000888073 001__ 888073
000888073 005__ 20210130010806.0
000888073 0247_ $$2doi$$a10.25493/E1YQ-65U
000888073 037__ $$aFZJ-2020-04650
000888073 1001_ $$0P:(DE-HGF)0$$aHenssen, A.$$b0
000888073 245__ $$aProbabilistic cytoarchitectonic map of Area Fo3 (OFC) (v3.4)
000888073 260__ $$bHuman Brain Project Neuroinformatics Platform$$c2019
000888073 3367_ $$2BibTeX$$aMISC
000888073 3367_ $$0PUB:(DE-HGF)32$$2PUB:(DE-HGF)$$aDataset$$bdataset$$mdataset$$s1605856120_1263
000888073 3367_ $$026$$2EndNote$$aChart or Table
000888073 3367_ $$2DataCite$$aDataset
000888073 3367_ $$2ORCID$$aDATA_SET
000888073 3367_ $$2DINI$$aResearchData
000888073 520__ $$aThis dataset contains the distinct architectonic Area Fo3 (OFC) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area Fo3 (OFC). The probability map of Area Fo3 (OFC) are provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area Fo3 (OFC): Henssen et al. (2018) [Data set, v3.2] [DOI: 10.25493/9ZWB-EEZ](https://doi.org/10.25493%2F9ZWB-EEZ) The most probable delineation of Area Fo3 (OFC) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D)
000888073 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000888073 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
000888073 588__ $$aDataset connected to DataCite
000888073 7001_ $$0P:(DE-Juel1)131714$$aZilles, Karl$$b1$$ufzj
000888073 7001_ $$0P:(DE-Juel1)131701$$aPalomero-Gallagher, Nicola$$b2$$ufzj
000888073 7001_ $$0P:(DE-Juel1)145628$$aSchleicher, Axel$$b3
000888073 7001_ $$0P:(DE-Juel1)131660$$aMohlberg, Hartmut$$b4$$ufzj
000888073 7001_ $$0P:(DE-HGF)0$$aGerboga, F.$$b5
000888073 7001_ $$0P:(DE-Juel1)131678$$aEickhoff, Simon$$b6$$ufzj
000888073 7001_ $$0P:(DE-Juel1)131636$$aBludau, Sebastian$$b7$$ufzj
000888073 7001_ $$0P:(DE-Juel1)131631$$aAmunts, Katrin$$b8$$ufzj
000888073 773__ $$a10.25493/E1YQ-65U
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000888073 9141_ $$y2020
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