001019122 001__ 1019122
001019122 005__ 20240226075506.0
001019122 037__ $$aFZJ-2023-05175
001019122 1001_ $$0P:(DE-Juel1)179447$$avan der Vlag, Michiel$$b0$$eCorresponding author$$ufzj
001019122 1112_ $$aJSC's End-of-Year Colloquium 2023$$cJülich$$d2023-12-05 - 2023-12-05$$wGermany
001019122 245__ $$aVast TVB parameter space exploration: A Modular Framework for Accelerating the Multi-Scale Simulation of Human Brain Dynamics
001019122 260__ $$c2022
001019122 3367_ $$033$$2EndNote$$aConference Paper
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001019122 520__ $$aNeural dynamics arise from the intricate multi-scale structures of the brain, where neurons communicate through synapses, forming transient assemblies that contribute to global brain dynamics. Local network activity is regulated by a complex interplay of intercellular communication, intracellular signaling cascades, and the extracellular molecular environment. Recent multi-scale models of brain function have successfully linked the emergence of global brain dynamics in both conscious and unconscious states to microscopic changes influencing local networks.Specifically, mean-field models, such as the Adaptive Exponential (AdEx) models representing statistical properties of local neuron populations, have been connected using human tractography data to simulate multi-scale neural phenomena within The Virtual Brain (TVB). While mean-field models can be run on personal computers for short simulations or on high-performance computing (HPC) architectures for longer simulations, the computational demands remain high, leaving extensive areas of the parameter space unexplored. In this work, we introduce our TVB-HPC framework, a modular set of methods designed to implement the TVB-AdEx model for GPU, enhancing simulation speed and significantly reducing computational resource requirements. This framework maintains the stability and robustness of the TVB-AdEx model, enabling more detailed exploration of vast parameter spaces and longer simulations that were previously challenging. Comparisons between our TVB-HPC framework and TVB-AdEx demonstrate the similarity in generating patterns of functional connectivity between brain regions. By varying global coupling and spike-frequency adaptation, we reproduce their interdependence in inducing transitions between dynamics associated with conscious and unconscious brain states. Exploring theparameter space further, we unveil a nonlinear interplay between spike-frequency adaptation and subthreshold adaptation, along with previously unnoticed interactions between global coupling, adaptation, and the propagation velocity of action potentials along the human connectome. As our simulation and analysis toolkits are openly accessible as open-source packages, our TVB-HPC framework serves as a versatile template for scripting other models. This approach facilitates the use of personalized datasets in the study of inter-individual variability in parameters related to functional brain dynamics. Consequently, our results present potentially influential, publicly-available methods for simulating and analyzing various human brain states.
001019122 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001019122 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x1
001019122 536__ $$0G:(DE-Juel1)Helmholtz-SLNS$$aSLNS - SimLab Neuroscience (Helmholtz-SLNS)$$cHelmholtz-SLNS$$x2
001019122 7001_ $$0P:(DE-Juel1)165859$$aDiaz, Sandra$$b1$$ufzj
001019122 909CO $$ooai:juser.fz-juelich.de:1019122$$pec_fundedresources$$pVDB$$popenaire
001019122 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)179447$$aForschungszentrum Jülich$$b0$$kFZJ
001019122 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)165859$$aForschungszentrum Jülich$$b1$$kFZJ
001019122 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001019122 9141_ $$y2023
001019122 920__ $$lyes
001019122 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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001019122 980__ $$aI:(DE-Juel1)JSC-20090406
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