SHINE: Sequential Hierarchical Integration Network for EEG and MEG

arXiv:2602.23960 · cs.SD, cs.AI · Submitted 2026-02-27 · Read on arXiv

cs.SD, cs.AI

Submitted: 2026-02-27

Updated: 2026-09-24

Comments: submit to ICASSP 2027; ranked second at LibriBrain Competition 2025 https://neural-processing-lab.github.io/2025-libribrain-competition/prizes/

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• F1 Score — 3× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Activation Function — 2× in this paper · explained in 1 episode
• Ensemble Learning — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• False Positives — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Parker Jones Neural Processing Lab — 1× in this paper
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• True Positives — 1× in this paper

Sources

• The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset
• LibriBrain: Over 50 Hours of Within-Subject MEG to Improve Speech Decoding Methods at Scale

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