Establishing a spatial map of dopamine reward prediction error computations and their function in distinct associative learning processes across the striatum: a methodological framework

建立多巴胺奖励预测误差计算的空间图及其在纹状体不同联想学习过程中的功能：方法框架

• 批准号: 10725129
• 负责人: Eleanor Brown
• 金额: $ 3.17万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10725129
• 关键词: 3-Dimensional; Affect; Anatomy; Animals; Area; Association Learning; Basal Ganglia; Behavior; Behavioral; Behavioral Model; Behavioral Paradigm; Boston; Brain region; Characteristics; Choice Behavior; Chronic; Classification; Complex; Corpus striatum structure; Cues; Development; Devices; Diagnostic; Disease; Dopamine; Educational process of instructing; Etiology; Fiber; Fiber Optics; Fostering; Functional disorder; Future; Goals; Heterogeneity; Impairment; Investigation; Learning; Light; Location; Maps; Mental disorders; Mentorship; Methodology; Methods; Modeling; Mus; Neurosciences; Obsessive-Compulsive Disorder; Operant Conditioning; Optics; Outcome; Parkinson Disease; Pattern; Photometry; Process; Recording of previous events; Research; Resolution; Response to stimulus physiology; Rewards; Schizophrenia; Shapes; Signal Transduction; Site; Stimulus; Symptoms; Techniques; Testing; Traineeship; Training; Training Support; Universities; Update; Variant; addiction; behavior test; cell type; collaborative environment; design; digital; dopaminergic neuron; effective therapy; experience; flexibility; improved; in vivo; nervous system disorder; neural circuit; optical fiber; optogenetics; postsynaptic; programs; response; segregation; spatiotemporal; technology development; tool

PROJECT SUMMARY/ABSTRACT. Dopamine (DA) signaling in the striatum, the main input to the basal ganglia, is critical for instrumental learning, a process involving associations of stimuli, responses, and outcomes. DA dysfunction results in diverse symptoms in disorders such as obsessive-compulsive disorder, Parkinson’s Disease, and addiction, which are often attributed to an imbalance in distinct instrumental learning processes. Anatomically segregated subregions of the striatum are thought to support stimulus-outcome (S-O), stimulus- response (S-R), and response-outcome (R-O) associations. Further, while the dorsomedial striatum (DMS) is necessary for flexible goal-directed behavior, the dorsolateral striatum (DLS) supports automatic, outcome- independent habitual behavior. While dopamine (DA) is typically thought to encode a reward prediction error (RPE), a teaching signal which drives associative learning, studies suggest that DA release dynamics vary depending on the target region. However, it is unknown how natural spatiotemporal DA release dynamics support learning distinct stimulus, response, and outcome associations. These gaps hinder the development of targeted diagnostics and treatments for dopamine-dysfunction affecting distinct striatum regions. This proposed project will make strides toward understanding the functional and computational significance of spatially varying DA dynamics in distinct associative learning processes. A behavioral paradigm which requires mice to switch from a cue-dependent S-R strategy to a cue-independent strategy based on recent actions and outcomes will enable classification of behavior strategy across timescales. This behavioral paradigm will be combined with a new multi optical fiber photometry method to record DA release dynamics throughout the volume of the striatum as mice learn and update distinct stimulus, response and outcome contingencies. This new large-scale, cell-type specific recording method will be applied to establish a spatial map of distinct DA RPE correlates and can be adapted to record distributed cell-type specific dynamics of any brain region with high spatiotemporal resolution. Finally, this method will be advanced with a digital mirror device (DMD) to target light to large, yet spatially precise, regions of the striatum for optogenetic manipulation which mimics the spatial scale and resolution of natural DA release dynamics. Completion of this project will support practical and theoretical training in three main areas: behavioral testing and analysis, functional circuit analysis, and technology development. Dr. Mark Howe (sponsor) will provide mentorship and training in in vivo analysis of neural circuits and dynamics. Dr. David Boas (co-sponsor), the director of the Neurophotonics Center at Boston University, will provide training in the concepts and techniques used for optical neuro-engineering, which will augment training supported by the NSF Neurophotonics National Research Traineeship Program. The Graduate Program for Neuroscience (GPN) at Boston University will provide additional training while fostering a collaborative and interdisciplinary environment.

项目摘要/摘要。纹状体中的多巴胺（DA）信号传导，是基本的主要输入 神经节对于工具学习至关重要，这是一个涉及刺激，反应和结果的过程。 DA功能障碍会导致诸如强迫症，帕金森氏症等疾病中的潜水员符号 疾病和成瘾，通常归因于不同工具学习过程中的失衡。 纹状体的解剖分离子区域被认为支持刺激结果（S-O），刺激 - 响应（S-R）和响应结果（R-O）关联。此外，虽然背侧纹状体（DMS）为 对于灵活的目标指导行为所必需的，背纹纹状体（DLS）支持自动，结果 - 独立的习惯行为。通常认为多巴胺（DA）编码奖励预测错误 （RPE），一种驱动关联学习的教学信号，研究表明DA释放动态变化 取决于目标区域。但是，尚不清楚自然时空DA释放动力学如何支持 学习独特的刺激，反应和结果关联。这些差距阻碍了目标的发展 多巴胺功能的诊断和治疗，影响不同的纹状体区域。 这个拟议的项目将迈向理解功能和计算 在不同的关联学习过程中空间变化的DA动力学的重要性。行为范式 这要求小鼠从基于最新 行动和结果将使行为策略跨时标进行分类。这种行为范式 将与一种新的多光纤光度法方法结合在一起，以记录整个释放动力学 随着小鼠的学习和更新不同的刺激，反应和结果突发事件，纹状体的体积。 这种新的大规模，细胞类型的特定记录方法将应用于建立不同DA的空间图 RPE相关，可以适应与任何大脑区域的分布的细胞类型特定动力学一起 高时空分辨率。最后，该方法将使用数字镜设备（DMD）来提前 光到大但在空间上精确的纹状体区域，用于光学遗传操作，模仿空间 自然DA释放动力学的比例和分辨率。 该项目的完成将支持三个主要领域的实用和理论培训：行为 测试和分析，功能电路分析和技术开发。马克·豪（Mark Howe）（赞助商）将 在神经回路和动力学的体内分析中提供精神和培训。 David Boas博士（共同发起人）， 波士顿大学神经素养中心主任将提供概念的培训 用于光学神经工程的技术，该技术将增加NSF支持的培训 Neurophotonics国家研究实习计划。神经科学研究生课程（GPN） 波士顿大学将在培养协作和跨学科环境的同时提供额外的培训。