Linking Brain Structure, Activity, and Cognitive Function through Computation
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
Linking Brain Structure, Activity, and Cognitive Function through Computation. / Amunts, Katrin; Defelipe, Javier; Pennartz, Cyriel; Destexhe, Alain; Migliore, Michele; Ryvlin, Philippe; Furber, Steve; Knoll, Alois; Bitsch, Lise; Bjaalie, Jan G.; Ioannidis, Yannis; Lippert, Thomas; Sanchez-Vives, Maria V.; Goebel, Rainer; Jirsa, Viktor.
In: eNeuro, Vol. 9, No. 2, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Linking Brain Structure, Activity, and Cognitive Function through Computation
AU - Amunts, Katrin
AU - Defelipe, Javier
AU - Pennartz, Cyriel
AU - Destexhe, Alain
AU - Migliore, Michele
AU - Ryvlin, Philippe
AU - Furber, Steve
AU - Knoll, Alois
AU - Bitsch, Lise
AU - Bjaalie, Jan G.
AU - Ioannidis, Yannis
AU - Lippert, Thomas
AU - Sanchez-Vives, Maria V.
AU - Goebel, Rainer
AU - Jirsa, Viktor
N1 - Publisher Copyright: © 2022 Amunts et al.
PY - 2022
Y1 - 2022
N2 - Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuro-science, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neu-roscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.
AB - Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuro-science, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neu-roscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.
KW - Artificial neuronal networks
KW - Brain complexity
KW - Connectivity
KW - Human brain mapping
KW - Multiscale brain organization
KW - Neuro-inspired technology
U2 - 10.1523/ENEURO.0316-21.2022
DO - 10.1523/ENEURO.0316-21.2022
M3 - Journal article
C2 - 35217544
AN - SCOPUS:85126303797
VL - 9
JO - eNeuro
JF - eNeuro
SN - 2373-2822
IS - 2
ER -
ID: 313781862