State equation from the spectral structure of human brain activity

Abstract : Neural electromagnetic (EM) signals recorded non-invasively from individual human subjects vary in complexity and magnitude. Nonetheless, variation in neural activity has been difficult to quantify and interpret, due to complex, broad-band features in the frequency domain. Studying signals recorded with magnetoencephalography (MEG) from healthy young adult subjects while in resting and active states, a systematic framework inspired by thermodynamics is applied to neural EM signals. Despite considerable inter-subject variation in terms of spectral entropy and energy across time epochs, data support the existence of a robust and linear relationship defining an effective state equation, with higher energy and lower entropy in the resting state compared to active, consistently across subjects. Mechanisms underlying the emergence of relationships between empirically measured effective state functions are further investigated using a model network of coupled oscillators, suggesting an interplay between noise and coupling strength can account for coherent variation of empirically observed quantities. Taken together, the results show macroscopic neural observables follow a robust, non-trivial conservation rule for energy modulation and information generation.
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Submitted on : Wednesday, July 31, 2019 - 3:24:01 PM
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  • HAL Id : hal-02202035, version 1
  • ARXIV : 1806.07365



Trang-Anh Nghiem, Jean-Marc Lina, Matteo Di Volo, Cristiano Capone, Alan C. Evans, et al.. State equation from the spectral structure of human brain activity. 2018. ⟨hal-02202035⟩



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