Artificial grammar recognition using two spiking neural networks

Philip Cavaco, Baran Curuklu, Magnus Karl-Petersson
1970 Frontiers in Neuroinformatics  
In this paper we explore the feasibility of artificial (formal) grammar recognition (AGR) using spiking neural networks. A biologically inspired minicolumn architecture is designed as the basic computational unit. A network topography is defined based on the minicolumn architecture, here referred to as nodes, connected with excitatory and inhibitory connections. Nodes in the network represent unique internal states of the grammar's finite state machine (FSM). Future work to improve the
more » ... ce of the networks is discussed. The modeling framework developed can be used by neurophysiological research to implement network layouts and compare simulated performance characteristics to actual subject performance.
doi:10.3389/conf.neuro.11.2009.08.096 fatcat:ue6kzuxd7nbtdbjheeuy6el4sa