How spiking brain networks learn and replay sequences with precise timing

Researchers extended a biologically inspired spiking neural network model to encode not just *what* happens in a sequence but *when*. Sequential activation of neuronal populations represents element duration, while oscillatory background signals act as a clock to flexibly control replay speed. This explains how brains might learn complex temporal patterns and why sleep spindles or theta oscillations correlate with sequence replay.