PROPAGATION OF SYNCHRONOUS SPIKING ACTIVITY IN FEEDFORWARD NEURAL NETWORKS

'Synfire' activity has been proposed as a model for the experimentally observed accurate spike patterns in cortical activity. We investigate d the structural and dynamical aspects of this theory. To quantify the degree of spnchrony in neural activity, we introduced the concept of 'pulse packets'. This enabled us to derive a novel neural transmission function which was used to assess the role of the single neuron dynam ics and to characterize the stability conditions for propagating synfi re activity. Thus, we could demonstrate that the cortical network is a ble to sustain synchronous spiking activity using local feedforward (s ynfire) connections. This new approach opens the way for a quantitativ e description of neural network dynamics, and enables us to rest the s ynfire hypothesis on physiological data.