Measuring, Modeling, and Modulating Cross-Frequency Coupling

项目摘要 虽然节奏是大脑活动的一个突出特征，但节奏在大脑功能中的作用（以及 功能障碍）仍然难以捉摸。已经提出节奏来组织内部的信息传递， 在不同的时间尺度上调节神经兴奋性，节奏也被 提出在这些不同的时间尺度上相互作用，这种现象被称为交叉频率耦合或 CFC。临床和实验观察已经确定了许多不同类型的CFC，如耦合 低频节律的相位和高频节律的振幅（相位-振幅 耦合），或两个不同频率节律的相位之间（相位-相位耦合）。许多功能 CFC的作用已被提出，包括在工作记忆，神经元计算，通信， 学习和情感。尽管CFC的实验证据越来越多，但三个重要挑战 对这一现象理解仍然有限。首先，已经有许多不同的数据分析方法， 这些方法是为确定氟氯化碳的特性而开发的，每种方法通常侧重于一种氟氯化碳。选择一个 不适当的方法削弱了统计功效，并引入了混淆效应的机会。第二、 CFC的分析通常发生在事后，禁止在实验期间调节CFC的机会。 需要新的方法来真实的评估CFC，同时限制潜在混淆的影响。第三、 产生CFC的机制尚不清楚。虽然开发了计算模型来探索这些 机制提供了重要的见解，这些模型主要限于突触机制， 节奏的产生和两种节奏之间的关联。需要新的模型来检查 其他节律和节律产生机制在CFC中的作用。包括更真实的生物学 神经节律模拟的特点促进了对一个新挑战的探索：电刺激如何 调节CFC。在这个项目中，一个跨学科的研究小组，由一个统计学家， 数学家和精神病学家工程师将分析，建模和调制交叉频率耦合。到 为此，该小组将开发和应用适用于CFC真实的时间分析的统计推断框架， 并应用这一框架来分析-并与电刺激调制-从大鼠体内记录 皮层和皮层下。该团队还将开发CFC的计算模型，将观测数据与 细胞机制，并创建可在体内实验中检验的假设。完成建议 这项研究将是朝着更全面地了解交叉频率迈出的重要一步 耦合，并朝着探索和测试其调制的创新方法的系统。

PROJECT SUMMARY Although rhythms are a prominent feature of brain activity, the role of rhythms in brain function (and dysfunction) remains elusive. Rhythms have been proposed to organize information transfer within and between brain regions by modulating neural excitability at different time scales. Rhythms have also been proposed to interact across these different time scales, a phenomenon labeled cross-frequency coupling or CFC. Clinical and experimental observations have identified many different types of CFC, such as coupling between the phase of a low frequency rhythm and the amplitude of a high frequency rhythm (phase-amplitude coupling), or between the phases of two different frequency rhythms (phase-phase coupling). Many functional roles for CFC have been proposed, including in working memory, neuronal computation, communication, learning and emotion. Despite the mounting experimental evidence for CFC, three important challenges remain that limit understanding of this phenomenon. First, many different data analysis methods have been developed to characterize CFC, with each method typically focused on one type of CFC. Choosing an inappropriate method weakens statistical power and introduces opportunities for confounding effects. Second, analysis of CFC typically occurs post hoc, prohibiting opportunities to modulate CFC during an experiment. New methods are needed to assess CFC in real time while limiting the impacts of potential confounds. Third, the mechanisms that produce CFC are not known. While computational models developed to explore these mechanisms provide important insights, these models have been mainly restricted to synaptic mechanisms of rhythm generation and associations between two types of rhythms. New models are needed to examine the role of other rhythms and rhythm generating mechanisms in CFC. Inclusion of more realistic biological features in simulations of neural rhythms facilitates exploration of a new challenge: how electrical stimulation modulates CFC. In this project, an interdisciplinary research group consisting of a statistician, a mathematician, and a psychiatrist-engineer will analyze, model, and modulate cross-frequency coupling. To do so, the team will develop and apply a statistical inference framework suitable for real time analysis of CFC, and apply this framework to analyze - and modulate with electrical stimulation - in vivo recordings from rat cortex and subcortex. The team will also develop computational models of CFC, to link the observed data to cellular mechanisms, and create hypotheses testable in the in vivo experiments. Completion of the proposed research will represent a significant step forward toward a more complete understanding of cross-frequency coupling, and toward a system for exploring and testing innovative methods for its modulation.