#neural-signals News & Analysis

2 articles tagged with #neural-signals. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · May 287/10

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CaMBRAIN: Real-time, Continuous EEG Inference with Causal State Space Models

Researchers introduce CaMBRAIN, a causal state space model based on Mamba architecture that enables real-time, continuous EEG signal processing with linear-time complexity. The model achieves state-of-the-art results across multiple datasets while processing signals >10x faster than existing attention-based methods, overcoming critical limitations in handling variable-length brain activity recordings.

AINeutralarXiv – CS AI · Mar 57/10

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Escaping the BLEU Trap: A Signal-Grounded Framework with Decoupled Semantic Guidance for EEG-to-Text Decoding

Researchers propose SemKey, a novel framework that addresses key limitations in EEG-to-text decoding by preventing hallucinations and improving semantic fidelity through decoupled guidance objectives. The system redesigns neural encoder-LLM interaction and introduces new evaluation metrics beyond BLEU scores to achieve state-of-the-art performance in brain-computer interfaces.