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所在平台: Udemy |
课程主页: https://www.udemy.com/course/eegerp-analysis-with-python-and-mne-an-introductory-course/
课程评论：没有评论
**课程名称：** EEG/ERP 分析：Python 与 MNE 入门课程 **课程概述：** 本课程适合 EEG 数据分析领域的初学者，旨在帮助您掌握 EEG 数据分析的基础知识。您将从 EEG 历史的起源一路学到如今的前沿技术。 **主要内容：** * **EEG 数据记录与质量：** 学习高质量 EEG 数据记录的要点，了解构成优质 EEG 数据的标准。 * **信号去噪：** 掌握伪迹（artifact）的基础知识，识别不同类型的噪声，并通过多种滤波技术进行实际的噪声去除。 * **时域与频域分析：** 深入理解频域（包括不同脑电频率）和时域分析，同时探索事件相关电位 (ERPs) 和时频分析。 * **PythonEEG 分析基础：** 熟悉 Python 基础、ANACONDA 安装、编码基础和数据绘图。安装 MNE (MNE-Python) 并开始您的 EEG 分析实践。 * **MNE-Python预处理：** 使用 MNE-Python 进行 EEG 数据预处理，包括数据导入、滤波、排除坏道以及进行独立成分分析 (ICA) 以去除噪声。 * **Python 与 MNE 频域分析：** 利用 MNE 的 PSD 函数进行频域分析，创建精美的频段图和地形图，探索 EEG 数据中的奥秘。 * **重要 ERPs 探索：** 回顾 P300、N170 以及与语言相关的 ERPs 等关键成分，理解其意义和在 EEG 分析中的应用。 * **Python 与 MNE ERP 及时频分析：** 掌握使用 Python 可视化 ERPs 的方法，运用 MNE 解释 ERPs，并深入学习时频分析的绘图与解读。 **课程特色：** 本课程专为初学者设计，提供从基础到高级 EEG 分析技术的平滑过渡。通过实际的 Python 编码练习和 MNE-Python 的实践案例，您将获得在 EEG 数据分析领域至关重要的实践技能。 **加入我们，一同揭开 EEG 的奥秘！立即报名，开启您的 EEG 分析之旅。**
Whether you're a novice in the field or looking to enhance your skills, this course is your gateway to understanding the basics of EEG data analysis.A Journey Through EEG History: Join us on a fascinating exploration of the origins of EEG data, from its introduction to the cutting-edge techniques used today.Recording EEG Data: Learn the essentials of recording high-quality EEG data and what constitutes good EEG data. Learn the basics of artifacting, recognizing different types of noises, and witness noise reduction in action through various filtering techniques.Frequency and Time Domain Analyses: Demystify the complexities of frequency and time domain analyses. Understand different brain frequencies, conduct frequency analysis, explore time domain analysis and Event-Related Potentials (ERPs), and venture into time-frequency analysis.Python for EEG Analysis: Familiarize yourself with Python basics, ANACONDA installation, coding fundamentals, and data plotting. Install MNE (MNE-Python) and kickstart your journey into EEG analysis.MNE-Python Pre-processing: Explore MNE-Python for pre-processing EEG data. Import data, gain an overview, implement filtering, reject bad channels, and perform Independent Component Analysis (ICA) for noise removal.Frequency Analysis with Python and MNE: Utilize MNE's PSD function for frequency analysis. Create visually stunning frequency band plots and topographic maps to explore the mysteries hidden within EEG data.Exploring Important ERPs: Review essential Event-Related Potentials (ERPs), such as the P300 and N170 components, along with language-related components. Understand their significance and applications in EEG analysis.ERP and Time-Frequency Analysis in Python and MNE: Master the art of visualizing ERPs using Python. Leverage MNE for interpreting ERPs and delve into plotting and interpreting time-frequency analyses.Why Choose This Course:This course is designed for beginners, providing a seamless transition from the basics to advanced EEG analysis techniques. With hands-on Python coding exercises and practical examples using MNE-Python, you'll gain practical skills that are essential for anyone seeking proficiency in EEG data analysis.Join us on this educational journey, and let's unravel the mysteries of EEG together! Enroll now to kickstart your EEG analysis adventure.
