Statistical Mechanics of Spike Trains: Self-Consistent Activity Ensembles and Phase Transitions
How brains switch between steady and rhythmic firing modes
Researchers developed a physics-based framework for understanding when populations of neurons oscillate versus fire steadily, treating entire sequences of neural spikes as energy states similar to how physicists model physical matter. The model reveals that brain activity undergoes a phase transition—like water freezing into ice—where a competition between synaptic rules and random noise shifts neurons from one firing pattern to a completely different one.
Understanding these transitions could explain abnormal brain rhythms in epilepsy, sleep disorders, and neuropsychiatric conditions, where the brain gets stuck in pathological oscillations or fails to generate normal rhythmic activity like sleep spindles. The framework provides a new mathematical language for predicting when and why these shifts happen, potentially guiding development of therapies that nudge neural activity out of harmful states.