Volta

Beyond the Forest and the Trees: Overlooking the Overlooked Terrain of Neural State Dynamics

Abstract State-transition approaches, including EEG microstate analysis and related fMRI methods such as hidden Markov models (HMMs) and co-activation pattern (CAP) analysis, provide widely used tools for coarse-graining neural dynamics into a small set of quasi-stable states. Its utility has been demonstrated across resting-state and task paradigms, with broad applications ranging from cognitive neuroscience to candidate biomarkers for psychiatric and neurological disorders. A fundamental limitation remains, however: nearly all downstream temporal measures are conditional on the template maps defined at the outset. In the conventional pipeline, templates are derived from polarity-invariant clustering of voltage maps at global field power (GFP) peaks, making the resulting state definitions sensitive to preprocessing, sampling, initialization, clustering algorithms, and the choice of cluster number. Consequently, …

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