Statistical learning refers to the ability to identify structure in the input based on its statistical properties. For many linguistic structures, the relevant statistical features are distributional: They are related to the frequency and variability of exemplars in the input. These distributional regularities have been suggested to play a role in…

A theory for storage and retrieval of associative information is presented. Items or events are represented as random vectors. Convolution is used as the storage operation, correlation as the retrieval operation. A distributed memory system is assumed. The theory applies to recognition and recall and covers both accuracy and latency. (Author/RD)

A model of association formation, storage, and retrieval is described. Experiments which test new predictions derived from the model against human recall are reported. The model is applied to previous findings: prototype abstraction, the A-B A-D paradigm and the Osgood transfer surface. Previous models of memory are discussed. (Author/RD)

The cascade model of information processing is compatible with the relation between time and accuracy in speed-accuracy trade-off experiments. Findings regarding the additive factors methods led to reexamination of conclusions drawn from several studies about the locus of perceptual and attentional effects on processing. (Author/RD)