Stability and Robustness of Hippocampal Representations of Space

项目摘要 大脑是如何平衡保存先前知识的需要和不断学习的必要性的呢 新消息稳定性和可塑性之间的权衡是生物学和阿尔蒂文学中固有的。 受有限资源和能力限制的学习系统。海马体是一个大脑区域， 记忆形成和空间学习，这可以提供一个强大的实验系统，表征 这个交易。海马体在空间认知中的作用得到了以下发现的支持： 这个区域的神经元（位置细胞）在环境中的特定位置（位置场）放电。的人口 在环境中活跃的位置细胞被认为形成了一个神经表征或认知地图， 环境空间学习对生存至关重要，涉及两个相互竞争的限制： 空间必须是可塑的，以便能够快速学习新环境和行为偶然性的变化， 并且随着时间的推移保持稳定，从而能够识别熟悉的环境、可靠的导航以及利用 以前的学习。这些相互竞争的约束是如何影响地点场在时间上的稳定性的？的 海马体空间表征长期稳定性的实验表征， 因为它需要在很长一段时间内跟踪多个位置细胞的活动， (days周）。我们建议在大规模电生理学和成像中使用新方法， 行为啮齿动物来表征哪些神经元改变了它们的空间调谐以及这些变化如何依赖于 关于行为。此外，我们将使用记录和电路扰动来表征活动模式 来预测调谐稳定性的变化。我们的分析将在一个理论的背景下进行， 框架理解可塑性和稳定性之间的相互作用海马表示。 描述神经表征的进化对于理解如何 信息在大脑回路中维持，以及这种维持在大脑疾病中是如何受到干扰的。

PROJECT SUMMARY How does the brain balance the need to preserve prior knowledge with the necessity to continuously learn new information? The tradeoff between stability and plasticity is inherent in both biological and artificial learning systems constrained by finite resources and capacity. The hippocampus is a brain region critical for memory formation and spatial learning, which can provide a powerful experimental system for characterizing this tradeoff. The role of the hippocampus in spatial cognition is supported by the finding that pyramidal neurons in this area (place cells) fire in specific locations in an environment (place fields). The population of place cells active in an environment is believed to form a neural representation or cognitive map of that environment. Spatial learning is critical for survival and involves two competing constraints: representations of space must be plastic to enable fast learning of new environments and changes in behavioral contingencies, and stable over time to enable recognition of familiar environments, reliable navigation, and leveraging of previous learning. How do these competing constraints affect the stability of place fields across time? The experimental characterization of the long-term stability of spatial representations in the hippocampus has been challenging as it requires tracking the activity of multiple place cells across extended periods of time (days to weeks). We propose to use novel approaches in large-scale electrophysiology and imaging in behaving rodents to characterize which neurons change their spatial tuning and how these changes depend on behavior. Furthermore, we will use recordings and circuit perturbations to characterize the activity patterns that predict changes in tuning stability. Our analysis will be carried out in the context of a theoretical framework for understanding the interplay between plasticity and stability of hippocampal representations. Characterizing the evolution of neural representations is of fundamental importance in understanding how information is maintained across brain circuits and how such maintenance is perturbed in brain disorders.