Thermodynamic rigidity of harmonic brain states relates to general mental ability in juvenile myoclonic epilepsy

Abstract

Cognitive difficulties are increasingly recognized in juvenile myoclonic epilepsy (JME), but scalable biomarkers linking resting-state brain dynamics to general mental ability remain limited. Here, we combined topological data analysis, graph signal processing, machine learning, inverse Langevin modeling, and biophysical simulations to test whether EEG-derived network dynamics capture individual differences in general mental ability in JME. We studied 54 patients with JME and 45 healthy controls using resting-state high-density EEG and the raw estimated full-scale score derived from the Wechsler Abbreviated Scale of Intelligence (WASI), used here as an index of general mental ability. Subject-specific low-alpha activity was reconstructed with generalized eigendecomposition, and graph-derived features were extracted from the projection of topological and alpha-power signals onto the functional connectome, providing a graph-harmonic description of large-scale brain-state dynamics. In controls, dynamic EEG-derived features significantly predicted general mental ability, whereas the same framework failed in JME. Because prediction in controls was driven mainly by dynamic measures of smoothness (Dirichlet energy), we next examined the temporal organization of alpha-power smoothness using an inverse Langevin framework. Within the patient group, greater thermodynamic rigidity--that is, stronger confinement of fluctuations around preferred network states--was associated with lower general mental ability. Relative to controls, patients also showed lower thermodynamic noise, indicating a reduced tendency to explore alternative network regimes. Biophysical simulations suggested that reduced dendritic arborization can generate rigidity directly, whereas pharmacological stabilization of hyperexcitable circuits can shift the system toward a more rigid, lower-noise regime. Together, these findings suggest that cognition in JME is linked not only to altered resting-state network dynamics but also to stronger confinement of network-state fluctuations, with both intrinsic circuit abnormalities and treatment-related stabilization representing plausible routes to this rigid phenotype.