Quantifying Trait-State Hierarchy in EEG Foundation Model and Signal Processing Embeddings

arXiv cs.AINovember 5, 2026en

arXiv:2611.05652v1 Announce Type: new Abstract: Electroencephalography (EEG) measures brain activity through recording electrical potentials of the scalp. EEG recordings capture two distinct sets of characteristics in the signal: (1) \emph{Traits} -- information that remains relatively constant over the course of a recording session, such as subject identity, age, and sex; (2) \emph{States} -- signatures that encode responses to external stimuli, including visual, auditory, and motor information. There is limited understanding of how different EEG modeling features (signal processing and foundation models) encode state and trait characteristics. In this work, we quantify state- and trait-lev

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