Associative learning underlies the formation of new episodic memories. Associative memory improves across development, and this age-related improvement is supported by the development of the hippocampus and pFC. Recent work, however, additionally suggests a role for visual association cortex in the formation of associative memories. This study investigated the role of category-preferential visu...

The effect of emotional arousal on memory presents a complex pattern with previous studies reporting conflicting results of both improved and reduced memory performance following arousal manipulations. In this study we further tested the effect of negative emotional arousal (NEA) on individual-item recognition and associative recognition of neutral stimuli in healthy participants, and hypothesi...

The purpose of this paper is to show how fundamental results from variational approximation theory can be exploited to design recurrent associative memory networks. We begin by stating the problem of learning a set of given patterns to an associative memory network as a hypersurface construction problem, then we show that the associated approximation problem is well posed. Characterizing and de...

| We apply evolutionary computations to Hopeld's neural network model of associative memory. In the Hop eld model, almost in nite number of combinations of synaptic weights give a network a function of associative memory. Furthermore, there is a trade-o between the storage capacity and size of basin of attraction. Therefore, the model can be thought of as a test suite of multi-modal and/or mult...

The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions....

In this paper a Cellular Fuzzy Associative Memory containing fuzzy rules for bidimensional image fuzzification in robot vision systems is developed. This cellular processor constitutes a subsystem of a CNNbased architecture which can store both bidimensional patterns and the rules to process them. After establishing the fuzzy rules characterizing the Fuzzy Associative Memory, a CNN behaving as ...

Image compression often leads to undesired artifacts. This paper shows an image restoration approach to correct for these artifacts by an associative memory. Investigations for modeling the coder-decoder process by a linear system are described. A compensating system consisting of a neural network based associative memory has been developed to process the degraded result after compression/decom...

We apply evolutionary algorithms to Hop eld model of associative memory. Previously we reported that a genetic algorithm using ternary chromosomes evolves the Hebb-rule associative memory to enhance its storage capacity by pruning some connections. This paper describes a genetic algorithm using real-encoded chromosomes which successfully evolves over-loaded Hebbian synaptic weights to function ...

In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associati...

We apply evolutionary computations to Hop eld model of associative memory. Although there have been a lot of researches which apply evolutionary techniques to layered neural networks, their applications to Hop eld neural networks remain few so far. Previously we reported that a genetic algorithm using discrete encoding chromosomes evolves the Hebb-rule associative memory to enhance its storage ...