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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. FPED: A Functional-Network Prior-Guided Mixture-of-Experts Framework for Interpretable Brain Decoding

    Researchers have developed FPED, a novel Mixture-of-Experts (MoE) framework designed for interpretable brain decoding using fMRI data. This approach explicitly models different functional brain networks as specialized experts, utilizing adaptive routing to capture their combined contributions to visual semantic understanding. FPED aims to overcome limitations of current methods that flatten fMRI signals, thereby disrupting the brain's natural network topology and reducing neuroscientific interpretability. The framework demonstrates competitive performance with a small parameter count and offers transparent insights into the correspondence between brain networks and semantic processing. AI

    FPED: A Functional-Network Prior-Guided Mixture-of-Experts Framework for Interpretable Brain Decoding

    IMPACT Introduces a novel framework for brain decoding that could bridge neural decoding and biologically inspired AI.