We are pleased to announce the launch of the NeurIPS 2025 EEG Foundation Challenge - From Cross-Task to Cross-Subject EEG Decoding!
A major challenge in the deep learning models of EEG recording is the lack of reproducibility. To address this issue, we propose a large-scale machine learning competition!
Here, we are focusing on two things:
- Advancing the Cross-Task Transfer Learning EEG Decoding:
We need to develop models that can learn across cognitive tasks and can use this knowledge learned.
- What the models learn needs to be clinically helpful:
Models must learn to generalise across subjects and provide a useful psychopathology clinical measure.
As we are also in the era of the large language model, we have many novelties:
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Unprecedented Scale and Complexity: We are introducing a large-scale dataset from over 3,000 participants, with high-density 128-channel EEG recordings across six diverse cognitive tasks.
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Novel Generalisation Scenarios: Challenge 1 focuses on the ability of analytical approaches to generalise to new tasks and new individuals without task-specific adjustments, a crucial step for real-world applicability.
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Prediction of Psychological Constructs: Challenge 2 uses EEG data to predict latent psychopathology factors (like the p-factor), which could contribute to developing objective markers for mental health research.
This challenge presents a significant opportunity to advance EEG-based decoding and contribute to discovering scientifically validated psychiatric biomarkers.
Are you interested? Stay updated on our website and competition dates.
Let’s brain decode!
Together with:
Bruno Aristimunha, Young Truong, Pierre Guetschel, Seyed Yahya Shirazi,
Isabelle Guyon, Alexandre Franco, Michael Milham, Aviv Dotan,
Scott Makeig, Alexandre Gramfort, Jean-Rémi King, Marie-Constance Corsi,
Pedro A. Valdes-Sosa, Amit Majumdar, Alan Evans, Terry Sejnowski,
Oren Shriki, Sylvain Chevallier, Arnaud Delorme
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Bruno Aristimunha
PhD Student in Computer Science (Resume)
https://www.linkedin.com/in/bruaristimunha/
Go open-source! bruAristimunha (Bru) · GitHub