Learning, Prefrontal Cortex, and Multiple Memory Systems

学习、前额叶皮质与多重记忆系统 学习要有用，就必须在环境的指导下，对情况的相关特征敏感 机会，并从过去类似情况下的行动中获得信息。换句话说，学习是由 记忆。整合学习和记忆的神经机制在很大程度上是未知的。这个 海马体对学习事实和记忆事件至关重要，新纹状体对习惯很重要 学习，需要前额叶皮质(PFC)来灵活地修改先前学习到的反应。 这些大脑区域中的每一个功能障碍或它们的连接中断都会导致神经精神障碍 包括痴呆症、创伤后应激障碍和精神分裂症。这项提案将调查这些结构如何相互作用 在记忆引导的学习过程中。这些实验是一个更大的研究项目的一部分，这个项目是关于前额叶皮质如何 有助于记忆和认知，将检验这一假设，即PFC、海马和 背外侧纹状体(DLS)回路通过整合抽象记忆为记忆引导学习提供关键机制 规则、事件顺序和刺激导向的行动。具体目标将通过以下方式调查这些机制 结合行为分析、暂时失活、同时记录神经元活动和深度 大脑刺激。目标1将评估PFC、海马体和DLS之间的功能相互作用 在学习过程中，通过暂时中断本地电路。大鼠将被训练成两个行为相同的+ 迷宫任务，一个需要海马体，另一个需要DLS进行初始学习~PFC需要 在它们之间切换。PFC和其他结构之间的相互作用将由临时 MPFC和其他结构中的一个都位于大脑的另一边。如果需要PFC交互 对于灵活的学习，“交叉失活”应该会在转换时产生不对称的损伤 从一个战略到另一个战略。目标2将同时记录三个结构中的神经元活动，以确定 PFC和其他结构内部和之间的活动如何预测学习。我们最近发现了脑电波 海马体中预测记忆提取的模式，并发现DBS既可以模仿这些 模式和恢复记忆，否则健忘的动物。因此，目标3将测试因果关系 通过结合单侧失活、双边记录和DBS来实现PFC和其他结构之间的连接。 在PFC中记录，同时单方面扰乱海马体或DLS的活动，或反之亦然，将决定 每个结构中的正常编码依赖于另一个结构的程度，以及这些相互作用如何影响 学习。DBS的目标模式将用于模拟电路内和电路之间的识别信号，以 确定是否可以克服失活的影响，或者是否可以修改学习策略。结果将是 通过揭示PFC、海马体和DLS如何相互作用来实现记忆引导，推动神经科学的发展 学习，并将为神经精神障碍的新兴治疗提供信息，涉及神经精神障碍的瓦解 前额叶皮质、海马体和纹状体功能，包括精神分裂症和阿尔茨海默病。

Learning, Prefrontal Cortex, and Multiple Memory Systems Learning, to be useful, must be sensitive to the relevant features of situations, guided by environmental opportunities, and informed by past actions in similar circumstances. In other words, learning is guided by memory. The neuronal mechanisms that integrate learning and memory are largely unknown. The hippocampus is crucial for learning facts and remembering events, the neostriatum is important for habit learning, and the prefrontal cortex (PFC) is needed to modify previously learned responses flexibly. Dysfunction of each of these brain regions or their disconnection contributes to neuropsychiatric disorders including dementia, PTSD, and schizophrenia. This proposal will investigate how these structures interact during memory-guided learning. The experiments, part of a larger research program on how prefrontal cortex contributes to memory and cognition, will test the hypothesis that interactions between PFC, hippocampal and dorsolateral striatal (DLS) circuits provide key mechanisms for memory guided learning by integrating abstract rules, event sequences, and stimulus-directed actions. The specific aims will investigate these mechanisms by combining behavior analysis, temporary inactivation, simultaneous recording of neuronal activity, and deep brain stimulation. Aim 1 will assess the functional interactions between the PFC, hippocampus, and DLS the during learning by temporary disruption of local circuits. Rats will be trained to two behaviorally identical + maze tasks, one that requires the hippocampus, the other the DLS for initial learning~ the PFC is needed to switch between them. Interactions between the PFC and the other structures will be tested by temporarily the mPFC and one of the other structures both the on opposite side of the brain. If PFC interactions are required for flexible learning, then the "crossed inactivation" should produce asymmetric impairments in switching from one strategy to the other. Aim 2 will record neuronal activity in the three structures simultaneously to determine how activity within and between the PFC and the other structures predict learning. We recently identified EEG patterns in the hippocampus that predicted memory retrieval, and discovered that DBS could both mimic these patterns and restore memory in otherwise amnestic animals. Aim 3 will therefore test the causal relationships between the PFC and the other structures by combining unilateral inactivation, bilateral recordings, and DBS. Recording in PFC while disrupting activity unilaterally in the hippocampus or DLS, or vice versa, will determine the extent to which normal coding in each structure depends on the other, and how these interactions influence learning. Targetted patterns of DBS will be used to mimic identified signals within and between circuits to determine if the effects of inactivation can be overcome, or learning strategy modified. The outcome will advance neuroscience by revealing how the PFC, hippocampus, and DLS interact to allow memory-guided learning, and will inform emerging treatments for neuropsychiatric disorders that involve disintegration of prefrontal cortex, hippocampal, and striatal functions, including schizophrenia and Alzheimer's disease.