Consolidating a Link Centered Neural Connectivity Framework with Directed Transfer Function Asymptotics
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.
Cite
@article{arxiv.1501.05836,
title = {Consolidating a Link Centered Neural Connectivity Framework with Directed Transfer Function Asymptotics},
author = {Luiz A. Baccalá and Daniel Y. Takahashi and Koichi Sameshima},
journal= {arXiv preprint arXiv:1501.05836},
year = {2015}
}
Comments
12 figures