Artificial grammar learning and neural networks

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 processin

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Adaptability of Older Workers to Technological Change: Performance in Retraining

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86678/1/j.1464-0597.1962.tb00453.x.pd