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Updated: Jan 26, 2026

PIPEMAT-RS: Development and Validation of a Standardized MATLAB Pipeline for Resting-State EEG Preprocessing
Published on: June 6, 2025
MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG
Li Dong1, Fali Li1, Qiang Liu2
1Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Researchers have developed user-friendly MATLAB toolboxes for the Reference Electrode Standardization Technique (REST) in electroencephalography (EEG). These open-source tools simplify applying REST for zero-referencing scalp EEG data, aiding researchers globally.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- The Reference Electrode Standardization Technique (REST) is a valuable re-referencing method for electroencephalography (EEG) and event-related potentials (ERPs).
- A need exists for accessible tools to implement REST for scalp EEG data analysis.
Purpose of the Study:
- To develop and provide open-source MATLAB toolboxes for simplifying the application of REST in EEG analysis.
- To offer both an EEGLAB-integrated version and a batch version for diverse user needs.
Main Methods:
- Development of two distinct MATLAB toolboxes for REST.
- One toolbox is integrated into the EEGLAB environment.
- A standalone batch version is provided for efficiency.
Main Results:
- Successfully created user-friendly and flexible REST toolboxes.
- The toolboxes facilitate the transformation of multi-channel EEG recordings to approximately zero reference.
- Comparative analysis demonstrates the utility of REST against average referencing.
Conclusions:
- The developed REST toolboxes enhance the accessibility and application of this novel re-referencing technique in EEG studies.
- These open-source resources aim to support both novice and experienced researchers in EEG data processing.
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