OpenNeuroLens wins Rep. Mike Johnson’s 2025 Congressional App Challenge in Louisiana’s Fourth District

When asked what inspired the creation of OpenNeuroLens, the students said, “The idea for OpenNeuroLens began during my research at LSU Health Shreveport, where our team collected EEG data from firefighters performing Go/No-Go cognitive tasks before and after intense physical exercise. We used a commercial software called BrainVision Analyzer to process the data, which was a reliable but prohibitively expensive tool, limiting how many students could participate in the analysis.

“I realized that cost shouldn’t be the barrier keeping people from doing neuroscience. The core methods behind BrainVision (filtering, artifact rejection, ERP extraction, and spectral analysis) are well-established and reproducible with open-source tools. What was missing was an accessible, user-friendly platform that tied those methods together for students and researchers who aren’t programmers.

“That gap became my motivation; I wanted to build an open alternative that could deliver professional-quality EEG analysis using freely available software. Python offered everything needed: MNE and NumPy for signal processing, Streamlit for an intuitive interface, and cloud hosting for accessibility. Developing OpenNeuroLens became a way to democratize neuroscience research, and every design choice(low cost, simplicity, accuracy, and compatibility with common EEG formats) reflected that goal.

“What inspired me most was seeing how this kind of tool could help others. Students could now visualize brain activity, interpret data, and contribute to real research without needing institutional licenses or expensive equipment. That sense of opening doors and making science more inclusive continues to drive the project forward.”