Publications Details

Acquisition and representation of spatio-temporal signals in polychronizing spiking neural networks

Wang, Felix W.; Severa, William M.; Rothganger, Fredrick R.

The ability of an intelligent agent to process complex signals such as those found in audio or video depends heavily on the nature of the internal representation of the relevant information. This work explores the mechanisms underlying this process by investigating theories inspired by the function of the neocortex. In particular, we focus on the phenomenon of polychronization, which describes the self-organization in a spiking neural network resulting from the interplay between network structure, driven spiking activity, and synaptic plasticity. What emerges are groups of neurons that exhibit reproducible, time-locked patterns of spiking activity. We propose that this representation is well suited to spatio-temporal signal processing, as it naturally resembles patterns found in real-world signals. We explore the computational properties of this approach and demonstrate the ability of a simple polychronizing network to learn different spatio-temporal signals.