State space analysis of synchronous spiking in cortical neural networks

Abstract Recent proposals that information in cortical neurons may be encoded by precise spike timing have been challenged by the assumption that neurons in vivo can only operate in a noisy fashion, due to large fluctuations in synaptic input activity. Here, we show that despite the background, volleys of precisely synchronized action potentials can stably propagate within a model network of basic integrate-and-fire neurons. The construction of an iterative mapping for the transmission of synchronized spikes between groups of neurons allows for a two-dimensional state space analysis. An attractor, yielding stable spiking precision in the (sub-)millisecond range, governs the synchronization dynamics.