Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain
Functional magnetic resonance data acquired in a task-absent condition ("resting state'') require new data analysis techniques that do not depend on an activation model. Here, we propose a new analysis method called "Connectivity Concordance Mapping (CCM)".The ma...
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Frontiers Media S.A.
2012-03-01
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Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnsys.2012.00013/full |
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doaj-30e2ecb144fe4c2fab39065a1f82acb72020-11-24T21:43:04ZengFrontiers Media S.A.Frontiers in Systems Neuroscience1662-51372012-03-01610.3389/fnsys.2012.0001319029Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brainGabriele eLohmann0Smadar eOvadia-Caro1Smadar eOvadia-Caro2Gerhard Jan eJungehülsing3Daniel S Margulies4Daniel S Margulies5Arno eVillringer6Robert eTurner7Max Planck Institute for Human Cognitive and Brain SciencesMax Planck Institute for Human Cognitive and Brain SciencesHumbold UniversityUniversity Clinic ChariteMax Planck Institute for Human Cognitive and Brain SciencesHumbold UniversityMax Planck Institute for Human Cognitive and Brain SciencesMax Planck Institute for Human Cognitive and Brain SciencesFunctional magnetic resonance data acquired in a task-absent condition ("resting state'') require new data analysis techniques that do not depend on an activation model. Here, we propose a new analysis method called "Connectivity Concordance Mapping (CCM)".The main idea is to assign a label to each voxel based on the reproducibility of its whole-brain pattern of connectivity. Specifically, we compute the correlations across measurements of each voxel's correlation-based functional connectivity map, resulting in a voxelwise map of concordance values. Regions of high interscan concordance can be assumed to be functionally consistent, and may thus be of specific interest for further analysis. Here we present two fMRI studies to test the algorithm. The first is a eyes open/eyes closed paradigm designed to highlight the potential of the method in a relatively simple state-dependent domain. The second study is a longitudinal repeated measurement of a patient following stroke. Longitudinal clinical studies such as this may represent the most interesting domain of applications for this algorithm, as it provides an exploratory means to identify changes in connectivity, such as those during post-stroke recovery.http://journal.frontiersin.org/Journal/10.3389/fnsys.2012.00013/fullBrainfMRIresting stateCCMconcordanceconnectivity mapping |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gabriele eLohmann Smadar eOvadia-Caro Smadar eOvadia-Caro Gerhard Jan eJungehülsing Daniel S Margulies Daniel S Margulies Arno eVillringer Robert eTurner |
spellingShingle |
Gabriele eLohmann Smadar eOvadia-Caro Smadar eOvadia-Caro Gerhard Jan eJungehülsing Daniel S Margulies Daniel S Margulies Arno eVillringer Robert eTurner Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain Frontiers in Systems Neuroscience Brain fMRI resting state CCM concordance connectivity mapping |
author_facet |
Gabriele eLohmann Smadar eOvadia-Caro Smadar eOvadia-Caro Gerhard Jan eJungehülsing Daniel S Margulies Daniel S Margulies Arno eVillringer Robert eTurner |
author_sort |
Gabriele eLohmann |
title |
Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain |
title_short |
Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain |
title_full |
Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain |
title_fullStr |
Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain |
title_full_unstemmed |
Connectivity concordance mapping: a new tool for model-free analysis of fMRI data of the human brain |
title_sort |
connectivity concordance mapping: a new tool for model-free analysis of fmri data of the human brain |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Systems Neuroscience |
issn |
1662-5137 |
publishDate |
2012-03-01 |
description |
Functional magnetic resonance data acquired in a task-absent condition ("resting state'') require new data analysis techniques that do not depend on an activation model. Here, we propose a new analysis method called "Connectivity Concordance Mapping (CCM)".The main idea is to assign a label to each voxel based on the reproducibility of its whole-brain pattern of connectivity. Specifically, we compute the correlations across measurements of each voxel's correlation-based functional connectivity map, resulting in a voxelwise map of concordance values. Regions of high interscan concordance can be assumed to be functionally consistent, and may thus be of specific interest for further analysis. Here we present two fMRI studies to test the algorithm. The first is a eyes open/eyes closed paradigm designed to highlight the potential of the method in a relatively simple state-dependent domain. The second study is a longitudinal repeated measurement of a patient following stroke. Longitudinal clinical studies such as this may represent the most interesting domain of applications for this algorithm, as it provides an exploratory means to identify changes in connectivity, such as those during post-stroke recovery. |
topic |
Brain fMRI resting state CCM concordance connectivity mapping |
url |
http://journal.frontiersin.org/Journal/10.3389/fnsys.2012.00013/full |
work_keys_str_mv |
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