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arXiv · 1501.05836

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

Luiz A. Baccalá·Daniel Y. Takahashi·Koichi Sameshima
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Abstract

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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Luiz A. Baccalá, Daniel Y. Takahashi, Koichi Sameshima. 2015-01-23. Consolidating a Link Centered Neural Connectivity Framework with Directed Transfer Function Asymptotics. https://arxiv.org/abs/1501.05836

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