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| Hauptseite > Publikationsdatenbank > Cortical intensity profiles sampled across BigBrain isocortex (v1.0) > print |
| Hauptseite > Publikationsdatenbank > Cortical intensity profiles sampled across BigBrain isocortex (v1.0) > print |
| 001 | 911551 | ||
| 005 | 20221118130917.0 | ||
| 024 | 7 | _ | |a 10.25493/18ED-DS3 |2 doi |
| 037 | _ | _ | |a FZJ-2022-04811 |
| 100 | 1 | _ | |a Wagstyl, Konrad |0 P:(DE-HGF)0 |b 0 |
| 245 | _ | _ | |a Cortical intensity profiles sampled across BigBrain isocortex (v1.0) |
| 260 | _ | _ | |c 2022 |b EBRAINS |
| 336 | 7 | _ | |a MISC |2 BibTeX |
| 336 | 7 | _ | |a Dataset |b dataset |m dataset |0 PUB:(DE-HGF)32 |s 1668768506_28492 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Chart or Table |0 26 |2 EndNote |
| 336 | 7 | _ | |a Dataset |2 DataCite |
| 336 | 7 | _ | |a DATA_SET |2 ORCID |
| 336 | 7 | _ | |a ResearchData |2 DINI |
| 520 | _ | _ | |a BigBrain is a publicly available 3D model of the human brain at 20 micron isotropic resolution, reconstructed from 7404 histological tissue sections that have been stained for cell bodies. This dataset contains profiles of the staining intensities, sampled at surface positions across the complete isocortex, ranging from the pial surface to the gray/white matter boundary. Since BigBrain's staining is sensitive to cell bodies, profiles are an approximate local measure of cortical cell density. |
| 536 | _ | _ | |a 5251 - Multilevel Brain Organization and Variability (POF4-525) |0 G:(DE-HGF)POF4-5251 |c POF4-525 |f POF IV |x 0 |
| 536 | _ | _ | |a HIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015) |0 G:(DE-HGF)InterLabs-0015 |c InterLabs-0015 |x 1 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 650 | _ | 7 | |a Neuroscience |2 Other |
| 700 | 1 | _ | |a Larocque, Stéphanie |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Cucurull, Guillem |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Lepage, Claude |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Cohen, Joseph Paul |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Bludau, Sebastian |0 P:(DE-Juel1)131636 |b 5 |
| 700 | 1 | _ | |a Palomero-Gallagher, Nicola |0 P:(DE-Juel1)131701 |b 6 |
| 700 | 1 | _ | |a Lewis, Lindsay B. |b 7 |
| 700 | 1 | _ | |a Funck, Thomas |0 P:(DE-Juel1)181092 |b 8 |
| 700 | 1 | _ | |a Spitzer, Hannah |b 9 |
| 700 | 1 | _ | |a Dickscheid, Timo |0 P:(DE-Juel1)165746 |b 10 |
| 700 | 1 | _ | |a Fletcher, Paul C. |b 11 |
| 700 | 1 | _ | |a Romero, Adriana |b 12 |
| 700 | 1 | _ | |a Zilles, Karl |b 13 |
| 700 | 1 | _ | |a Amunts, Katrin |0 P:(DE-Juel1)131631 |b 14 |
| 700 | 1 | _ | |a Bengio, Yoshua |b 15 |
| 700 | 1 | _ | |a Evans, Alan C. |b 16 |
| 773 | _ | _ | |a 10.25493/18ED-DS3 |
| 909 | C | O | |o oai:juser.fz-juelich.de:911551 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 5 |6 P:(DE-Juel1)131636 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)131701 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 8 |6 P:(DE-Juel1)181092 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 10 |6 P:(DE-Juel1)165746 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 14 |6 P:(DE-Juel1)131631 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-525 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Decoding Brain Organization and Dysfunction |9 G:(DE-HGF)POF4-5251 |x 0 |
| 914 | 1 | _ | |y 2022 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-1-20090406 |k INM-1 |l Strukturelle und funktionelle Organisation des Gehirns |x 0 |
| 980 | _ | _ | |a dataset |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)INM-1-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
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