Model order reduction of multiscale models in neuroscience

Keyphrases

• Neuroscience 100%
• Model Order Reduction 100%
• Mathematical Model 66%
• Mean-field Approach 50%
• Discrete Empirical Interpolation Method 50%
• Computational Neuroscience 33%
• System Dynamics 33%
• Proper Orthogonal Decomposition 33%
• Partial Differential Equation Systems 33%
• Order Reduction 16%
• Computational Efficiency 16%
• Probability Density Function 16%
• Numerical Analysis 16%
• Numerical Model 16%
• Numerical Simulation 16%
• Computational Demand 16%
• Potential Gains 16%
• Engineering Science 16%
• Low Computational Complexity 16%
• Robotics 16%
• Original Model 16%
• Scientific Computing 16%
• Neuronal Cells 16%
• Original System 16%
• Control Theory 16%
• Large-scale Networks 16%
• Simulation Time 16%
• Signaling Pathway 16%
• Underutilization 16%
• Computational Burden 16%
• Whole Brain 16%
• Mesoscopic 16%
• Number of Dimensions 16%
• Population-based 16%
• Physical Level 16%
• Pathway Model 16%
• Nonlinear Mathematical Model 16%
• Homeostatic Synaptic Plasticity 16%
• Approximation Error 16%
• Nonlinear Model Order Reduction 16%
• Partial Differential Equation Model 16%
• Random Fluctuations 16%
• Subspace Projection Method 16%
• General Nonlinear Systems 16%
• Minimal Information 16%
• Brain Model 16%
• System of Nonlinear Partial Differential Equations 16%
• Multi-level Simulation 16%
• Mean-field Approximation 16%
• Steady-state Dynamics 16%
• Neurobiological Models 16%
• Whole-brain Connectivity 16%
• Fokker-Planck 16%
• Statistical Similarity 16%

Engineering

• Multiscale Model 100%
• Mathematical Model 100%
• Partial Differential Equation 80%
• Systems Dynamics 40%
• Proper Orthogonal Decomposition 40%
• Equation System 40%
• Discretization 40%
• Nonlinear System 40%
• Engineering 20%
• Similarities 20%
• Numerical Model 20%
• Equation Model 20%
• Dimensionality 20%
• Computational Efficiency 20%
• Multiscale 20%
• Nonlinear Model 20%
• Simulation Time 20%
• Potential Benefit 20%
• Fokker 20%
• Dynamic State 20%
• Model Reduction 20%
• Final Application 20%
• Natural Sciences Computing 20%
• Random Fluctuation 20%
• Computer Simulation 20%
• Probability Density Function 20%

Mathematics

• Mathematical Modeling 100%
• Reduction of Order 100%
• Reduction Method 60%
• Discretization 40%
• Discrete Empirical Interpolation Method 40%
• Partial Differential Equation System 40%
• Nonlinear System 40%
• Partial Differential Equation 20%
• Approximates 20%
• Control Theory 20%
• Probability Density Function 20%
• Numerical Analysis 20%
• Projection Method 20%
• Approximation Error 20%
• Differential Equation Model 20%
• Random Fluctuation 20%
• Field Approximation 20%
• Systems Of Partial Differential Equations 20%
• Computer Simulation 20%
• Nonlinear Model 20%