Hauptseite > Publikationsdatenbank > Brain parcellation and functional territories introduction > print |
001 | 911676 | ||
005 | 20221123131042.0 | ||
024 | 7 | _ | |a 2128/32729 |2 Handle |
037 | _ | _ | |a FZJ-2022-04931 |
100 | 1 | _ | |a GENON, Sarah |0 P:(DE-Juel1)161225 |b 0 |e Corresponding author |
111 | 2 | _ | |a Organization for Human Brain Mapping |c Glasgow, Scotland |d 2022-06-19 - 2022-06-23 |w UK |
245 | _ | _ | |a Brain parcellation and functional territories introduction |
260 | _ | _ | |c 2022 |
336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
336 | 7 | _ | |a Other |2 DataCite |
336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
336 | 7 | _ | |a conferenceObject |2 DRIVER |
336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1669124432_2260 |2 PUB:(DE-HGF) |x Plenary/Keynote |
520 | _ | _ | |a A defining aspect of brain organization is its spatial heterogeneity, which gives rise to multiple topographies at different scales. Brain parcellation — defining distinct partitions in the brain, be they areas or networks that comprise multiple discontinuous but closely interacting regions — is thus fundamental for understanding brain organization and function. The past decade has seen an explosion of in vivo MRI-based approaches to identify and parcellate the brain on the basis of a wealth of different features, ranging from local properties of brain tissue to long-range connectivity patterns, in addition to structural and functional markers. In this talk, I will introduce brain parcellation and provide an overview of the main approaches. I will then focus more particularly on connectivity-based parcellation (CBP) applied to different connectivity features. This will lead us to discuss convergence and divergence across features and the related open challenges. Articles discussed: Eickhoff, S. B., Yeo, B. T. T., & Genon, S. (2018). Imaging-based parcellations of the human brain. Nat Rev Neurosci, 19(11), 672-686. doi:10.1038/s41583-018-0071-7 Genon, S., Bernhardt, B. C., La Joie, R., Amunts, K., & Eickhoff, S. B. (2021). The many dimensions of human hippocampal organization and (dys) function. Trends in Neurosciences. Plachti, A., Eickhoff, S. B., Hoffstaedter, F., Patil, K. R., Laird, A. R., Fox, P. T., . . . Genon, S. (2019). Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient. Cereb Cortex, 29(11), 4595-4612. doi:10.1093/cercor/bhy336 Software employed: CBBtools: https://github.com/inm7/cbptools Data: https://www.humanconnectome.org/study/hcp-young-adult/data-releases |
536 | _ | _ | |a 5252 - Brain Dysfunction and Plasticity (POF4-525) |0 G:(DE-HGF)POF4-5252 |c POF4-525 |f POF IV |x 0 |
856 | 4 | _ | |u https://orbi.uliege.be/handle/2268/292566 |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/911676/files/Parcellation_GenonS_OHBM2022_compressed.pdf |y OpenAccess |
909 | C | O | |o oai:juser.fz-juelich.de:911676 |p openaire |p open_access |p VDB |p driver |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)161225 |
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)POF4-5252 |x 0 |
914 | 1 | _ | |y 2022 |
915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)INM-7-20090406 |k INM-7 |l Gehirn & Verhalten |x 0 |
980 | 1 | _ | |a FullTexts |
980 | _ | _ | |a conf |
980 | _ | _ | |a VDB |
980 | _ | _ | |a UNRESTRICTED |
980 | _ | _ | |a I:(DE-Juel1)INM-7-20090406 |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|