Role of neural variation in hippocampal coding and plasticity

许多研究人员已经表明，在人类中，海马结构是必要的， 形成对事实或事件的新记忆。在啮齿类动物中，这些相同的结构在一个 动物学习和记忆复杂关联的能力，包括动物必须完成的任务 学习和记忆有关一组空间线索的信息，以便在环境中导航。 人类的事件/事实记忆和啮齿动物的空间记忆都需要学习复杂的关系， 这种相似性强烈地表明，人类和大鼠的处理过程在性质上是相似的。 海马，使大鼠海马一个有吸引力的模型系统，研究记忆加工。 记忆储存和回忆需要在看似矛盾的要求之间取得平衡：系统 必须具有足够的可塑性，以允许新的活动模式被快速储存，但又足够稳定， 以前存储的记忆可以在没有太大扭曲的情况下恢复。本提案的目的是比较 海马体的输入、海马体本身和海马体的输出之间的神经变异性 海马，并确定是否变异与行为和动态调节过程中， 学习我们将测试以下假设：1）海马回路产生低变异性 高度可变输入的空间表示，2）海马回路的可变性降低， 记忆任务的背景，以及3）学习导致海马体中可变性的快速变化， 内嗅皮层（EC）下游深层的变化较慢，反映了 快速学习的海马和慢速学习的深层EC之间的关系 位置和行为。把我们的研究结果与其他项目的研究结果结合起来， 了解大脑系统中神经代码变化的作用。

Numerous researchers have shown that, in humans, the hippocampal formation is necessary for the formation of new memories of facts or events. In rodents these same structures play an essential role in an animal's ability to learn about and remember complex associations, including tasks where the animal must learn and remember information about a set of spatial cues in order to navigate through an environment. Both event / fact memory in humans and spatial memory in rodents requires learning complex relationships, and that parallel strongly suggests that qualitatively similar processing occurs in the human and the rat hippocampus, making the rat hippocampus an attractive model system for investigating memory processing. Memory storage and recall require a balance between seemingly contradictory requirements: the system must be sufficiently plastic to allow new patterns of activity to be rapidly stored, yet sufficiently stable to allow previously stored memories to be retrieved without great distortion. The aim of this proposal is to compare neural variability among the inputs to the hippocampus, the hippocampus itself and the outputs of the hippocampus and to determine whether variability is related to behavior and dynamically regulated during learning. We will test the following hypotheses: 1) the hippocampal circuit creates a low variability representation of space from highly variable inputs, 2) variability in the hippocampal circuit is decreased in the context of memory tasks, and 3) learning causes rapid changes in variability in the hippocampus but slower changes in the downstream deep layers of the entorhinal cortex (EC), reflecting the specialization of the hippocampus for rapid learning and of the deep EC for slower learning of the relationships between locations and behaviors. Integrating our findings with those of the other projects will help us better understand the role of variation in the neural code across brain systems.