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  Multi-modal ultra-high resolution structural 7-Tesla MRI data repository

Forstmann, B. U., Keuken, M. C., Schäfer, A., Bazin, P.-L., Alkemade, A., & Turner, R. (2014). Multi-modal ultra-high resolution structural 7-Tesla MRI data repository. Scientific Data, 1: 140050. doi:10.1038/sdata.2014.50.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0024-3F6A-F Version Permalink: http://hdl.handle.net/21.11116/0000-0003-7C30-C
Genre: Journal Article

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 Creators:
Forstmann, Birte U.1, Author
Keuken, Max C.1, Author
Schäfer, Andreas2, Author              
Bazin, Pierre-Louis2, 3, Author              
Alkemade, Anneke1, Author
Turner, Robert2, Author              
Affiliations:
1Amsterdam Brain and Cognition (ABC), University of Amsterdam, the Netherlands, ou_persistent22              
2Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_634549              

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 Abstract: Structural brain data is key for the understanding of brain function and networks, i.e., connectomics. Here we present data sets available from the ‘atlasing of the basal ganglia (ATAG)’ project, which provides ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. The ATAG data set includes whole-brain and reduced field-of-view MP2RAGE and T2*-weighted scans of the subcortex and brainstem with ultra-high resolution at a sub-millimeter scale. The data can be used to develop new algorithms that help building high-resolution atlases both relevant for the basic and clinical neurosciences. Importantly, the present data repository may also be used to inform the exact positioning of electrodes used for deep-brain-stimulation in patients with Parkinson’s disease and neuropsychiatric diseases.

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Language(s): eng - English
 Dates: 2014-07-112014-11-052014-12-09
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1038/sdata.2014.50
PMID: 25977801
PMC: PMC4421933
Other: eCollection 2014
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Title: Scientific Data
Source Genre: Journal
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Publ. Info: London, United Kingdom : Nature Publishing Group
Pages: - Volume / Issue: 1 Sequence Number: 140050 Start / End Page: - Identifier: ISSN: 2052-4463
CoNE: /journals/resource/2052-4463