TY - JOUR
T1 - A Process for Digitizing and Simulating Biologically Realistic Oligocellular Networks Demonstrated for the Neuro-Glio-Vascular Ensemble
AU - Coggan, Jay S.
AU - Calì, Corrado
AU - Keller, Daniel
AU - Agus, Marco
AU - Boges, Daniya
AU - Abdellah, Marwan
AU - Kare, Kalpana
AU - Lehväslaiho, Heikki
AU - Eilemann, Stefan
AU - Jolivet, Renaud Blaise
AU - Hadwiger, Markus
AU - Markram, Henry
AU - Schürmann, Felix
AU - Magistretti, Pierre J.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): 2313
Acknowledgements: This work was supported by the CRG grant no. 2313 from King Abdullah University of Science and Technology “KAUST-EPFL Alliance for Integrative Modeling of Brain Energy Metabolism,” as well as ETH Board funding to the Blue Brain Project. Support by the NCCR Synapsy and the Prefargier Foundation to PM, and the Australian Research Council (DP180101494) to RBJ are also acknowledged. Calculations were performed on the EPFL Blue Brain IV BlueGene/Q hosted at the Swiss National Supercomputing Center (CSCS) in Lugano.
PY - 2018/9/25
Y1 - 2018/9/25
N2 - One will not understand the brain without an integrated exploration of structure and function, these attributes being two sides of the same coin: together they form the currency of biological computation. Accordingly, biologically realistic models require the re-creation of the architecture of the cellular components in which biochemical reactions are contained. We describe here a process of reconstructing a functional oligocellular assembly that is responsible for energy supply management in the brain and creating a computational model of the associated biochemical and biophysical processes. The reactions that underwrite thought are both constrained by and take advantage of brain morphologies pertaining to neurons, astrocytes and the blood vessels that deliver oxygen, glucose and other nutrients. Each component of this neuro-glio-vasculature ensemble (NGV) carries-out delegated tasks, as the dynamics of this system provide for each cell-type its own energy requirements while including mechanisms that allow cooperative energy transfers. Our process for recreating the ultrastructure of cellular components and modeling the reactions that describe energy flow uses an amalgam of state-of the-art techniques, including digital reconstructions of electron micrographs, advanced data analysis tools, computational simulations and in silico visualization software. While we demonstrate this process with the NGV, it is equally well adapted to any cellular system for integrating multimodal cellular data in a coherent framework.
AB - One will not understand the brain without an integrated exploration of structure and function, these attributes being two sides of the same coin: together they form the currency of biological computation. Accordingly, biologically realistic models require the re-creation of the architecture of the cellular components in which biochemical reactions are contained. We describe here a process of reconstructing a functional oligocellular assembly that is responsible for energy supply management in the brain and creating a computational model of the associated biochemical and biophysical processes. The reactions that underwrite thought are both constrained by and take advantage of brain morphologies pertaining to neurons, astrocytes and the blood vessels that deliver oxygen, glucose and other nutrients. Each component of this neuro-glio-vasculature ensemble (NGV) carries-out delegated tasks, as the dynamics of this system provide for each cell-type its own energy requirements while including mechanisms that allow cooperative energy transfers. Our process for recreating the ultrastructure of cellular components and modeling the reactions that describe energy flow uses an amalgam of state-of the-art techniques, including digital reconstructions of electron micrographs, advanced data analysis tools, computational simulations and in silico visualization software. While we demonstrate this process with the NGV, it is equally well adapted to any cellular system for integrating multimodal cellular data in a coherent framework.
UR - http://hdl.handle.net/10754/628800
UR - https://www.frontiersin.org/articles/10.3389/fnins.2018.00664/full
UR - http://www.scopus.com/inward/record.url?scp=85054012828&partnerID=8YFLogxK
U2 - 10.3389/fnins.2018.00664
DO - 10.3389/fnins.2018.00664
M3 - Article
C2 - 30319342
SN - 1662-453X
VL - 12
JO - Frontiers in Neuroscience
JF - Frontiers in Neuroscience
ER -