  On the basis of convolutional (Hamming) version of recent Neural Network
Assembly Memory Model (NNAMM) for intact two-layer autoassociative Hopfield
network optimal receiver operating characteristics (ROCs) have been derived
analytically. A method of taking into account explicitly a priori probabilities
of alternative hypotheses on the structure of information initiating memory
trace retrieval and modified ROCs (mROCs, a posteriori probabilities of correct
recall vs. false alarm probability) are introduced. The comparison of empirical
and calculated ROCs (or mROCs) demonstrates that they coincide quantitatively
and in this way intensities of cues used in appropriate experiments may be
estimated. It has been found that basic ROC properties which are one of
experimental findings underpinning dual-process models of recognition memory
can be explained within our one-factor NNAMM.
