Data-driven modelling of brain activity using neural networks, diffusion maps, and the Koopman operator

Keyphrases

• Brain Activity 100%
• Neural Network 100%
• Data-driven Modeling 100%
• Diffusion Maps 100%
• Koopman Operator 100%
• Network Diffusion 100%
• Feedforward Neural Network 75%
• Geometric Harmonics 75%
• Ambient Space 75%
• FMRI Time Series 75%
• Functional Magnetic Resonance Imaging 50%
• Reduced Order Model 50%
• Preimage Problem 50%
• Latent Space 25%
• Truncation 25%
• Machine Learning Approach 25%
• Discrete-time 25%
• Manifold Embedding 25%
• Manifold Learning 25%
• Per Se 25%
• Function Space 25%
• Task Dependency 25%
• Low-dimensional Manifolds 25%
• Coordinate Functions 25%
• Operator Approach 25%
• Coupled Diffusion 25%
• Long-term Dynamics 25%
• Integrable Function 25%
• Visuomotor Task 25%
• Map Function 25%
• Nonlinear Map 25%
• Koopman Modes 25%
• Five-dimensional Model 25%
• High-dimensional Time Series 25%

Mathematics

• Neural Network 100%
• Ambient Space 75%
• Pre-Image 50%
• Nonlinear 25%
• Manifold 25%
• Function Space 25%
• Operator Approach 25%
• Dimensional Time 25%
• Practical Purpose 25%
• Dimensional Manifold 25%
• Coordinate Function 25%
• Linear Map 25%
• Integrable Function 25%
• Truncation 25%
• Stochastics 25%
• Discrete Time 25%
• Dimensional Model 25%
• Embedded Manifold 25%