Hauptseite > Publikationsdatenbank > Parcellation-based structural and resting-state functional brain connectomes of a healthy cohort > print |
001 | 893376 | ||
005 | 20210720135228.0 | ||
024 | 7 | _ | |a 10.25493/81EV-ZVT |2 doi |
037 | _ | _ | |a FZJ-2021-02717 |
041 | _ | _ | |a English |
100 | 1 | _ | |a Domhof, Justin |0 P:(DE-Juel1)179582 |b 0 |u fzj |
245 | _ | _ | |a Parcellation-based structural and resting-state functional brain connectomes of a healthy cohort |
260 | _ | _ | |c 2021 |b EBRAINS |
336 | 7 | _ | |a MISC |2 BibTeX |
336 | 7 | _ | |a Dataset |b dataset |m dataset |0 PUB:(DE-HGF)32 |s 1626778675_6696 |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 Nowadays, connectivity patterns of brain networks are of special interest, as they may reflect communication in the brain at the structural and functional levels. Their extraction, however, is a complex process that requires deep knowledge of magnetic resonance imaging (MRI) data processing methods. Furthermore, there is no consensus as to which parcellation of the brain is most suitable for a given analysis. Therefore, 19 different state-of-the-art cortical parcellations were used in this dataset to reconstruct the region-based empirical structural connectivity (representing the anatomy of axonal tracts) and functional connectivity (representing the temporal correlation between neuronal activity of brain regions) from diffusion-weighted (dwMRI) and resting-state functional magnetic resonance imaging (fMRI) data, respectively. The repository provides individual connectomes for 200 subjects from the Human Connectome Project. The data can be used by members of the neuroimaging community to investigate structural and functional human connectomes, and to extend the investigation to whole-brain models for further analyses of brain structure and function. |
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536 | _ | _ | |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) |0 G:(EU-Grant)785907 |c 785907 |f H2020-SGA-FETFLAG-HBP-2017 |x 1 |
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588 | _ | _ | |a Dataset connected to DataCite |
650 | _ | 7 | |a Neuroscience |2 Other |
650 | 1 | 7 | |a Health and Life |0 V:(DE-MLZ)GC-130-2016 |2 V:(DE-HGF) |x 0 |
700 | 1 | _ | |a Jung, Kyesam |0 P:(DE-Juel1)178611 |b 1 |u fzj |
700 | 1 | _ | |a Eickhoff, Simon |0 P:(DE-Juel1)131678 |b 2 |u fzj |
700 | 1 | _ | |a Popovych, Oleksandr |0 P:(DE-Juel1)131880 |b 3 |e Corresponding author |u fzj |
773 | _ | _ | |a 10.25493/81EV-ZVT |
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914 | 1 | _ | |y 2021 |
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980 | _ | _ | |a UNRESTRICTED |
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