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MEGCOMMUNITY  December 2018

MEGCOMMUNITY December 2018

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Subject:

Measuring Granger-causal effects in multivariate time series by system editing

From:

Roberto D Pascual-Marqui <[log in to unmask]>

Reply-To:

Roberto D Pascual-Marqui <[log in to unmask]>

Date:

Mon, 31 Dec 2018 03:12:14 +0000

Content-Type:

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Dear Colleagues,
The preprint entitled 
"Measuring Granger-causal effects in multivariate time series by system editing"
is available at bioRxiv 
https://doi.org/10.1101/504068 
and includes supplementary material for the sake of reproducible research: program codes (PASCAL), executable file, & toy data in human readable format.
The abstract can be found below.
Cordially, Roberto
...
Roberto D. Pascual-Marqui, PhD, PD
The KEY Institute for Brain-Mind Research, University of Zurich
Visiting Professor at Neuropsychiatry, Kansai Medical University, Osaka
[https://www.uzh.ch/keyinst/loreta]
[https://scholar.google.com/citations?user=pascualmarqui]
...

Abstract: What is the role of each node in a system of many interconnected nodes? This can be quantified by comparing the dynamics of the nodes in the intact system, with their modified dynamics in the edited system, where one node is deleted. In detail, the spectra are calculated from a causal multivariate autoregressive model for the intact system. Next, without re-estimation, one node is deleted from the model and the modified spectra at all other nodes are re-calculated. The change in spectra from the edited system to the intact system quantifies the role of the deleted node, giving a measure of its Granger-causal effects (CFX) on the system. A generalization of this novel measure is available for networks (i.e. for groups of nodes), which quantifies the role of each network in a system of many networks. For the sake of reproducible research, program codes (PASCAL), executable file, and toy data in human readable format are included in the supplementary material.

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