Prospective Coding and Memory Retrieval

前瞻性编码和记忆检索

• 批准号: 10323036
• 负责人: Matthew L Shapiro
• 金额: $ 40.5万
• 依托单位: ALBANY MEDICAL COLLEGE
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-02-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323036
• 关键词: Affect; Area; Axon; Basal Nucleus of Meynert; Behavior; Behavioral; Bilateral; Brain; Cannulas; Code; Cognitive; Communication; Data; Discrimination; Electrodes; Episodic memory; Fimbria of hippocampus; Functional disorder; Goals; Halorhodopsins; Hippocampus (Brain); Impairment; Implant; Infusion procedures; Learning; Light; Link; Location; Medial; Memory; Mental Depression; Mental disorders; Muscimol; Names; Neurons; Neuropsychology; Operative Surgical Procedures; Outcome; Output; Pacemakers; Pattern; Performance; Phase; Physiological; Population; Prefrontal Cortex; Presynaptic Terminals; Rattus; Recording of previous events; Reuniens Thalamic Nucleus; Reversal Learning; Rewards; Role; Schizophrenia; Septal Area; Septal Nuclei; Series; Space Perception; Specific qualifier value; Stimulus; Structure; Temporal Lobe; Testing; Thalamic structure; Time; Training; Virus; autism spectrum disorder; base; density; design; expectation; experience; experimental study; flexibility; improved; memory retrieval; network architecture; neuromechanism; neurotransmission; optical fiber; outcome prediction; predictive signature; prospective; relating to nervous system; severe psychiatric disorder; transmission process; vector

Memory evolved to predict outcomes, but the neural mechanisms that link outcomes and remembered episodes are unclear. Episodic memory requires the hippocampus (HPC), working flexibly with memory requires the prefrontal cortex (PFC), and both structures are needed for tracking outcomes that change over space or time. Spatial reversal learning entails learning to stop approaching a previously rewarded location and instead approaching a previously unrewarded one. The PFC and HPC are needed for spatial reversal learning, and each structure supports different functions. HPC inactivation impairs all spatial learning, whereas PFC inactivation spares discrimination but impair reversal learning. Different PFC circuits guide reversals depending on outcome history: medial prefrontal cortex (mPFC) supports switching between rapidly changing goals, orbitofrontal cortex (OFC) supports switching from one well-established goal to another. Neural representations in each structure predict choices that correspond with the inactivation effects: OFC predictions develop relatively slowly across episodes, while mPFC and HPC predictions develop quickly. The proposed experiments combine local circuit manipulations with high density unit recording in rats performing spatial reversals to test the extent to which coordinated HPC and PFC activity associates episodes and outcomes. Aim 1 will test how outcome history affects reversal strategies and functional interactions between PFC and CA1 by disrupting local circuits. Groups of rats will be trained in a HPC-dependent spatial task followed by reversals designed to require either OFC or mPFC while local OFC or mPFC circuits are temporarily inactivated. To investigate the required circuitry, mPFC and OFC will be infected with halorhodopsin (NpHR3.0) or channelrhodopsin (ChR2) containing viruses and PFC axon terminals will be modulated by light delivered to the n. reuniens, a thalamic relay between PFC and CA1. The results will determine if mPFC and OFC contribute independently or interactively to spatial outcome predictions, and test the extent to which these interactions require the n. reuniens. Aim 2 will investigate how outcome history affects PFC and CA1 coding interactions by recording simultaneously in the three regions or inactivating one while recording the other two as rats perform the tasks described in Aim 1. The results will identify neuronal signals and CA1 interactions with mPFC or OFC that predict outcome guided memory representations. Aim 3 will test PFC-HPC communication mechanisms by modulating the temporal coordination of PFC and HPC activity. Electrically stimulating the fimbria fornix synchronizes local field potentials in widespread cortical and subcortical networks and improves spatial learning and memory. “Pacemaker” stimulation of the medial septal area (MSA) and nucleus basalis modulate HPC and PFC synchrony independently. Enhancing or disrupting learning-related activity patterns recorded in Aim 2 will test if network synchrony is needed to link outcomes with memory.

记忆的进化是为了预测结果，但连接结果和记忆的神经机制 事件的情节尚不清楚。情节记忆需要海马体(HPC)，与记忆一起灵活工作 需要前额叶皮质(PFC)，这两个结构都需要跟踪结果的变化 空间或时间。空间反转学习需要学习停止接近之前获得奖励的位置，并 取而代之的是接近一个以前没有回报的项目。空间反转学习需要PFC和HPC， 并且每个结构支持不同的功能。HPC失活会损害所有的空间学习，而PFC 失活可以避免辨别，但会损害反转学习。不同的PFC电路引导反转取决于 关于结果史：内侧前额叶皮质(MPFC)支持在快速变化的目标之间切换， 眼眶额叶皮质(OFC)支持从一个既定目标切换到另一个目标。神经表示法 在每个结构中预测与失活效果相对应的选择：OFC预测 跨剧集的预测相对较慢，而mPFC和HPC预测发展得很快。建议数 局部电路操作与高密度单位记录相结合的大鼠空间操作实验 逆转以测试协调的HPC和PFC活动将事件和结果联系在一起的程度。 目标1将测试结果历史如何影响PFC和PFC之间的逆转策略和功能相互作用 通过中断本地电路来实现CA1。一组大鼠将接受依赖于HPC的空间任务的训练，然后 反转需要OFC或mPFC，而本地OFC或mPFC电路暂时 已停用。为了调查所需的电路，mPFC和OFC将感染卤视紫质 (NpHR3.0)或含有病毒的通道视紫红质(ChR2)和PFC轴突终末将受光调制 传递给北极星，这是PFC和CA1之间的丘脑中继站。结果将决定mPFC和 OFC独立或交互地对空间结果预测做出贡献，并测试这些预测的程度 相互作用需要n.重聚。目标2将调查结果历史如何影响PFC和CA1编码 通过在三个区域中同时记录或在记录另外两个区域时停用一个区域来进行交互 当大鼠执行目标1中描述的任务时。结果将识别神经元信号和CA1相互作用 具有预测结果引导的记忆表示的mPFC或OFC。AIM 3将测试PFC-HPC 通过调节PFC和HPC活动的时间协调来实现沟通机制。电学上 刺激穹隆海马伞在广泛的皮质和皮质下网络中同步局部场电位 并改善空间学习和记忆。起搏器刺激内侧隔区(MSA)和 基底核独立地调节HPC和PFC的同步性。增强或破坏与学习相关的内容 Aim 2中记录的活动模式将测试是否需要网络同步来将结果与记忆联系起来。

项目成果

Time and again.

一次又一次。

• DOI: 10.1016/j.neuron.2014.02.034
• 发表时间: 2014
• 期刊: Neuron
• 影响因子: 16.2
• 作者: Shapiro,MatthewL

Goal Choices Modify Frontotemporal Memory Representations.

目标选择会改变额颞叶记忆表征。

• DOI: 10.1523/jneurosci.1939-22.2023
• 发表时间: 2023
• 期刊: The Journal of neuroscience : the official journal of the Society for Neuroscience
• 作者: Srinivasan,Aditya;Riceberg,JustinS;Goodman,MichaelR;Srinivasan,Arvind;Guise,KevinG;Shapiro,MatthewL
• 通讯作者: Shapiro,MatthewL

An in silico model for determining the influence of neuronal co-activity on rodent spatial behavior.

用于确定神经元协同活动对啮齿动物空间行为影响的计算机模型。

• DOI: 10.1016/j.jneumeth.2022.109627
• 发表时间: 2022
• 期刊: Journal of neuroscience methods
• 影响因子: 3
• 作者: Srinivasan,Aditya;Srinivasan,Arvind;Riceberg,JustinS;Goodman,MichaelR;Guise,KevinG;Shapiro,MatthewL
• 通讯作者: Shapiro,MatthewL

Hippocampal signals modify orbitofrontal representations to learn new paths.

海马信号修改眶额表征以学习新路径。

• DOI: 10.1016/j.cub.2022.06.010
• 发表时间: 2022
• 期刊: Current biology : CB
• 作者: Riceberg,JustinS;Srinivasan,Aditya;Guise,KevinG;Shapiro,MatthewL
• 通讯作者: Shapiro,MatthewL