Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52757

TitleConstruction of functional brain connectivity networks
Author(s)Magalhães, Ricardo José Silva
Marques, Paulo César Gonçalves
Veloso, Telma Alves
Soares, José Miguel Montenegro
Sousa, Nuno
Alves, Victor
KeywordsConnectome
Graph theory
Python
Rs-fMRI
Shell scripting
fMRI Pre-Processing
Issue date2015
PublisherSpringer International Publishing
JournalAdvances in Intelligent Systems and Computing
Abstract(s)Graph theory and the study of complex networks have, over the last decade, received increasing attention from the neuroscience research community. It allows for the description of the brain as a full network of connections, a connectome, as well as for the quantitative characterization of its topological properties. Still, there is a clear lack of standard procedures for building these networks. In this work we describe a specifically designed full workflow for the pre-processing of resting state functional Magnetic Resonance Imaging (rsfMRI) data and connectome. The proposed workflow focuses on the removal of confound data, the minimization of resampling effects and increasing subject specificity. It is implemented using open source software and libraries through shell and python scripting, allowing its easy integration into other systems such as BrainCAT. With this work we provide the neuroscience research community with a standardized framework for the construction of functional connectomes, simplifying the interpretation and comparison of different studies.
TypeConference paper
URIhttp://hdl.handle.net/1822/52757
ISBN978-3-319-19637-4
DOI10.1007/978-3-319-19638-1_35
ISSN2194-5357
Publisher versionhttps://link.springer.com/chapter/10.1007/978-3-319-19638-1_35
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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