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Neural Plasticity
Volume 2016, Article ID 1938292, 8 pages
http://dx.doi.org/10.1155/2016/1938292
Research Article

Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex

1GCS fMRI, Koelliker Hospital, Turin, Italy
2Functional Neuroimaging and Neural Complex System Group, Department of Psychology, University of Turin, Turin, Italy
3Department of Psychology, University of Turin, Turin, Italy
4Neuroscience Institute of the Cavalieri Ottolenghi Foundation and Department of Neuroscience, University of Turin, Turin, Italy

Received 29 April 2015; Revised 29 June 2015; Accepted 6 July 2015

Academic Editor: Yong Liu

Copyright © 2016 Ugo Vercelli 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

Several functional connectivity approaches require the definition of a set of regions of interest (ROIs) that act as network nodes. Different methods have been developed to define these nodes and to derive their functional and effective connections, most of which are rather complex. Here we aim to propose a relatively simple “one-step” border detection and ROI estimation procedure employing the fuzzy -mean clustering algorithm. To test this procedure and to explore insular connectivity beyond the two/three-region model currently proposed in the literature, we parcellated the insular cortex of 20 healthy right-handed volunteers scanned in a resting state. By employing a high-dimensional functional connectivity-based clustering process, we confirmed the two patterns of connectivity previously described. This method revealed a complex pattern of functional connectivity where the two previously detected insular clusters are subdivided into several other networks, some of which are not commonly associated with the insular cortex, such as the default mode network and parts of the dorsal attentional network. Furthermore, the detection of nodes was reliable, as demonstrated by the confirmative analysis performed on a replication group of subjects.