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Data-driven Koopman operator approach for computational neuroscience

https://doi.org/10.1007/s10472-019-09666-2
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Outgoing claims: the papers this work cites, builds on, or argues with.

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Approximation of discrete and orbital Koopman operators over subsets and manifolds
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An overview of Koopman-based control: From error bounds to closed-loop guarantees
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Top-down prediction signals from the medial prefrontal cortex govern auditory cortex prediction errors
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Identification of noisy Koopman models
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Propofol anesthesia destabilizes neural dynamics across cortex
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Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning
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Parallel encoding of speech in human frontal and temporal lobes
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Online real-time learning of dynamical systems from noisy streaming data
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Optimizing deep brain stimulation based on isostable amplitude in essential tremor patient models
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Non-Stationary Dynamic Mode Decomposition
inferred← citeshttps://doi.org/10.1109/tsmc.2023.3253077openalex-snapshot
Koopman-Theoretic Modeling of Quasiperiodically Driven Systems: Example of Signalized Traffic Corridor
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Data-driven acoustic control of a spherical bubble using a Koopman linear quadratic regulator
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Modern Koopman Theory for Dynamical Systems
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Individualized Closed-Loop Acoustic Stimulation Suggests an Alpha Phase Dependence of Sound Evoked and Induced Brain Activity Measured with EEG Recordings
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Attractor-Like Dynamics Extracted from Human Electrocorticographic Recordings Underlie Computational Principles of Auditory Bistable Perception
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Predicting Latent States of Dynamical Systems With State-Space Reconstruction and Gaussian Processes
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Overview and Applications of Dynamic Mode Decomposition: Toward Application to Control Problems of Neural Systems
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Data, models and transitions in computational neuroscience : bottom-up and top-down approaches
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Uncovering Quasi-periodic Nature of Physical Systems: A Case Study of Signalized Intersections
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