Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Centre Hospitalier Le Vinatier, Bâtiment, Boulevard Pinel, Bron, France.
Comput Intell Neurosci. 2011;2011:158970. doi: 10.1155/2011/158970. Epub 2011 Apr 20.
The recent surge in computational power has led to extensive methodological developments and advanced signal processing techniques that play a pivotal role in neuroscience. In particular, the field of brain signal analysis has witnessed a strong trend towards multidimensional analysis of large data sets, for example, single-trial time-frequency analysis of high spatiotemporal resolution recordings. Here, we describe the freely available ELAN software package which provides a wide range of signal analysis tools for electrophysiological data including scalp electroencephalography (EEG), magnetoencephalography (MEG), intracranial EEG, and local field potentials (LFPs). The ELAN toolbox is based on 25 years of methodological developments at the Brain Dynamics and Cognition Laboratory in Lyon and was used in many papers including the very first studies of time-frequency analysis of EEG data exploring evoked and induced oscillatory activities in humans. This paper provides an overview of the concepts and functionalities of ELAN, highlights its specificities, and describes its complementarity and interoperability with other toolboxes.
最近计算能力的大幅提升促进了方法学的发展和先进信号处理技术的进步，这些在神经科学领域发挥着关键作用。特别是，脑信号分析领域呈现出对大数据集进行多维分析的强烈趋势，例如对高时空分辨率记录进行单次试验时频分析。在这里，我们描述了免费的 ELAN 软件包，它为包括头皮脑电图（EEG）、脑磁图（MEG）、颅内 EEG 和局部场电位（LFPs）在内的电生理数据提供了广泛的信号分析工具。ELAN 工具箱基于里昂大脑动力学和认知实验室 25 年的方法学发展，在许多论文中都有应用，包括最早研究探索人类诱发性和诱导性振荡活动的 EEG 数据时频分析的论文。本文概述了 ELAN 的概念和功能，突出了其特点，并描述了它与其他工具箱的互补性和互操作性。
