Volume 10 Supplement 1
Artificial grammar recognition using spiking neural networks
© Cavaco et al; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
A biologically inspired neocortical model consisting of spiking neurons is designed to perform artificial grammar processing. Building on work in , the model is designed to categorize symbol strings as belonging to a Reber grammar . Columnar organization of the cortex is used as the general inspiration of the network [3, 4].
- Petersson KM: Artificial grammar learning and neural networks. Proc Cogn Sci Soc. 2005, 1726-1731.Google Scholar
- Reber AS: Implicit learning of artificial grammar. J Verb Learn & Verb Behav. 1967, 6: 855-863. 10.1016/S0022-5371(67)80149-X.View ArticleGoogle Scholar
- Çürüklü B: A Canonical Model of the Primary Visual Cortex. 2005, Mälardalen University PressGoogle Scholar
- Mountcastle VB: The columnar organization of the neocortex. Brain. 1997, 701-722. 10.1093/brain/120.4.701.Google Scholar
- Gewaltig MO, Diesmann M: NEST. Scholarpedia. 2007, 2: 1430.View ArticleGoogle Scholar
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