Bridging Scales to Understand Endogenous Neuromodulation and its Regulation

桥接尺度以了解内源性神经调节及其调节

• 批准号: 10567073
• 负责人: Rachel Alison Adcock
• 金额: $ 59.34万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-08 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10567073
• 关键词: Address; Back; Behavior; Behavioral; Blood - brain barrier anatomy; Brain; Cell Nucleus; Cognition; Cognitive; Complement; Cues; Decision Making; Disadvantaged; Dissociation; Dopamine; Dopaminergic Agents; Education; Evolution; Foundations; Functional Magnetic Resonance Imaging; Goals; Grant; Hippocampus; Human; Imagery; Individual; Informal Social Control; Intervention; Knowledge; Learning; Machine Learning; Measures; Medial; Memory; Mental Health; Mental disorders; Methods; Midbrain structure; Modeling; Motivation; Neuromodulator; Neurons; Neurotransmitters; Norepinephrine; Participant; Pattern; Pharmaceutical Preparations; Pharmacologic Substance; Pharmacotherapy; Physiological; Positioning Attribute; Regulation; Resources; Serotonin; Signal Transduction; Specific qualifier value; Statistical Models; Stream; System; Temporal Lobe; Time; Training; Up-Regulation; Work; analytical method; basal forebrain; clinical application; financial incentive; improved; learned behavior; locus ceruleus structure; method development; motivated behavior; multidimensional data; multilevel analysis; neural; neural model; neural network; neurofeedback; neuroimaging; neuroregulation; neurotransmitter release; novel; resilience; response; side effect; spatiotemporal; support network; tool

Neuromodulatory nuclei detect and transform brain network activity into simpler signals, then send neurotransmitters back out to large-scale brain networks to change their function. Such nuclei are centrally implicated in mental disorders and adaptive resilience, and their regulation remains an untapped resource for interventions. The purpose of this grant is to understand how neuromodulatory nuclei detect and in turn influence distributed patterns of brain activity to impact behavior. To understand their regulation and effects on brain function, the investigative team has developed novel neuroimaging, behavioral, and analytic methods. These methods include: training participants to endogenously self-regulate dopaminergic midbrain, isolating distinct streams of information in the midbrain over multiple timescales, distinguishing behavioral contexts and network effects associated with univariate activation in neuromodulatory nuclei, and finally relating midbrain activation to memory-conducive states in medial temporal lobe memory systems. Our team has recently developed whole-brain analyses of real-time fMRI during midbrain neurofeedback and machine-learning tools for characterizing nonlinear latent dynamics from high-dimensional data. Now, with these tools, we can relate midbrain activation to whole brain states. We hypothesize 1) that distinct distributed spatiotemporal patterns precede and follow midbrain univariate activation, specify it uniquely among neuromodulatory nuclei, and distinguish sustained from transient midbrain responses; 2) that the evolution of these patterns over the training session will predict learning to upregulate midbrain, and 3) that endogenous midbrain regulation will predict brain and behavioral effects we and others have previously shown to be associated with midbrain activation and dopamine function. If the aims of this project are achieved, we will have introduced a multi-level model of the neural states that support midbrain activation, a complement of methods for regulating midbrain noninvasively, and an improved understanding of its impact on learning and motivated behavior. Reliable cognitive strategies for dynamically and selectively fine-tuning neural networks to suit behavioral contexts will lay the foundation for a wide array of interventions across educational and clinical applications.

神经调制核团检测并将大脑网络活动转换为更简单的信号，然后发送 神经递质返回到大规模的大脑网络以改变其功能。这样的原子核集中在 与精神障碍和适应能力有关，它们的调节仍然是一种未开发的资源 干预措施。这项资助的目的是了解神经调节核是如何检测并反过来 影响大脑活动的分布模式，从而影响行为。要了解它们的监管和对 在大脑功能方面，研究小组开发了新的神经成像、行为和分析方法。 这些方法包括：训练参与者内源性自我调节多巴胺能中脑，分离 在多个时间尺度上，中脑中的不同信息流，区分行为背景和 与神经调节核团单变量激活相关的网络效应，最终与中脑有关 内侧颞叶记忆系统中有利于记忆的状态的激活。我们的团队最近 在中脑神经反馈和机器学习工具期间开发实时fMRI的全脑分析 用于从高维数据中表征非线性潜在动力学。现在，有了这些工具，我们可以联系 中脑激活到全脑状态。我们假设1)不同的分布时空模式 在中脑单变量激活之前和之后，在神经调节核团中唯一地指定它，以及 区分持续的和短暂的中脑反应；2)这些模式在 训练课程将预测学习如何上调中脑，以及3)内源性中脑调节将 预测我们和其他人之前已经证明与中脑有关的大脑和行为影响 激活和多巴胺功能。如果这个项目的目标实现了，我们将引入一个多层次的 支持中脑激活的神经状态模型，是调节中脑的方法的补充 非侵入性，以及对其对学习和动机行为的影响的更好的理解。可靠 动态和选择性地微调神经网络以适应行为环境的认知策略将 为广泛的教育和临床应用干预措施奠定基础。