Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex
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 p...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2016/1938292 |
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| _version_ | 1832551939002335232 |
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| author | Ugo Vercelli Matteo Diano Tommaso Costa Andrea Nani Sergio Duca Giuliano Geminiani Alessandro Vercelli Franco Cauda |
| author_facet | Ugo Vercelli Matteo Diano Tommaso Costa Andrea Nani Sergio Duca Giuliano Geminiani Alessandro Vercelli Franco Cauda |
| author_sort | Ugo Vercelli |
| collection | DOAJ |
| description | 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 c-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. |
| format | Article |
| id | doaj-art-342dc11aff9b46658b3e22aee8480fb1 |
| institution | Kabale University |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-342dc11aff9b46658b3e22aee8480fb12025-02-03T05:59:53ZengWileyNeural Plasticity2090-59041687-54432016-01-01201610.1155/2016/19382921938292Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular CortexUgo Vercelli0Matteo Diano1Tommaso Costa2Andrea Nani3Sergio Duca4Giuliano Geminiani5Alessandro Vercelli6Franco Cauda7GCS fMRI, Koelliker Hospital, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalyNeuroscience Institute of the Cavalieri Ottolenghi Foundation and Department of Neuroscience, University of Turin, Turin, ItalyGCS fMRI, Koelliker Hospital, Turin, ItalySeveral 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 c-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.http://dx.doi.org/10.1155/2016/1938292 |
| spellingShingle | Ugo Vercelli Matteo Diano Tommaso Costa Andrea Nani Sergio Duca Giuliano Geminiani Alessandro Vercelli Franco Cauda Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex Neural Plasticity |
| title | Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex |
| title_full | Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex |
| title_fullStr | Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex |
| title_full_unstemmed | Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex |
| title_short | Node Detection Using High-Dimensional Fuzzy Parcellation Applied to the Insular Cortex |
| title_sort | node detection using high dimensional fuzzy parcellation applied to the insular cortex |
| url | http://dx.doi.org/10.1155/2016/1938292 |
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