| Abstract: | Correction Notice: An erratum for this article was reported in Vol 92(4) of Psychological Review (see record 2008-10982-001). In this article, there were two erroneous sentences, one on page 284 and one on page 285. The sentences are corrected in the erratum.] Compares 2 closely related distributed memory models in terms of plausibility; arithmetic simplicity; economy of storage space; and ability to account for associative, similarity, and order data in recall and recognition. It is argued that the storage-retrieval system brought about by the convolution-correlation concept outlined by M. A. Eich (see record 1983-04922-001) and B. B. Murdock (see record 1983-04936-001) is neurally implausible, necessitates more complex analyses, and is less economical in storage space than is the matrix memory concept described by J. A. Anderson et al (see record 1978-22353-001). It is shown that the matrix model can easily account for associative symmetry–asymmetry data and for item similarity effects. Means and variances of operating strength for various recall and recognition situations, modeled by the matrix system, are presented, and it is shown how signal-to-noise ratios can be derived. (25 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
