A multiple synfire-chain model for the predictive synchrony in the motor-related cortical areas

The intrinsic properties of ´synfire chain´, the feedforward network propagating synchronous spike packets, has been studied so far. Possible functional roles of the synfire chain, however, has been poorly understood. Considering that coordinated activities of multiple synfire chains can serve as a reference time, we study whether a network model based on the multiple synfire chains contributes to generation of predictive synchrony to occurrence times of external events, observed in the primary motor cortex. In our model, neurons that code occurrence times of external events are partly innervated by the multiple synfire chains. The event times are embedded into the synaptic projections between layers that coincide with the events and event coding neurons through spike-timing-dependent synaptic learning. From our simulation results, it is found that our model can generate the predictive synchrony when the ratio of the projections is within a suitable range.