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Conference Paper

Artificial grammar learning and neural networks

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Petersson, K. M., Grenholm, P., & Forkstam, C. (2005). Artificial grammar learning and neural networks. In G. B. Bruna, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th Annual Conference of the Cognitive Science Society (pp. 1726-1731).

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-39F2-8
Recent FMRI studies indicate that language related brain regions are engaged in artificial grammar (AG) processing. In the present study we investigate the Reber grammar by means of formal analysis and network simulations. We outline a new method for describing the network dynamics and propose an approach to grammar extraction based on the state-space dynamics of the network. We conclude that statistical frequency-based and rule-based acquisition procedures can be viewed as complementary perspectives on grammar learning, and more generally, that classical cognitive models can be viewed as a special case of a dynamical systems perspective on information processing