Maximum entropy models of neuronal populations at and off criticality

TL;DR

This study investigates the relationship between neuronal avalanche criticality and thermodynamic signatures in maximum entropy models, revealing that these models distinguish subcritical from critical and supercritical states but cannot differentiate between critical and supercritical regimes.

Contribution

The paper demonstrates that maximum entropy models reflect criticality in thermodynamic measures for neuronal populations, but cannot distinguish between critical and supercritical states.

Findings

ME models show thermodynamic signatures in critical and supercritical cultures

Subcritical cultures lack thermodynamic signatures of criticality

Models can distinguish subcritical from critical/supercritical but not between critical and supercritical

Abstract

Empirical evidence of scaling behaviors in neuronal avalanches suggests that neuronal populations in the brain operate near criticality. Departure from scaling in neuronal avalanches has been used as a measure of distance to criticality and linked to brain disorders. A distinct line of evidence for brain criticality has come from thermodynamic signatures in maximum entropy (ME) models. Both of these approaches have been widely applied to the analysis of neuronal data. However, the relationship between deviations from avalanche criticality and thermodynamics of ME models of neuronal populations remains poorly understood. To address this question, we study spontaneous activity of organotypic rat cortex slice cultures in physiological and drug-induced hypo- or hyper-excitable conditions, which are classified as critical, subcritical and supercritical based on avalanche dynamics. We find that ME models inferred from critical cultures show signatures of criticality in thermodynamic quantities, e.g. specific heat. However, such signatures are also present, and equally strong, in models inferred from supercritical cultures -- despite their altered dynamics and poor functional performance. On the contrary, ME models inferred from subcritical cultures do not show thermodynamic hints of criticality. Importantly, we confirm these results using an interpretable neural network model that can be tuned to and away from avalanche criticality. Our findings indicate that maximum entropy models correctly distinguish subcritical from critical/supercritical systems. However, they may not be able to discriminate between avalanche criticality and supercriticality, although they may still capture a number of important features from neuronal data.