  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.

Neurons and Cognition;Disordered Systems and Neural Networks