EEG-PRISM: Physiologically-Grounded Interpretability of Predictions by EEG Foundation Models
Bridging the gap between deep learning and clinical neuroscience for brain signal analysis.
Objective: Foundation models represent the next advancement in AI for EEG analysis; however current explainable AI techniques provide attribution scores in the time-channel input space, which is mismatched to clinical intuition about EEG. Thus, there is a critical need for a univ...
ArXiv CS.LG
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EEG-PRISM bridges the gap between opaque foundation model outputs and clinical neuroscience by mapping complex data back to familiar spectral and spatial domains. This advancement allows clinicians to trust AI-driven diagnostics by grounding algorithmic predictions in established physiological markers like seizure onset regions.
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