The Dynamics of Memory Retrieval and Forgetting

描述（由申请人提供）：这里提出的研究的具体目的是：1)测试通过计算模型做出的关于theta节律与记忆检索和记忆强度之间关系的预测；2)进一步完善和发展这些模型。这些模型及其预测，如果得到证实，将与阿尔茨海默病、成瘾和创伤后应激障碍（PTSD）等疾病的临床治疗发展直接相关。在具体目标#1下，我将在两种环境中为老鼠提供丰富的经验。定义这些环境的特征将包括封闭照明和行为奖励偶然性。当大鼠进行纯环境试验和混合环境试验时，我将记录海马体中位置细胞和内嗅皮层内侧网格细胞的活动。在纯环境试验中，环境特征将在整个试验过程中保持固定；我将使用这些试验来描述两个独立环境中所有细胞的空间调优（即空间地图）。在混合环境试验期间，环境特征将在每次试验期间多次在定义单独环境的环境特征之间切换。我将根据人口活动推断，在这些混合环境试验中，哪个空间地图在每个时刻被激活。在实验1中，我将测试一个空间地图关闭而另一个空间地图取代它的时刻是否在正在进行的θ节奏的阶段中不均匀地发生。在实验2中，我将测试是否有可能诱导空间地图的部分检索，从而改变替代空间地图激活的点，正如我之前提出的模型所预测的那样。在实验3中，我将测试大鼠的行为与哪个空间图被激活之间的对应关系，以测试这种操作是否可以作为改变行为的临床治疗。在实验4中，我将探讨海马和内嗅重映射的相对时间。在Specific Aim #2中，我将使用计算建模来支持Specific Aim #1中描述的实证工作。具体来说，我将使用生成预测的相同模型来模拟我将用于测试这些预测的任务。从这些模拟中，我将生成合成数据，我将在这些数据上验证数据分析方法，我将使用这些方法来推断每个时刻哪个空间地图是活跃的。这些模拟也将允许我开发刺激控制协议，用于特定目标#1的实验2，这将最可靠地产生部分检索。最重要的是，它们将允许我生成额外的可测试预测，这些预测是关于具体目标#1中描述的预测的边界条件，从而激励我进行下一系列实验。

DESCRIPTION (provided by applicant): The specific aims of the research proposed here are to 1) test predictions, made by computational models, regarding the relationship between theta rhythms and memory retrieval and memory strength; and 2) further refine and develop these models. These models and their predictions, if verified, carry direct relevance for the development of clinical therapies for disorders such as Alzheimer's disease, addiction, and post-traumatic stress disorder (PTSD). Under Specific Aim #1, I will provide rats with extensive experience in two environments. Defining features of these environments will include the enclosure lighting and the behavior-reward contingency. I will record the activity of place cells in the hippocampus and grid cells in the medial entorhinal cortex as the rats perform pure-environment trials and mixed-environment trials. During pure-environment trials, the environmental features will remain fixed throughout the trial; I will use these trials to characterize the spatial tunings of all of the cells (i.e., the spatial map) in the two separate environments. During mixed-environment trials, the environmental features will be flipped between those that define the separate environments multiple times during each trial. I will infer, based on the population activity, which spatial map is activated at each moment during these mixed-environment trials. In Experiment 1, I will test whether the moment at which one spatial map turns off and the other takes its place occurs non-uniformly over the phases of ongoing theta rhythms. In Experiment 2, I will test whether it is possible to induce the partial retrieval of a spatial map and thereby shift the point at which the alternate spatial map activates as was predicted by my previously proposed model. In Experiment 3, I will test the correspondence between the rat's behavior and which spatial map is activated to test whether such manipulations could serve as a clinical therapy to alter behavior. In Experiment 4, I will explore the relative timing of hippocampal and entorhinal remapping. Under Specific Aim #2, I will use computational modeling to support the empirical work described under Specific Aim #1. Specifically, I will use the same models that generated the predictions that I will address under Specific Aim #1 to simulate the task that I will use to test these predictions. From these simulations, I will generate synthetic data on which I will verify the data analysis methods that I will use to infer which spatial map is active at each moment. These simulations will also allow me to develop the stimulus control protocol, for use during Experiment 2 of Specific Aim #1, that will most reliably generate partial retrieval. Most powerfully, they will allow me to generate additional testable predictions regarding the boundary conditions of the predictions described under Specific Aim #1 and thereby motivate my next series of experiments.