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BASCO: a toolbox for task-related functional connectivity

BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses si...

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Detalles Bibliográficos
Autores principales: Göttlich, Martin, Beyer, Frederike, Krämer, Ulrike M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565057/
https://www.ncbi.nlm.nih.gov/pubmed/26441558
http://dx.doi.org/10.3389/fnsys.2015.00126
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author Göttlich, Martin
Beyer, Frederike
Krämer, Ulrike M.
author_facet Göttlich, Martin
Beyer, Frederike
Krämer, Ulrike M.
author_sort Göttlich, Martin
collection PubMed
description BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses since the actual interaction between brain regions involved in a task can be explored. BASCO supports seed-based functional connectivity as well as brain network analyses. Although there are a multitude of advanced toolboxes for investigating resting-state functional connectivity, BASCO is the first toolbox for evaluating task-related whole-brain functional connectivity employing a large number of network nodes. Thus, BASCO allows investigating task-specific rather than resting-state networks. Here, we summarize the main features of the toolbox and describe the methods and algorithms.
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spelling pubmed-45650572015-10-05 BASCO: a toolbox for task-related functional connectivity Göttlich, Martin Beyer, Frederike Krämer, Ulrike M. Front Syst Neurosci Neuroscience BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses since the actual interaction between brain regions involved in a task can be explored. BASCO supports seed-based functional connectivity as well as brain network analyses. Although there are a multitude of advanced toolboxes for investigating resting-state functional connectivity, BASCO is the first toolbox for evaluating task-related whole-brain functional connectivity employing a large number of network nodes. Thus, BASCO allows investigating task-specific rather than resting-state networks. Here, we summarize the main features of the toolbox and describe the methods and algorithms. Frontiers Media S.A. 2015-09-10 /pmc/articles/PMC4565057/ /pubmed/26441558 http://dx.doi.org/10.3389/fnsys.2015.00126 Text en Copyright © 2015 Göttlich, Beyer and Krämer. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Göttlich, Martin
Beyer, Frederike
Krämer, Ulrike M.
BASCO: a toolbox for task-related functional connectivity
title BASCO: a toolbox for task-related functional connectivity
title_full BASCO: a toolbox for task-related functional connectivity
title_fullStr BASCO: a toolbox for task-related functional connectivity
title_full_unstemmed BASCO: a toolbox for task-related functional connectivity
title_short BASCO: a toolbox for task-related functional connectivity
title_sort basco: a toolbox for task-related functional connectivity
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4565057/
https://www.ncbi.nlm.nih.gov/pubmed/26441558
http://dx.doi.org/10.3389/fnsys.2015.00126
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