Measuring, Modeling, and Modulating Cross-Frequency Coupling

项目总结 尽管节律是大脑活动的显著特征，但节律在大脑功能中的作用(和 功能障碍)仍然难以捉摸。已经提出了组织内部和内部的信息传输的节奏 通过在不同的时间尺度上调节神经兴奋性，在大脑区域之间进行调节。节奏也一直是 提出在这些不同的时间尺度上相互作用，这种现象被标记为交叉频率耦合或 Cfc。临床和实验观察已经确定了许多不同类型的cfc，例如偶联。 在低频节奏的相位和高频节奏的幅度(相位-幅度)之间 耦合)，或在两个不同频率节律的相位之间(相位-相位耦合)。多种功能 已经提出了氟氯化碳的作用，包括在工作记忆、神经元计算、通信、 学习和情感。尽管有越来越多的氯氟化碳实验证据，但有三个重要的挑战 仍然限制了对这一现象的理解。首先，已经有许多不同的数据分析方法 为确定氯氟化碳的特性而开发，每种方法通常侧重于一种类型的氯氟化碳。选择一个 不恰当的方法削弱了统计能力，并带来了混淆效果的机会。第二, 对氯氟化碳的分析通常是在特殊情况下进行的，禁止在实验期间调节氯氟化碳的机会。 需要新的方法来实时评估氯氟化碳，同时限制潜在混杂的影响。第三, 产生氯氟化碳的机制尚不清楚。虽然计算模型的开发是为了探索这些 机制提供了重要的见解，这些模型主要局限于突触机制 节奏生成和两种类型节奏之间的关联。需要新的模型来检查 其他节律和节律生成机制在心力衰竭中的作用。包含更现实的生物学 神经节律模拟的特征有助于探索一项新的挑战：电刺激如何 调节氯氟烃。在这个项目中，一个由统计学家、 数学家和精神病学家兼工程师将对交叉频率耦合进行分析、建模和调整。至 为此，该小组将开发和应用一个适用于氟氯化碳实时分析的统计推断框架， 并将该框架应用于分析-并用电刺激调制-来自大鼠的活体记录 皮质和皮质下。该团队还将开发氯氟化碳的计算模型，将观测数据与 细胞机制，并创建可在活体实验中验证的假说。完成拟议的 研究将代表着朝着更全面地理解交叉频率迈出的重要一步 耦合，并朝向用于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.