Rescorla (in press) investigated the change in associative strength undergone by cues A and B as a result of reinforcement or nonreinforcement of an AB compound. Many leading theories of associative learning predict that if A and B are equally salient then the associative change experienced by each should be the same regardless of their associative strength preceding AB trials. Rescorla explore...

This paper proposes Neural Network architecture for implementing associative memory. A new model has been developed that has good learning structure and high storage capacity. Hybrid Network Learning comprises interactive counter propagation network and associative memory. Interactive counter propagation network is used for pattern completion. The associative memory is applied for pattern assoc...

Associative learning is an important part of human cognition, and is thought to play key role in list learning. We present here an account of associative learning that learns asymmetric itemto-item associations, strengthening or weakening associations over time with repeated exposures. This account, combined with an existing account of activation strengthening and decay, predicts the complicate...

An increasing number of empirical phenomena that were previously interpreted as a result of cognitive control, turn out to reflect (in part) simple associative-learning effects. A prime example is the proportion congruency effect, the finding that interference effects (such as the Stroop effect) decrease as the proportion of incongruent stimuli increases. While this was previously regarded as s...

Two connectionist models of attention in associative learning, previously used to model human category learning, are shown to have special cases that are essentially equivalent to N. J. Mackintosh's (1975, Psychological Review, 82, 276 298) classic model of attention in animal learning. The models unify formulas for associative weight change with formulas for attentional change, under a common ...

We consider application of neural associative memories to chemical image recognition. Chemical image recognition is identification of substance using chemical sensors' data. The primary advantage of associative memories as compared with feed-forward neural networks is highspeed learning. We have made experiments on odour recognition using hetero-associative and modular autoassociative memories....

An explanation for the acquisition of word-object mappings is the associative learning in a crosssituational scenario. Here we present analytical results of the performance of a simple associative learning algorithm for acquiring a one-to-one mapping between N objects and N words based solely on the co-occurrence between objects and words. In particular, a learning trial in our learning scenari...

The brain mechanisms that enable us to form durable associations between different types of information are not completely understood. Although the hippocampus is widely thought to play a substantial role in forming associations, the role of surrounding cortical regions in the medial temporal lobe, including perirhinal and parahippocampal cortex, is controversial. Using anatomically constrained...