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arxiv: 1501.05836 · v1 · pith:MX7UJK7Anew · submitted 2015-01-23 · 🧬 q-bio.NC · math.ST· stat.TH

Consolidating a Link Centered Neural Connectivity Framework with Directed Transfer Function Asymptotics

classification 🧬 q-bio.NC math.STstat.TH
keywords textitdirectedconnectivitygrangercenteredframeworkfunctionlink
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We present a unified mathematical derivation of the asymptotic behaviour of three of the main forms of \textit{directed transfer function} (DTF) complementing recent partial directed coherence (PDC) results \cite{Baccala2013}. Based on these results and numerical examples we argue for a new directed `link' centered neural connectivity framework to replace the widespread correlation based effective/functional network concepts so that directed network influences between structures become classified as to whether links are \textit{active} in a \textit{direct} or in an \textit{indirect} way thereby leading to the new notions of \textit{Granger connectivity} and \textit{Granger influenciability} which are more descriptive than speaking of Granger causality alone.

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