Distributed plasticity across network layers enables robust sensory learning in electric fish
By combining connectomics, electrophysiology, and modeling of electric fish circuits, researchers show that synaptic plasticity spread across multiple network layers cooperates to achieve fast, accurate, and noise-robust sensory prediction. This work highlights how distributed changes support adaptive learning.
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The research employed a multi-faceted approach, integrating detailed anatomical mapping of neural connections with live
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Original headline: “Connectome analysis of a cerebellum-like circuit for sensory prediction.” Browse more stories.