v1.0

Release Notes: ExperimentTestingFramework v1.0

We are pleased to announce the release of ExperimentTestingFramework, the official code repository for the paper titled "A standardized framework to test event-based experiments." This repository provides all necessary code and data to replicate the simulations and analyses presented in the paper.

Key Features:

• Dummy Experiment: A Jupyter notebook illustrating how to apply the testing framework on a simple experiment to characterize the performance of an experimental setup.
• Setup and Dependencies: The repository requires only MNE-Python. Follow the provided installation guidelines to get started.
• ERP Simulation: Scripts for simulating ERP data, including jitter and label shuffle effects, using real EEG data.
• RT Simulation: Scripts for simulating reaction time data, generating differences in RT between conditions, and applying jitter and label shuffle.
• Survey Results: Preprocessed survey results with scripts to generate the plots used in the paper.

Detailed Instructions:

Data Preparation:

• Download the EEG dataset here.
• Convert the data to an MNE-compatible format using 00_object_processing_dataset_preparation.py

Simulations:

• ERP Simulation: Run 01_simulation_erp.py with the appropriate config file.
• RT Simulation: Run 02_simulation_rt.py with the appropriate config file.
• Plotting: Generate plots for ERP and RT simulations using 03_plot_simulation.py.

Survey Analysis:

• Process and analyze survey results using process_survey.py.

We hope this framework will enhance the reproducibility of results, accelerate multi-center studies, and improve research quality. For more details, please refer to the README in the repository.