Theoretical and Computational Physics

Defining and measuring proximity to criticality

The paper develops a method to measure proximity to criticality in complex systems using a temporal renormalization group and information theory, applying it to brain activity data to show shifts in criticality during wakefulness and sleep.

Simulating neural network criticality and resource dynamics with Rydberg gases

This paper experiments with Rydberg gases to simulate neural network criticality and resource dynamics, finding peak temporal correlations and stochastic oscillations at criticality.

Critical Scaling Laws and Universality Classes in Biomolecular Condensates

The paper investigates criticality in biomolecular condensates using simulations, identifying critical exponents and two universality classes based on molecular interactions.

Distinguishing near- versus off-critical phase behaviors of intrinsically disordered proteins

This paper maps the critical regime of an intrinsically disordered protein using simulations and finite-size scaling, identifying three distinct phase behavior regimes.

Is critical brain dynamics more prevalent than previously thought?

This paper shows that criticality in brain dynamics may be more prevalent than previously thought, as traditional methods can miss it by failing to detect hidden criticality in subspaces.

Inferring global exponents in subsampled neural systems

This study shows that certain critical exponents in neural systems remain robust under subsampling, allowing for unbiased estimation of exponents from partial observations.

Hyperdisordered cell packing on a growing surface

The paper studies cell packing on a growing surface using squid skin chromatophores, finding hyperdisordered scaling and size distribution patterns.

Thermodynamic analog of integrate-and-fire neuronal networks by maximum entropy modelling

The paper applies maximum entropy modeling to integrate-and-fire neuronal networks to study criticality and finite-size effects in spontaneous activity.

Power spectrum and critical exponents in the 2D stochastic Wilson Cowan model

The paper analyzes a 2D stochastic Wilson Cowan model and finds different critical exponents compared to mean field models.

The 2D Ising model, criticality and AIT

The paper uses the 2D Ising model to explore links between criticality and complexity, focusing on phase transitions and their implications for neuroscience and information theory.

Critical behaviour of the stochastic Wilson-Cowan model

The paper analyzes the stochastic Wilson-Cowan model to show it exhibits critical behavior with scale-free avalanche dynamics and diverging relaxation times.

Robust Cortical Criticality and Diverse Neural Network Dynamics Resulting from Functional Specification

The paper shows that functional specification of neural layers leads to robust criticality in leaky neuron networks, independent of external stimuli strength.

Reconciliation of theoretical and empirical brain criticality via network heterogeneity

This paper introduces a heterogeneous neural network model that reconciles discrepancies between theoretical and empirical brain criticality by incorporating synchronization effects in feedforward connectivity.

Criticality between cortical states

The paper shows that the cerebral cortex operates near a critical phase transition in spiking variability, with critical exponents distinct from mean-field directed percolation.