# ERPLAB: Extensible, open source software for analysis of event-related potentials

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA AT DAVIS · 2024 · $235,500

## Abstract

This project continues the development and support of ERPLAB Toolbox, a Matlab-based open
source software package for the analysis of event-related potential (ERP) data. ERPs provide
information about brain activity related to perception, cognition, emotion, and action with millisecond
resolution and are widely used to study a broad range of basic and translational science issues in
psychology, neuroscience, psychiatry, neurology, and related fields. ERPs are widely used in research
on the mind and brain, but progress has been hampered by the limited abilities of commercial ERP
analysis packages, which often include out-of-date processing and analysis procedures, obscure the
details of the algorithms, make it difficult to automate data processing, and discourage the development
and sharing of new processing and analysis methods. Moreover, these packages are extremely
expensive, taking funds away from other purposes and limiting the number of analysis workstations that
a given lab can afford.
 ERPLAB Toolbox directly addresses these shortcomings of commercial ERP analysis packages. It
provides powerful but easy-to-use tools for the basic and advanced analysis procedures that are
commonly used by ERP researchers. The individual procedures are designed to provide substantial
flexibility while also encouraging best practices that maximize reproducibility and replicability. All
ERPLAB tools can be accessed from a GUI to maximize ease of use, and they can also be accessed
from Matlab scripts to provide automation and customization. In addition, ERPLAB can be easily
extended by anyone with rudimentary programming skills, making it possible for researchers to create
innovative new data processing and analysis procedures and link ERPs with other types of biological
data.
 ERPLAB has been downloaded over 45,000 times and has been cited in over 1650 publications. It
has been used to replace expensive commercial software for conventional analyses, and it has been
used as a platform for developing new analysis procedures and for linking ERP data with other open
source toolboxes. In the proposed funding period, we will continue to provide basic support and
develop new features that reflect trends in basic, translational, and clinical research. We will focus on
four themes: increased workflow efficiency; addition of multivariate pattern analysis methods; tools for
increasing the reproducibility of methods and the replicability of results; and extensive new training
materials. Our goal is to give researchers free, open-source tools that allow them to conduct innovative,
state-of-the-art, high-impact research on normal and disordered brain function.

## Key facts

- **NIH application ID:** 10740879
- **Project number:** 5R01MH087450-14
- **Recipient organization:** UNIVERSITY OF CALIFORNIA AT DAVIS
- **Principal Investigator:** STEVEN J LUCK
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $235,500
- **Award type:** 5
- **Project period:** 2009-12-01 → 2025-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10740879

## Citation

> US National Institutes of Health, RePORTER application 10740879, ERPLAB: Extensible, open source software for analysis of event-related potentials (5R01MH087450-14). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10740879. Licensed CC0.

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