000888100 001__ 888100
000888100 005__ 20210130010816.0
000888100 0247_ $$2doi$$a10.25493/QA7B-JM9
000888100 037__ $$aFZJ-2020-04677
000888100 1001_ $$0P:(DE-Juel1)131701$$aPalomero-Gallagher, Nicola$$b0$$eCorresponding author
000888100 245__ $$aProbabilistic cytoarchitectonic map of Area p24c (pACC) (v16.1)
000888100 260__ $$bHuman Brain Project Neuroinformatics Platform$$c2019
000888100 3367_ $$2BibTeX$$aMISC
000888100 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1605867599_1263
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000888100 520__ $$aThis dataset contains the distinct architectonic areas pv24c, pd24cv and pd24cd (combined to a single probability map named Area p24c (pACC)) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area p24c (pACC). The probability map of Area p24c (pACC) is provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area p24c (pACC): Palomero-Gallagher et al. (2019) [Data set, v16.0] [DOI: 10.25493/YSP3-WR3](https://doi.org/10.25493%2FYSP3-WR3) The most probable delineation of Area p24c (pACC) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D)
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000888100 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
000888100 588__ $$aDataset connected to DataCite
000888100 7001_ $$0P:(DE-Juel1)131684$$aHoffstaedter, Felix$$b1
000888100 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, Hartmut$$b2
000888100 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b3
000888100 7001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b4
000888100 7001_ $$0P:(DE-Juel1)131714$$aZilles, Karl$$b5
000888100 773__ $$a10.25493/QA7B-JM9
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000888100 9141_ $$y2020
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