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EEG foundation models

topic2 events
papersTODAY 04:00 UTC

MANAS-2: Constrained Reconstruction Approach for EEG Foundation Models

A new arXiv paper introduces MANAS-2, an EEG foundation model that reframes masked reconstruction as a constrained problem. The authors argue that optimizing reconstruction on low-SNR brain waveforms does not reliably yield the most useful latent representations. The model is presented as a step toward EEG pretraining objectives that better match downstream usefulness.

eeg/foundation-models/research/representation-learning
papersTODAY 04:00 UTC

EEG-Xplain framework targets interpretability of EEG foundation models

A new arXiv paper proposes EEG-Xplain, a unified attribution framework intended to make EEG foundation models such as BIOT, LaBraM, and EEGMamba more interpretable. The authors argue that the black-box nature of these models hinders clinical trust and neuroscientific validation. The work aims to provide a common approach for attributing model outputs to neural signal inputs.

interpretability/eeg/foundation-models/research