MEDUSA©: A novel Python-based software ecosystem to accelerate brain-computer interface and cognitive neuroscience research. (March 2023)

• Record Type: Journal Article
• Authors: Santamaría-Vázquez, Eduardo; Martínez-Cagigal, Víctor; Marcos-Martínez, Diego; Rodríguez-González, Víctor; Pérez-Velasco, Sergio; Moreno-Calderón, Selene; Hornero, Roberto
• Is Part Of: Computer methods and programs in biomedicine. Volume 230(2023)
• Publication Date: 2023-03
• Subjects: Brain-computer interfaces -- Neurotechnology -- Neuroscience -- Electroencephalography; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2023.107357
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: MEDUSA is a novel open-source, Python-based software ecosystem to accelerate BCI and cognitive neuroscience research. Compatibility with any signal acquisition system through the lab-streaming layer (LSL) protocol, including the possibility of recording multiple signals at the same time. Complete suite of BCI paradigms and cognitive neuroscience experiments: c-VEP) and P300 spellers, motor imagery, neurofeedback and multiple neuropsychological tasks. State-of-the-art signal processing methods and models for offline and online analysis. Developer tools to simplify the implementation and sharing of custom open-loop and closed-loop experiments for BCI and cognitive neuroscience. Abstract: Background and objective: Neurotechnologies have great potential to transform our society in ways that are yet to be uncovered. The rate of development in this field has increased significantly in recent years, but there are still barriers that need to be overcome before bringing neurotechnologies to the general public. One of these barriers is the difficulty of performing experiments that require complex software, such as brain-computer interfaces (BCI) or cognitive neuroscience experiments. Current platforms have limitations in terms of functionality and flexibility to meet the needs of researchers, who often need to implement new experimentation settings. This work was aimed to propose a novel software ecosystem, called MEDUSA©, to overcome these limitations. Methods: We followed strict development practices to optimize MEDUSA© for research in BCI and cognitive neuroscience, making special emphasis in the modularity, flexibility and scalability of our solution. Moreover, it was implemented in Python, an open-source programming language that reduces the development cost by taking advantage from its high-level syntax and large number of community packages. Results: MEDUSA© provides a complete suite of signal processing functions, including several deep learning architectures or connectivity analysis, and ready-to-use BCI and neuroscience experiments, making it one of the most complete solutions nowadays. We also put special effort in providing tools to facilitate the development of custom experiments, which can be easily shared with the community through an app market available in our website to promote reproducibility. Conclusions: MEDUSA© is a novel software ecosystem for modern BCI and neurotechnology experimentation that provides state-of-the-art tools and encourages the participation of the community to make a difference for the progress of these fields. Visit the official website at https://www.medusabci.com/ to know more about this project.