Antonio J. Fontenele

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.

This study examines whether Parkinson's disease alters criticality in motor cortex by analyzing EEG data and finding near-critical oscillations in patients.

The paper identifies a molecular signal that encodes within-bout sleep history by showing PKA-SP decreases exponentially during sleep and integrates sleep duration and interruption.

The paper identifies criticality signatures in cortical networks during synchronization onset, showing both intra- and inter-hemispheric coordination patterns.

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.

The paper develops a temporal renormalization group approach to assess criticality in neural activity and finds that the relaxed awake state is closest to criticality, while deep sleep and active states deviate from it.

The paper shows that awake mouse motor cortex has both a low-dimensional critical subspace and a high-dimensional desynchronized subspace, resolving a long-standing debate about cortical dynamics.

The paper shows sensory signals are encoded in low-dimensional subspaces correlated with upstream sensory regions, improving decoding accuracy and generalizing across sensory systems.

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.