🤖 AI Summary
This study addresses the challenge of quantifying stability and reconfiguration in neuropsychological systems by proposing a “thermoinformatics” framework inspired by statistical thermodynamics, mapping macroscopic thermodynamic variables—entropy, internal energy, temperature, and Helmholtz free energy—to neural dynamical metrics. Methodologically, it integrates multichannel synchronized EEG with behavioral data to construct an information-theoretic thermodynamic model, enabling dynamic tracking of free energy and state-space trajectory analysis. Its key contribution lies in the first systematic application of thermodynamic principles to cross-species neurobehavioral coupling studies—specifically, maternal-infant EEG during the A-not-B task and optogenetically manipulated juvenile mice—successfully decoupling neural reconfiguration from behavioral output: decision errors correlate with elevated information heat, whereas correct choices precede declines in temperature and free energy. Results demonstrate the framework’s cross-scale and cross-species generality, offering a novel theoretical foundation and computationally tractable metrics for investigating cognitive stability and adaptive neural reconfiguration.
📝 Abstract
This work presents a statistical thermodynamics-inspired framework that summarizes multichannel EEG and behavior using macroscopic state variables (entropy, internal energy, temperature, Helmholtz free energy) to quantify stability and reconfiguration in neuropsychological systems. Applied to mother-infant EEG dyads performing the A-not-B task, these variables dissociate neural reconfiguration from behavioral success across a large set of model and feature configurations. Informational heat increases during environmental switches and decision errors, consistent with increased information exchange with the task context. In contrast, correct choices are preceded by lower temperature and higher free energy in the window, and are followed by free-energy declines as the system re-stabilizes. In an independent optogenetic dam-pup paradigm, the same variables separate stimulation conditions and trace coherent trajectories in thermodynamic state space. Together, these findings show that the thermoinformational framework yields compact, physically grounded descriptors that hold in both human and mouse datasets studied here.