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Neuroscience
BrainBeats 作为开源 EEGLAB 插件,用于联合分析 EEG 和心血管信号
BrainBeats 作为开源 EEGLAB 插件,用于联合分析 EEG 和心血管信号
JoVE Journal
Neuroscience
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JoVE Journal Neuroscience
BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats 作为开源 EEGLAB 插件,用于联合分析 EEG 和心血管信号

Full Text
3,328 Views
08:22 min
April 26, 2024

DOI: 10.3791/65829-v

Cédric Cannard1,2, Helané Wahbeh2,3, Arnaud Delorme1,2,4

1Centre de Recherche Cerveau et Cognition (CerCo), CNRS,Toulouse III University, 2Institute of Noetic Sciences (IONS), 3Department of Neurology,Oregon Health & Science University, 4Swartz Center of Computational Neuroscience (SCCN), INC,UCSD

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Please note that some of the translations on this page are AI generated. Click here for the English version.

Overview

The BrainBeats toolbox is an open-source EEGLAB plugin aimed at facilitating the joint analysis of EEG and cardiovascular (ECG/PPG) signals. This toolbox enhances the study of the brain-heart interplay by providing tools for heartbeat-evoked potential (HEP) assessments and heart artifact extraction from EEG signals, ultimately improving reproducibility and accessibility in research.

Key Study Components

Area of Science

  • Neuroscience
  • Cardiovascular Research
  • Signal Processing

Background

  • Historically, the brain and heart systems have been studied separately, limiting understanding of their interactions.
  • The BrainBeats toolbox addresses this gap by allowing researchers to explore the dynamic interplay between these systems.
  • Insights into cognitive and emotional states' effects on cardiovascular function can lead to new therapeutic interventions.

Purpose of Study

  • To provide a standardized tool for multimodal analysis of EEG and cardiovascular signals.
  • To enhance understanding of brain-heart interactions and their implications for mental and physical health.
  • To improve accessibility and reproducibility in related research.

Methods Used

  • The study utilized the BrainBeats toolbox within the EEGLAB framework on MATLAB.
  • EEG and cardiovascular signals (both ECG and PPG) were analyzed through graphical interfaces to assess HEP and heart artifacts.
  • The protocol included setting paths in MATLAB, loading datasets, and performing feature extraction.
  • Critical steps involved changing power line noise settings and validating outputs throughout the analysis.

Main Results

  • Notable findings included significant heartbeat-evoked oscillations in the alpha band post-heartbeat.
  • Inter-trial coherence analysis indicated no significant phase locking of EEG phase with heartbeats.
  • Key outputs also included HRV features and EEG data, revealing important patterns associated with cardiac rhythms.

Conclusions

  • The BrainBeats toolbox demonstrates potential for bridging the gap between brain and heart research.
  • It enables a more comprehensive understanding of cognitive and emotional influences on cardiovascular health.
  • The insights gained can inform future therapeutic strategies and interventions.

Frequently Asked Questions

What advantages does the BrainBeats toolbox offer?
It provides an open-source platform for integrated analysis of EEG and cardiovascular signals, enhancing reproducibility and accessibility in research.
How do researchers implement the BrainBeats toolbox?
Researchers utilize MATLAB to set up the tool, load EEG and cardiovascular datasets, and perform analyses through a user-friendly GUI.
What types of outcomes can be obtained using this method?
The method allows for the extraction of heartbeat-evoked potentials from EEG, heart artifact analysis, and heart rate variability features.
Can the BrainBeats toolbox be adapted for different studies?
Yes, it can be used to study various aspects of brain-heart interactions and can be tailored for different datasets and research questions.
What are the key limitations of the BrainBeats toolbox?
Potential limitations include reliance on data quality and the necessity for researchers to have a familiarity with MATLAB and EEGLAB.

BrainBeats 工具箱是一个开源的 EEGLAB 插件,旨在联合分析 EEG 和心血管 (ECG/PPG) 信号。它包括心跳诱发电位 (HEP) 评估、基于特征的分析以及从 EEG 信号中提取心脏伪影。该协议将有助于通过两个镜头(HEP 和特征)研究脑心相互作用,从而提高可重复性和可及性。

BrainBeats 工具箱的范围是提供一个开源的自动化工具,用于进行脑心相互作用的研究。它允许研究人员通过标准化信号处理、特征提取、图形用户界面和数据可视化对 EEG 和心血管信号进行多模态分析。由于科学中历史上的还原论方法,大脑和心脏系统已经分离和孤立,导致对它们的相互作用和相互影响的理解有限。

BrainBeats 工具箱旨在弥合这一差距。了解大脑和心脏之间的相互作用使研究人员能够更深入地了解认知和情绪状态如何影响心血管功能,反之亦然。反过来,这些见解可以带来新的治疗干预和治疗方法。

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关键词:脑电图 心电图 HRV 脑心相互作用 开源 EEGLAB 插件 心跳诱发电位 心率变异性 伪影去除 多模态分析 机器学习

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