SMR applied to EEG and iEEG data shows strong reconstruction persists after excluding local neighbors, indicating that electrode signals contain both local redundancy and broader distributed structure.
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A self-consistent framework with generalized local order parameters is derived for the Kuramoto model with dyadic and triadic interactions on hypergraphs, showing bistability onset depends on eigenvector correlations between dyadic and triadic structures.
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Spatially Masked Regression Reveals Local and Distributed Predictability in Electrophysiological Recordings
SMR applied to EEG and iEEG data shows strong reconstruction persists after excluding local neighbors, indicating that electrode signals contain both local redundancy and broader distributed structure.
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Self-consistent analysis of the Kuramoto model with higher-order interactions
A self-consistent framework with generalized local order parameters is derived for the Kuramoto model with dyadic and triadic interactions on hypergraphs, showing bistability onset depends on eigenvector correlations between dyadic and triadic structures.