  Although recent neurophysiological experiments suggest that synchronous
neural activity is involved in some perceptual and cognitive processes, the
functional role of such coherent neuronal behavior is not well understood. As a
first step in clarifying this role, we investigate how the temporal coherence
of certain neuronal activity affects the activity pattern in a neural network.
Using a simple network of leaky integrate-and-fire neurons, we study the
effects of synchronized incoming spikes on the functioning of two mechanisms
typically used in model neural systems, winner-take-all competition and
associative memory. We demonstrate that a pair of switches undergone by the
incoming spikes, from asynchronous to synchronous and then back to
asynchronous, triggers a transition of the network from one state to another
state. In the case of associative memory, for example, this switching controls
the timing of the next recalling, whereas the firing rate pattern in the
asynchronous state prepares the network for the next retrieval pattern.
