Thomas P Trappenberg | PubMed Health

PubMed2002

A unified model of spatial and episodic memory.

Medial temporal lobe structures including the hippocampus are implicated by separate investigations in both episodic memory and spatial function. We show that a single recurrent attractor network can store both the discrete memories that characterize episodic memory and the continuous representations that characterize physical space. Combining both types of representation in a single network is actually necessary if objects and where they are located in space must be stored. We thus show that episodic memory and spatial theories of medial temporal lobe function can be combined in a unified model.

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PubMedDate not supplied

Modelling divided visual attention with a winner-take-all network.

Experimental evidence on the distribution of visual attention supports the idea of a spatial saliency map, whereby bottom-up and top-down influences on attention are integrated by a winner-take-all mechanism. We implement this map with a continuous attractor neural network, and test the ability of our model to explain experimental evidence on the distribution of spatial attention. The majority of evidence supports the view that attention is unitary, but recent experiments provide evidence for split attentional foci. We simulate two such experiments. Our results suggest that the ability to divide attention depends on sustained endogenous signals from short term memory to the saliency map, stressing the interplay between working memory mechanisms and attention.

Algorithms↗