{"ID":2870631,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.00011","arxiv_id":"2510.00011","title":"Robust State-space Reconstruction of Brain Dynamics via Bootstrap Monte Carlo SSA","abstract":"Reconstructing latent state-space geometry from time series provides a powerful route to studying nonlinear dynamics across complex systems. Delay-coordinate embedding provides the theoretical basis but assumes long, noise-free recordings, which many domains violate. In neuroimaging, for example, fMRI is short and noisy; low sampling and strong red noise obscure oscillations and destabilize embeddings. We propose bootstrap Monte Carlo SSA with a red-noise null and bootstrap stability to retain only oscillatory modes that reproducibly exceed noise. This produces reconstructions that are red-noise-robust and mode-robust, enhancing determinism and stabilizing subsequent embeddings. Our results show that BMC-SSA improves the reliability of functional measures and uncovers differences in state-space dynamics in fMRI, offering a general framework for robust embeddings of noisy, finite signals.","short_abstract":"Reconstructing latent state-space geometry from time series provides a powerful route to studying nonlinear dynamics across complex systems. Delay-coordinate embedding provides the theoretical basis but assumes long, noise-free recordings, which many domains violate. In neuroimaging, for example, fMRI is short and nois...","url_abs":"https://arxiv.org/abs/2510.00011","url_pdf":"https://arxiv.org/pdf/2510.00011v1","authors":"[\"Sir-Lord Wiafe\",\"Carter Hinsley\",\"Vince D. Calhoun\"]","published":"2025-09-16T20:47:14Z","proceeding":"q-bio.NC","tasks":"[\"q-bio.NC\"]","methods":"[]","has_code":false}