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Sliding-window prediction correlation (SWpC) for time-varying directed functional connectivity. Embeds directional LTI models within sliding windows to estimate time-resolved information flow in brain networks, going beyond undirected correlation.
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基于 SOC 职业分类
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| name | swpc-directed-functional-connectivity |
| description | Sliding-window prediction correlation (SWpC) for time-varying directed functional connectivity. Embeds directional LTI models within sliding windows to estimate time-resolved information flow in brain networks, going beyond undirected correlation. |
Paper: arXiv:2602.16004 Authors: Nan Xu, Xiaodi Zhang, Wen-Ju Pan, et al. Categories: q-bio.NC, cs.LG Year: 2026
SWpC estimates time-varying directed functional connectivity in brain networks. Unlike traditional sliding-window correlation (SWC) which captures undirected associations, SWpC resolves directional interactions by embedding a directional LTI model within each sliding window.
