Solving Inverse Problems for AI-Based Surrogate Brains (IMAGE)
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This illustration shows how data-driven inverse problems are solved in neural dynamical systems. Models are constructed and fitted to brain data with appropriate regularization terms that encode mathematical and neuroscience priors, while multi-initialization and perturbation tests are used to detect non-uniqueness and instability in the learned surrogate brain.
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