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Computational Intelligence and Neuroscience
Volume 2012 (2012), Article ID 412512, 21 pages
http://dx.doi.org/10.1155/2012/412512
Research Article

Brain Connectivity Analysis: A Short Survey

1CIML Group, Institute of Biophysics, University of Regensburg, 93040 Regensburg, Germany
2IEETA/DETI, Universidade de Aveiro, 3810-193 Aveiro, Portugal
3Institute of Experimental Psychology, University of Regensburg, 93040 Regensburg, Germany
4DTSTC, Facultad de Ciencias, Universidad Granada, 18071 Granada, Spain
5DATC/ESTII, Universidad de Granada, 18071 Granada, Spain

Received 8 May 2012; Revised 10 August 2012; Accepted 28 August 2012

Academic Editor: Mark Greenlee

Copyright © 2012 E. W. Lang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This short survey the reviews recent literature on brain connectivity studies. It encompasses all forms of static and dynamic connectivity whether anatomical, functional, or effective. The last decade has seen an ever increasing number of studies devoted to deduce functional or effective connectivity, mostly from functional neuroimaging experiments. Resting state conditions have become a dominant experimental paradigm, and a number of resting state networks, among them the prominent default mode network, have been identified. Graphical models represent a convenient vehicle to formalize experimental findings and to closely and quantitatively characterize the various networks identified. Underlying these abstract concepts are anatomical networks, the so-called connectome, which can be investigated by functional imaging techniques as well. Future studies have to bridge the gap between anatomical neuronal connections and related functional or effective connectivities.