Differential Roles Of CA1 Pyramidal Cells And Diverse Interneurons In Encoding Real-time Representation Of Episodic Experiences

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.