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Zyphra·Feb 18, 2026·v1.0·open source
ZUNA
ZUNA is Zyphra's first foundation model trained on brain data, aiming to advance noninvasive thought-to-text communication through brain–computer interfaces (BCIs). This 380M-parameter diffusion autoencoder model enhances the quality and usability of electroencephalography (EEG) data by reconstructing, denoising, and upsampling signals across various channel layouts.
CVLLMsMLBio
overview
ZUNA is Zyphra's first foundation model trained on brain data, aiming to advance noninvasive thought-to-text communication through brain–computer interfaces (BCIs). This 380M-parameter diffusion autoencoder model enhances the quality and usability of electroencephalography (EEG) data by reconstructing, denoising, and upsampling signals across various channel layouts.
key features
- 01Denoises existing EEG channels
- 02Reconstructs missing EEG channels
- 03Predicts novel channel signals based on scalp coordinates
- 04Operates across diverse EEG systems, from consumer headsets to clinical equipment
- 05Open-source under Apache 2.0 license
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