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  Connectivity concordance mapping: A new tool for model-free analysis of fMRI data of the human brain

Lohmann, G., Ovadia-Caro, S., Jungehülsing, G. J., Margulies, D. S., Villringer, A., & Turner, R. (2012). Connectivity concordance mapping: A new tool for model-free analysis of fMRI data of the human brain. Frontiers in Systems Neuroscience, 6: 13. doi:10.3389/fnsys.2012.00013.

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 Creators:
Lohmann, Gabriele1, Author           
Ovadia-Caro, Smadar2, Author
Jungehülsing, Gerhard Jan3, Author
Margulies, Daniel S.2, 4, Author           
Villringer, Arno2, 3, 5, Author           
Turner, Robert1, Author           
Affiliations:
1Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
2Berlin School of Mind and Brain, Humboldt University Berlin, Germany, ou_persistent22              
3Center for Stroke Research, Charité University Medicine Berlin, Germany, ou_persistent22              
4Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
5Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              

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Free keywords: Connectivity; Resting state
 Abstract: 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 of time courses of each voxel with every other voxel for each measurement. Voxels whose correlation pattern is consistent across measurements receive high values. The result of a CCM analysis is thus a voxel-wise map of concordance values. Regions of high inter-subject 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 demonstrate the possible applications of the algorithm. The first is a eyes-open/eyes-closed paradigm designed to highlight the potential of the method in a relatively simple 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.

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Language(s): eng - English
 Dates: 2011-11-152012-02-292012-03-20
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fnsys.2012.00013
PMID: 22470320
PMC: PMC3308143
Other: eCollection 2012
 Degree: -

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Title: Frontiers in Systems Neuroscience
  Abbreviation : Front Syst Neurosci
Source Genre: Journal
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Pages: - Volume / Issue: 6 Sequence Number: 13 Start / End Page: - Identifier: ISSN: 1662-5137
CoNE: https://pure.mpg.de/cone/journals/resource/1662-5137