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Robustness of brain state identification in synthetic phase-coupled neurodynamics using Hidden Markov Models

Hidden Markov Models (HMMs) have emerged as a powerful tool for analyzing time series of neural activity. Gaussian HMMs and their time-resolved extension, Time-Delay Embedded HMMs (TDE-HMMs), have been instrumental in detecting discrete brain states in the form of temporal sequences of large-scale b...

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Main Authors: Giulia Pieramico, Saeed Makkinayeri, Roberto Guidotti, Alessio Basti, Domenico Voso, Delia Lucarelli, Antea D’Andrea, Teresa L’Abbate, Gian Luca Romani, Vittorio Pizzella, Laura Marzetti
Format: Artigo
Language:Inglês
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Systems Neuroscience
Subjects:
HMM
TDE-HMM
phase coupling
brain states
simulation
Online Access:https://www.frontiersin.org/articles/10.3389/fnsys.2025.1548437/full
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