ROC mROC Memory Neural Network Cue Index Recall Recognition Signal Detection Theory
Institute of Information Theories and Applications FOI ITHEA
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.