G. V. Karanikolas — accepted AI-conference papers

2017

Identifying directional connections in brain networks via multi-kernel granger models

G. V. Karanikolas, Georgios B. Giannakis

ICASSP 2017accepted

Granger causality based approaches are popular in unveiling directed interactions among brain regions. The present work advocates a multi-kernel based nonlinear model for obtaining the effective connectivity between brain regions, by wedding the merits of partial correlation in undirected topology i…

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2016

Multi-kernel based nonlinear models for connectivity identification of brain networks

G. V. Karanikolas, Georgios B. Giannakis, Konstantinos Slavakis, Richard M. Leahy

ICASSP 2016accepted

Partial correlations (PCs) of functional magnetic resonance imaging (fMRI) time series play a principal role in revealing connectivity of brain networks. To explore nonlinear behavior of the blood-oxygen-level dependent signal, the present work postulates a kernel-based nonlinear connectivity model…

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