topoEEG: An Python-framework for analyzing EEG data in neurodegeneratives disease through Topological Deep Learning
topoEEG is a Python framework designed for advanced EEG analysis, combining the MNE library with Topological Deep Learning (TDL) to enhance insights into neuroimaging, particularly for neurodegenerative diseases such as Alzheimer’s. The framework preprocesses EEG data by removing artifacts using Independent Component Analysis (ICA) and performs Power Spectral Density (PSD) analysis to identify critical frequency bands. By incorporating TDL, topoEEG uncovers topological features that traditional methods often overlook, offering deeper insights into neural activity. Unlike other standalone tools, it provides a unified solution, enhancing the accessibility of sophisticated analytics and supporting research in the diagnosis and understanding of neurodegenerative diseases.
Authors
- Miriam Esteve (ORCID: https://orcid.org/0000-0002-5908-0581)
- Antonio Falcó (ORCID: https://orcid.org/0000-0001-6225-0935)
- J. J. Rodríguez-Sala (ORCID: https://orcid.org/0000-0002-3796-0692)
- Alejandro Martinez-Gracia
Institutions
- Universitat de Miguel Hernández d'Elx (ES)
- Universidad Cardenal Herrera CEU (ES)
Publication Details
- Journal
- SoftwareX
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1016/j.softx.2025.102222
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministerio de Ciencia, Innovación y Universidades
- Ministerio de Ciencia e Innovación
- Agencia Estatal de Investigación