Multi-scale analysis and computational modeling of intrinsic coupling modes in the ferret brain

内在生成的动态耦合构成了大脑活动的一个关键特征。现有的证据表明存在两种类型的固有耦合模式（ICM）：相位ICM来自振荡信号的相位耦合，而包络ICM来自信号包络的耦合波动。我们的总体目标是系统地分析和计算模型，这些类型的ICMs在雪貂的大脑。相位ICM被广泛研究神经生理学，但尚未很好地了解其结构连接体的关系建模方面。被膜ICM已被广泛探讨在连接模型，但没有很好地研究与神经生理学的方法。这些ICM之间的相互作用几乎完全未被探索，它们尚未在相同的数据集中进行系统分析。目前还没有关于雪貂脑中ICM的计算建模结果的报道。使用结构和功能的连接数据集，包括大规模的皮层电图（ECoG-）记录，我们以前在雪貂中获得的，我们将分析相位和包络ICM，并提供一个连贯的计算建模方法的基础上的结构连接。该项目将追求以下主要目标：（1）我们将通过结合神经生理数据分析和计算建模来研究相位ICM;（2）我们将分析和建模包络ICM;（3）我们将研究相位和包络ICM之间发生的相互作用。这些目标反映在我们的工作方案中。工作包1将集中在相位ICMs的结构连接体的关系，在时空变化的相位耦合，在相位ICMs与状态变化相关的变化，以及相位ICMs是否确定传播波和预测感官刺激处理。工作包2将研究是否信封ICM不同的结构连接体从相位ICM的关系，分析信封ICM的可变性和他们的调制状态变化，并测试是否在刺激前活动的信封ICM预测感觉处理和形成传播波。工作包3将研究这两种类型的ICM之间的关系，并测试它们是否在状态变化或刺激引起的网络扰动的背景下相互预测。我们将使用信号相位和包络之间的关系来量化大规模的连通性，并研究ICM与临界等动态现象的关系。作为TheVirtualBrain平台的一部分，我们将提供本项目中使用的数据和模型的开放访问存储库（虚拟雪貂），这将促进计算连接组学优先领域的数据共享和协作。该提案通过对复杂网络连接进行系统分析，并开发计算模型来解释网络结构如何产生神经动力学，从而解决了SPP 2041的关键主题。

Intrinsically generated dynamic coupling constitutes a key feature of brain activity. Available evidence suggests the existence of two types of intrinsic coupling modes (ICMs): Phase ICMs arise from phase coupling of oscillatory signals, whereas envelope ICMs result from coupled fluctuations of signal envelopes. Our overall goal is to systematically analyze and computationally model these types of ICMs in the ferret brain. Phase ICMs are widely studied neurophysiologically, but are not yet well understood in terms of modeling their relation to the structural connectome. Envelope ICMs have been extensively explored in connectomic models but are not well investigated with neurophysiological approaches. The interaction between these ICMs is almost completely unexplored and they have not yet been analyzed systematically in the same datasets. No computational modeling results have been reported for ICMs in the ferret brain. Using structural and functional connectomic datasets including large-scale electrocorticographic (ECoG-) recordings that we have previously acquired in the ferret, we will analyze both phase and envelope ICMs and provide a coherent computational modeling approach based on the structural connectome. The project will pursue the following key aims: (1) We will investigate phase ICMs by combining analysis of neurophysiological data and computational modeling; (2) we will analyze and model envelope ICMs; (3) we will investigate which interactions occur between phase and envelope ICMs. These aims map onto our work programme. Workpackage 1 will focus on the relation of phase ICMs to the structural connectome, on the spatiotemporal variability of phase coupling, on changes in phase ICMs associated with state changes, and on whether phase ICMs determine spreading waves and predict sensory stimulus processing. Workpackage 2 will study whether envelope ICMs differ in their relation to the structural connectome from phase ICMs, analyze the variability of envelope ICMs and their modulation by state changes, and test whether envelope ICMs in pre-stimulus activity predict sensory processing and form spreading waves. Workpackage 3 will investigate the relation between both types of ICMs and test whether they mutually predict each other in the context of state changes or network perturbation by stimuli. We will use the relation between signal phases and envelopes for quantifying large-scale connectivity, and investigate the relation of ICMs to dynamic phenomena such as criticality. We will provide an open-access repository of data and models used in this project (The Virtual Ferret) as part of TheVirtualBrain platform, which will facilitate data sharing and collaboration in the priority area of computational connectomics. The proposal addresses key themes of SPP 2041 by undertaking systematic analyses of complex network connectivity and developing computational models for explaining how network structure gives rise to neural dynamics.