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@ARTICLE{Amunts:902980,
author = {Amunts, Katrin and Lippert, Thomas},
title = {{B}rain research challenges supercomputing},
journal = {Science},
volume = {374},
number = {6571},
issn = {0036-8075},
address = {Cambridge, Mass.},
publisher = {Moses King},
reportid = {FZJ-2021-04726},
pages = {1054 - 1055},
year = {2021},
abstract = {The adult human brain contains ∼86 billion neurons (1).
Zooming into its cellular and subcellular details to reveal
different aspects of neuronal connectivity is a key area of
research. However, to link the different spatial scales from
the synaptic level (at nanometer range) through single
neurons and glial cells (at the micrometer level) to the
whole organ is most challenging. Recently, the connectome of
Caenorhabditis elegans, with its 302 neurons, has been
characterized, and a complete structural-functional model
has been proposed (2). A comparable level of detail of the
human brain connectome is still a long way off. As such,
decoding the human connectome, the mechanisms of signal
transduction, and relationships to brain function are linked
to exponentially growing challenges in advanced
computational and storage technologies, which in turn may
lead to creative solutions beyond neuroscience.},
cin = {INM-1 / JSC},
ddc = {500},
cid = {I:(DE-Juel1)INM-1-20090406 / I:(DE-Juel1)JSC-20090406},
pnm = {5251 - Multilevel Brain Organization and Variability
(POF4-525) / HBP SGA3 - Human Brain Project Specific Grant
Agreement 3 (945539) / 5111 - Domain-Specific Simulation
$\&$ Data Life Cycle Labs (SDLs) and Research Groups
(POF4-511)},
pid = {G:(DE-HGF)POF4-5251 / G:(EU-Grant)945539 /
G:(DE-HGF)POF4-5111},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:34822267},
UT = {WOS:000725668600021},
doi = {10.1126/science.abl8519},
url = {https://juser.fz-juelich.de/record/902980},
}