Segmentation and binding in an oscillatory neural network

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Abstract

The authors present a model of coupled oscillating neural networks which can simultaneously perform segmentation and binding. The two networks have memory patterns which are independent of one another, yet the input contains them in pairs as, for instance, objects and attributes. When presented with a mixture of such pairs in a constant input, the activities of the corresponding patterns oscillate in a staggered fashion, exhibiting segmentation. Moreover, the phases of the pairs lock with each other, demonstrating binding. The underlying networks are feedback systems which are composed of excitatory neurons grouped into cell-assemblies representing the memories and inhibitory interneurons to which they are connected. The oscillatory nature comes about by dynamic thresholds which implement a fatigue effect for the excitatory neurons.

Original languageEnglish
Title of host publicationProceedings. IJCNN - International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages243-248
Number of pages6
ISBN (Print)0780301641
StatePublished - 1992
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: 8 Jul 199112 Jul 1991

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Conference

ConferenceInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period8/07/9112/07/91

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