The nucleus basalis (NB) has been implicated in memory formation indirectly, by lesions, pharmacological manipulations, and neural correlates of learning. Prior findings imply that engagement of the NB during learning promotes memory storage. We directly tested this NB-memory hypothesis by determining whether stimulation of the NB induces behavioral associative memory. Rats were trained either ...

Deduction, induction and analogy are considered as slightly different manifestations of one and the same reasoning process. A model of this reasoning process called associative memory-based reasoning is proposed. A computer simulation demonstrates that deduction, induction and analogy in problem solving could be performed by a single mechanism which combines the neural network approach with sym...

is learned, it is stored in the brain, from e recalled later when required. Memory G y be d i v i d m t e r m ’ ” x m o r y , depending on the retention time (Arbib, 1989). Short-term memory refers to a compilation of knowledge representing the “current” state of the environment. Any discrepancies between knowledge stored in short-term memory and a “new” state are used to update the short-term ...

In this paper, we propose a Hetero Chaotic Associative Memory for Successive Learning (HCAMSL) with give up function. The proposed model is based on a Chaotic Associative Memory for Successive Memory (CAMSL). In the proposed HCAMSL, the learning process and the recall process are not divided. When an unstored pattern is given to the network, the HCAMSL can learn the pattern successively.

This paper presents a generalized associative memory model, which stores a collection of tuples whose components are sets rather than scalars. It is shown that all library patterns are stored stably. On the other hand spurious memories may develop. Applications of this model to storage and retrieval of naturallyarising generalized sequences in bioinformatics are presented. The model is shown to...

This paper argues that immunological memory is in the same class of associative memories as Kanerva’s Sparse Distributed Memory, Albus’s Cerebellar Model Arithmetic Computer, and Marr’s Theory of the Cerebellar Cortex. This class of memories derives its associative and robust nature from a sparse sampling of a huge input space by recognition units (B and T cells in the immune system) and a dist...

One of the simplest associative memories is the Willshaw Network (Willshaw, Buneman & Longuet-Higgins, 1969). Like other associative networks however (e.g., Hopfield, 1982), it fails completely as a memory device as soon as its capacity is exceeded. Three methods of synaptic change are analysed, decay, ageing and depression, under which this catastrophic failure can be preempted and stability u...

Using synthetic faces that varied along four perceptual dimensions (Wilson, Loffler, & Wilkinson, 2002), we examined the effects of face similarity on memory for face-name associations. The nature of these stimuli allowed us to go beyond the categorical similarity manipulations used in previous verbal associative memory studies to trace out the parametric relation between similarity and various...

This paper proposes an associative memory neural network whose limiting state is the nearest point in a polyhedron from a given input. Two implementations of the proposed associative memory network are presented based on Dykstra’s algorithm and a fixed point theorem for nonexpansive mappings. By these implementations, the set of all correctable errors by the network is characterized as a dual c...

Quantum computation uses microscopic quantum level effects to perform computational tasks and has produced results that in some cases are exponentially faster than their classical counterparts. The unique characteristics of quantum theory may also be used to create a quantum associative memory with a capacity exponential in the number of neurons. This paper combines two quantum computational al...