Tools for parameterizing and visualizing electrophysiological rhythmic and arrhythmic features

项目摘要 认知需要跨多个大脑区域的神经集合的动态协调。这是 最大的神经科学问题：神经群体如何在大脑中形成短暂的通信网络？ 认知服务？发生这种情况的一个令人兴奋的候选机制是通过神经元的耦合， 大脑区域之间的振荡。这些振荡是电生理学的普遍特征， 跨越物种。尽管他们进行了广泛的研究，但最近的工作突出了分析振荡的许多陷阱， 主要围绕三个主要问题：1）振荡应该相对于非周期（1/f）进行测量 因为严格地说，振荡被定义为功率谱的任何区域， 高于1/f背景，1/f背景本身已被证明与认知和疾病都是动态的; 2)大多数用于提取和量化振荡的工具都假定它们是正弦的，尽管事实上 他们很少是。此外，那些非正弦特征可以携带关键的生理信息; 3） 传统的方法可以混淆突发和非突发振荡，尽管迅速增加的证据， 这两种振荡模式是不同的，甚至可能发挥不同的功能作用。 在这个项目中，我们将大大扩展我的实验室开发的分析软件和平台，以测试 我们的工具对真实的和模拟数据的有效性。这些工具是专门为解决 上面概述的三个主要振荡分析问题。经过测试后，这些分析工具箱将 移动到网上，允许基于云的大规模分析振荡，1/f背景，非正弦 波形特征和振荡爆发。然后，我们将利用新的、动态的、交互式的浏览器 用于数据处理和探索的可视化工具。所有这些都将使用开源工具完成， 软件开发的行业标准，以透明的方式。 1

Project Summary Cognition requires the dynamic coordination of neural ensembles across multiple brain regions. This is one of the biggest neuroscientific questions: how do neural populations form transient communication networks in the service of cognition? One exciting candidate mechanism by which this occurs is through the coupling of neural oscillations between brain regions. These oscillations are a ubiquitous feature of electrophysiology, occurring across species. Despite their wide study, recent work has highlighted many pitfalls in analyzing oscillations, largely centered around three major issues: 1) Oscillations should be measured relative to the aperiodic (1/f) background because, strictly speaking, oscillations are defined as any regions of the power spectrum that rise above the 1/f background, which has itself been shown to be dynamic in relation to both cognition and disease; 2) Most tools for extracting and quantifying oscillations assume that they are sinusoidal despite the fact that they rarely ever are. Further, those non-sinusoidal features may carry critical physiological information; 3) Traditional methods can conflate bursting and non-bursting oscillations, despite the rapidly mounting evidence that the two oscillatory modes are distinct, and may even play different functional roles. In this project we will significantly expand upon analytic software and platforms, developed by my lab, to test the validity of our tools against real and simulated data. These tools are designed specifically to address the three major oscillation analysis issues outlined above. After testing, these analytic toolboxes will then be moved online, to permit cloud-based, large-scale analysis of oscillations, the 1/f background, non-sinusoidal waveform features, and oscillatory bursts. We will then leverage new, dynamic, interactive in-brower visualization tools for data processing and exploration. All of these will be done using open-source tools, built to industry standards of software development, in a transparent manner. 1