BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Summary

The BrainBeats toolbox is an open-source EEGLAB plugin designed to jointly analyze EEG and cardiovascular (ECG/PPG) signals. It includes heartbeat-evoked potentials (HEP) assessment, feature-based analysis, and heart artifact extraction from EEG signals. The protocol will aid in studying brain-heart interplay through two lenses (HEP and features), enhancing reproducibility and accessibility.

Abstract

The interplay between the brain and the cardiovascular systems is garnering increased attention for its potential to advance our understanding of human physiology and improve health outcomes. However, the multimodal analysis of these signals is challenging due to the lack of guidelines, standardized signal processing and statistical tools, graphical user interfaces (GUIs), and automation for processing large datasets or increasing reproducibility. A further void exists in standardized EEG and heart-rate variability (HRV) feature extraction methods, undermining clinical diagnostics or the robustness of machine learning (ML) models. In response to these limitations, we introduce the BrainBeats toolbox. Implemented as an open-source EEGLAB plugin, BrainBeats integrates three main protocols: 1) Heartbeat-evoked potentials (HEP) and oscillations (HEO) for assessing time-locked brain-heart interplay at the millisecond accuracy; 2) EEG and HRV feature extraction for examining associations/differences between various brain and heart metrics or for building robust feature-based ML models; 3) Automated extraction of heart artifacts from EEG signals to remove any potential cardiovascular contamination while conducting EEG analysis. We provide a step-by-step tutorial for applying these three methods to an open-source dataset containing simultaneous 64-channel EEG, ECG, and PPG signals. Users can easily fine-tune parameters to tailor their unique research needs using the graphical user interface (GUI) or the command line. BrainBeats should make brain-heart interplay research more accessible and reproducible.

Introduction

For a long time, the reductionist approach has dominated scientific inquiry in human physiology and cognition. This approach involved dissecting complex bodily and mental processes into smaller, more manageable components, allowing researchers to focus on individual systems in isolation. This strategy arose due to the challenges in studying the intricate and interconnected nature of the human body and mind¹. Reductionism has been instrumental in understanding individual subsystems in isolation, such as elucidating the role of ion channels and action potentials for neural² or cardiac³ communication....

Protocol

Informed consent was obtained from each participant, and the Ural Federal University ethics committee approved the experimental protocol.

1. BrainBeats requirements

1. Install MATLAB and EEGLAB on the computer. EEGLAB can be downloaded at https://github.com/sccn/eeglab and unzipped (or cloned for Git users) anywhere on the computer. See the GitHub page for more details on installation. 
2. Add the path to the EEGLAB folder in MATLAB's home panel b.......

Discussion

Critical steps in the protocol
Critical steps are described in steps 1.1-1.4. Warnings and error messages are implemented at various places in the toolbox to help users understand why they may encounter issues (e.g., electrode locations not loaded in the EEG data, file length being too short for calculating a reliable measure of ultra-low frequency HRV, signal quality being too low for any reliable analysis, etc.). Each function is documented for advanced users, and the parameters can be easily fin.......

Materials

Name	Company	Catalog Number	Comments
EEGLAB	Swartz Center for Computational Neuroscience (SCCN)		Free/Open-source
MATLAB	The Mathworks, Inc.		Requires a license
Windows PC	Lenovo, Inc.