneurons: an in vivo intracellular labeling study. J Neurosci 15:6651-6665.
88. Freund TF, Buzsaki G (1996) Interneurons of the hippocampus. Hippocampus 6: 347-470.
89. Perry E, Walker M, Grace J, Perry R (1999) Acetylcholine in mind:a neurotransmitter correlate of consciousness? Trends Neurosci 22:273-280.
90. O'Keefe J, Nadel L (1978) The hippocampus as a cognitive map:Oxford University Press.
91. O'Keefe J, Recce ML (1993) Phase relationship between hippocampal place units and the EEG theta rhythm. Hippocampus 3:317-330.
92. O'Keefe J, Burgess N (1996) Geometric determinants of the place fields of hippocampal neurons. Nature 381:425-428.
93. Foster DJ, Wilson MA (2006) Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature 440:680-683.
94. Diba K, Buzsaki G (2007) Forward and reverse hippocampal place-cell sequences during ripples. Nat Neurosci 10:1241-1242.
95. Ji D, Wilson MA (2007) Coordinated memory replay in the visual cortex and hippocampus during sleep. Nat Neurosci 10:100-107.
96. Hebb DO (1949) The organization of behavior; a neuropsychological theory. New York,:Wiley. xix,335 p. p.
97. Berger TW, Alger B, Thompson RF (1976) Neuronal substrate of classical conditioning in the hippocampus. Science 192:483-485.
98. Deadwyler SA, Bunn T, Hampson RE (1996) Hippocampal ensemble activity during spatial delayed-nonmatch-to-sample performance in rats. J Neurosci 16:354-372.
99. Dragoi G, Harris KD, Buzsaki G (2003) Place representation within hippocampal networks is modified by long-term potentiation. Neuron 39:843-853.
100. Weiss C, Kronforst-Collins MA, Disterhoft JF (1996) Activity of hippocampal pyramidal neurons during trace eyeblink conditioning. Hippocampus 6:192-209.
101. Abbott LF, Dayan P (1999) The effect of correlated variability on the accuracy of a population code. Neural Comput 11:91-101.
102. Lestienne R (2001) Spike timing, synchronization and information processing on the sensory side of the central nervous system. Prog Neurobiol 65:545-591.
103. Koch M (1999) The neurobiology of startle. Prog Neurobiol 59:107-128.
104. LeDoux JE (1994) Emotion, memory and the brain. Sci Am 270:50-57.
105. Osan R, Zhu L, Shoham S, Tsien JZ (2007) Subspace projection approaches to classification and visualization of neural network-level encoding patterns. PLoS ONE 2:e404.
106. Nicolelis MA, Lin RC, Chapin JK (1997) Neonatal whisker removal reduces the discrimination of tactile stimuli by thalamic ensembles in adult rats. J Neurophysiol 78:1691-1706.
107. Tsien JZ (2007) Real-time neural coding of memory. Prog Brain Res 165:105-122.
108. Sperling G (1960) The information available in brief visual presentations. Psychological Monographs:General and Applied 74:1-30.
109. Weedon B, Kaminska Z (1999) Echoic memory in primitive auditory selective attention. Retrieved December 8,2006.
110. Miller GA (1956) The magical number seven plus or minus two:some limits on our capacity for processing information. Psychol Rev 63:81-97.
111. Baddeley AD (1966) The influence of acoustic and semantic similarity on long-term memory for word sequences. Q J Exp Psychol 18:302-309.
112. Costa-Mattioli M, Sonenberg N (2008) Translational control of gene expression:a molecular switch for memory storage. Prog Brain Res 169:81-95.
113. Atkinson RC, Shiffrin RM (1968) Human memory:A proposed system and its control processes.; In Spence KWS, J.T., editor. New York:Academic Press.
114. Tulving E, Schacter DL (1990) Priming and human memory systems. Science 247: 301-306.
115. Squire LR (2004) Memory systems of the brain:a brief history and current perspective. Neurobiol Learn Mem 82:171-177.
116. Tulving E (1983) Elements of episodic memory. London:Oxford University Press.
117. Tulving E (2002) Episodic memory:from mind to brain. Annu Rev Psychol 53:1-25.
118. Yonelinas AP, Kroll NE, Dobbins I, Lazzara M, Knight RT (1998) Recollection and familiarity deficits in amnesia:convergence of remember-know, process dissociation, and receiver operating characteristic data. Neuropsychology 12:323-339.
119. Clayton NS, Bussey TJ, Dickinson A (2003) Can animals recall the past and plan for the future? Nat Rev Neurosci 4:685-691.
120. Clayton NS, Yu KS, Dickinson A (2003) Interacting Cache memories:evidence for flexible memory use by Western Scrub-Jays (Aphelocoma californica). J Exp Psychol Anim Behav Process 29:14-22.
121. Suddendorf T, Busby J (2003) Mental time travel in animals? Trends Cogn Sci 7: 391-396.
122. Suddendorf T, Corballis MC (2007) The evolution of foresight:What is mental time travel, and is it unique to humans? Behav Brain Sci 30:299-313; discussion 313-251.
123. Eacott MJ, Easton A (2007) On familiarity and recall of events by rats. Hippocampus 17:890-897.
124. Aggleton JP, McMackin D, Carpenter K, Hornak J, Kapur N, et al. (2000) Differential cognitive effects of colloid cysts in the third ventricle that spare or compromise the fornix. Brain 123 (Pt 4):800-815.
125. Squire LR, Zola SM (1996) Ischemic brain damage and memory impairment:a commentary. Hippocampus 6:546-552.
126. Aggleton JP, Brown MW (1999) Episodic memory, amnesia, and the hippocampal-anterior thalamic axis. Behav Brain Sci 22:425-444; discussion 444-489.
127. Mitchell DB, Brown AS, Murphy DR (1990) Dissociations between procedural and episodic memory:effects of time and aging. Psychol Aging 5:264-276.
128. Graham NL, Emery T, Hodges JR (2004) Distinctive cognitive profiles in Alzheimer's disease and subcortical vascular dementia. J Neurol Neurosurg Psychiatry 75: 61-71.
129. Dudai Y (2004) The neurobiology of consolidations, or, how stable is the engram? Annu Rev Psychol 55:51-86.
130. Lee JL, Everitt BJ, Thomas KL (2004) Independent cellular processes for hippocampal memory consolidation and reconsolidation. Science 304:839-843.
131. Born J (2010) Slow-wave sleep and the consolidation of long-term memory. World J Biol Psychiatry 11 Suppl 1:16-21.
132. Wolansky T, Clement EA, Peters SR, Palczak MA, Dickson CT (2006) Hippocampal slow oscillation:a novel EEG state and its coordination with ongoing neocortical activity. J Neurosci 26:6213-6229.
133. Nazer F, Dickson CT (2009) Slow oscillation state facilitates epileptiform events in the hippocampus. J Neurophysiol 102:1880-1889.
134. Sirota A, Csicsvari J, Buhl D, Buzsaki G (2003) Communication between neocortex and hippocampus during sleep in rodents. Proc Natl Acad Sci U S A 100:2065-2069.
135. Eschenko O, Molle M, Born J, Sara SJ (2006) Elevated sleep spindle density after learning or after retrieval in rats. J Neurosci 26:12914-12920.
136. Draguhn A, Traub RD, Bibbig A, Schmitz D (2000) Ripple (approximately 200-Hz) oscillations in temporal structures. J Clin Neurophysiol 17:361-376.
137. O'Neill J, Pleydell-Bouverie B, Dupret D, Csicsvari J (2010) Play it again: reactivation of waking experience and memory. Trends Neurosci 33:220-229.
138. Molle M, Yeshenko O, Marshall L, Sara SJ, Born J (2006) Hippocampal sharp wave-ripples linked to slow oscillations in rat slow-wave sleep. J Neurophysiol 96:62-70.
139. Puig MV, Ushimaru M, Kawaguchi Y (2008) Two distinct activity patterns of fast-spiking interneurons during neocortical UP states. Proc Natl Acad Sci U S A 105:8428-8433.
140. Nadasdy Z, Hirase H, Czurko A, Csicsvari J, Buzsaki G (1999) Replay and time compression of recurring spike sequences in the hippocampus. J Neurosci 19:9497-9507.
141. Euston DR, Tatsuno M, McNaughton BL (2007) Fast-forward playback of recent memory sequences in prefrontal cortex during sleep. Science 318:1147-1150.
142. O'Neill J, Senior TJ, Allen K, Huxter JR, Csicsvari J (2008) Reactivation of experience-dependent cell assembly patterns in the hippocampus. Nat Neurosci 11:209-215.
143. O'Neill J, Senior T, Csicsvari J (2006) Place-selective firing of CA1 pyramidal cells during sharp wave/ripple network patterns in exploratory behavior. Neuron 49:143-155.
144. Nakashiba T, Buhl DL, McHugh TJ, Tonegawa S (2009) Hippocampal CA3 output is crucial for ripple-associated reactivation and consolidation of memory. Neuron 62:781-787.
145. Muller R (1996) A quarter of a century of place cells. Neuron 17:813-822.
146. O'Keefe J, Gaffan D (1971) Response properties of units in the dorsal column nuclei of the freely moving rat:changes as a function of behaviour. Brain Res 31:374-375.
147. O'Keefe J (1976) Place units in the hippocampus of the freely moving rat. Exp Neurol 51:78-109.
148. de Hoz L, Wood ER (2006) Dissociating the past from the present in the activity of place cells. Hippocampus 16:704-715.
149. Lin L, Chen G, Kuang H, Wang D, Tsien JZ (2007) Neural encoding of the concept of nest in the mouse brain. Proc Natl Acad Sci U S A 104:6066-6071.
150. Cao X, Cui Z, Feng R, Tang YP, Qin Z, et al. (2007) Maintenance of superior learning and memory function in NR2B transgenic mice during ageing. Eur J Neurosci 25: 1815-1822.
151. Kuang H, Mei B, Cui Z, Lin L, Tsien JZ (2010) A novel behavioral paradigm for assessing concept of nests in mice. J Neurosci Methods.