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  Adding dynamics to the Human Connectome Project with MEG

Larson-Prior, L., Oostenveld, R., Della Penna, S., Michalareas, G., Prior, F., Babajani-Feremi, A., et al. (2013). Adding dynamics to the Human Connectome Project with MEG. NeuroImage, 80, 190-201. doi:10.1016/j.neuroimage.2013.05.056.

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Larson-Prior_2013_AddingDynamics.pdf (Publisher version), 2MB
 
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 Creators:
Larson-Prior, L.J., Author
Oostenveld, R., Author
Della Penna, S., Author
Michalareas, Giorgos1, 2, Author
Prior, F., Author
Babajani-Feremi, A., Author
Schoffelen, J.-M., Author
Marzetti, L., Author
de Pasquale, F., Author
Di Pompeo, F., Author
Stout, J., Author
Woolrich, M., Author
Luo, Q., Author
Bucholz, R., Author
Fries, Pascal1, 2, Author                 
Pizzella, V., Author
Romani, G.L., Author
Corbetta, M., Author
Snyder, A.Z., Author
WU-Minn HCP Consortium, Contributor              
Affiliations:
1Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, ou_2074314              
2Fries Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society, Deutschordenstraße 46, 60528 Frankfurt, DE, ou_3381216              

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Free keywords: Brain/*anatomy & histology/*physiology Connectome/*methods Humans Magnetoencephalography/*methods Models, Anatomic *Models, Neurological Nerve Net/*anatomy & histology/*physiology
 Abstract: The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be collected from 50 twin pairs both in the resting state and during performance of motor, working memory and language tasks. These data will be available to the general community. Additionally, using the cortical parcellation scheme common to all imaging modalities, the HCP will provide processing pipelines for calculating connection matrices as a function of time and frequency. Together with structural and functional data generated using magnetic resonance imaging methods, these data represent a unique opportunity to investigate brain network connectivity in a large cohort of normal adult human subjects. The analysis pipeline software and the dynamic connectivity matrices that it generates will all be made freely available to the research community.

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 Dates: 2013-10-152013
 Publication Status: Issued
 Pages: -
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 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2013.05.056
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Title: NeuroImage
Source Genre: Journal
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Pages: - Volume / Issue: 80 Sequence Number: - Start / End Page: 190 - 201 Identifier: ISSN: 10538119