Hungry hungry hippos: Towards language modeling with state space models

DY Fu, T Dao, KK Saab, AW Thomas, A Rudra… - ar** a foundation model for eeg
W Cui, W Jeong, P Thölke, T Medani… - arxiv preprint arxiv …, 2023 - researchgate.net
To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-
Computer Interface (BCI) tasks, and to harness the power of large publicly available data …

Neuro-gpt: Towards a foundation model for eeg

W Cui, W Jeong, P Thölke, T Medani… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-
Computer Interface (BCI) tasks, and to harness the power of large publicly available data …

CSLP-AE: A contrastive split-latent permutation autoencoder framework for zero-shot electroencephalography signal conversion

A Nørskov, A Neergaard Zahid… - Advances in Neural …, 2023 - proceedings.neurips.cc
Electroencephalography (EEG) is a prominent non-invasive neuroimaging technique
providing insights into brain function. Unfortunately, EEG data exhibit a high degree of noise …

fmri-pte: A large-scale fmri pretrained transformer encoder for multi-subject brain activity decoding

X Qian, Y Wang, J Huo, J Feng, Y Fu - arxiv preprint arxiv:2311.00342, 2023 - arxiv.org
The exploration of brain activity and its decoding from fMRI data has been a longstanding
pursuit, driven by its potential applications in brain-computer interfaces, medical diagnostics …