State of the Art Results
Our decoding methods already achieve world-leading reconstruction accuracy. Explore samples from our baseline work, and stay tuned for the release of our next-generation models.
Our end-to-end approach
From data collection, preprocessing, to machine learning, we develop the entire BCI stack in-house.
The Interface of the Future
By decoding neural signals in an interpretable way, we can unlock a wealth of possibilities. These can include:
Groundbreaking Research
We have pioneered research in the field of neural decoding. We made the largest datasets and trained state-of-the-art models for brain decoding. Applying these breakthroughs to EEG, we are excited to achieve orders of magnitude performance improvements for consumer level neural-decoding.
MindEye2
MindEye2 introduces a multi-subject architecture that can train 40 times faster than the previous state-of-the-art model while maintaining the same performance
Our Team
Hailing from various top institutions, we are a world-class team of researchers pushing the boundaries of neural decoding through machine learning.
Scientific Advisory Board
Backed by Leading Experts in Neuroscience and AI
Dr. Arnaud Delorme
Research Director at the French National Centre for Scientific Research (CNRS), Toulouse, Chief architect of EEGLAB Toolbox
Dr. Rufin VanRullen
Director of the Conscious AI Lab, CNRS (French National Centre for Scientific Research), Research Director, Centre de Recherche Cerveau et Cognition (CerCo)
Dr. Anil Seth
Co-Director of the Sackler Centre for Consciousness Science, Professor of Cognitive and Computational Neuroscience at the University of Sussex
Dr. Thomas Naselaris
Associate Professor, Department of Neuroscience at the University of Minnesota
Dr. Tanishq Mathew Abraham
Prev. Research Director at Stability AI, CEO of MedARC, Ph.D. in Biomedical Engineering from the University of California, Davis
Dr. Paul Scotti
Prev. Head of NeuroAI at Stability AI, Ph.D. in Cognitive Neuroscience from Ohio State University, Visiting research scientist at Princeton
We`re using machine learning, software engineering, and neuroscience to build the next generation of brain computer interfaces. If you are excited about meaningful work in these areas, we are actively hiring!
Reach us at [email protected].
