Author(s):
Magalhães, Ricardo José Silva ; Marques, Paulo César Gonçalves ; Veloso, Telma Alves ; Soares, José Miguel Montenegro ; Sousa, Nuno ; Alves, Victor
Date: 2015
Persistent ID: http://hdl.handle.net/1822/52757
Origin: RepositóriUM - Universidade do Minho
Project/scholarship:
info:eu-repo/grantAgreement/FCT/5876/147280/PT;
info:eu-repo/grantAgreement/FCT/3599-PPCDT/127675/PT
;
Subject(s): Connectome; Graph theory; Python; Rs-fMRI; Shell scripting; fMRI Pre-Processing; Science & Technology
Description
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.
This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013. RM is supported by a fellowship of the project FCT-ANR/NEU-OSD/0258/2012 founded by FCT/MEC (www.fct.pt) and by Fundo Europeu de Desenvolvimento Regional (FEDER). PM is supported by a fellowship of the project SwitchBox-FP7-HEALTH-2010-grant 259772-2
info:eu-repo/semantics/publishedVersion
