4.7 Article

Oscillatory model of attention-guided object selection and novelty detection

Journal

NEURAL NETWORKS
Volume 17, Issue 7, Pages 899-915

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2004.03.005

Keywords

oscillatory neural networks; synchronization; resonance; selective attention; novelty detection

Funding

  1. Biotechnology and Biological Sciences Research Council [BB/G006369/1] Funding Source: Medline

Ask authors/readers for more resources

We develop a new oscillatory model that combines consecutive selection of objects and discrimination between new and familiar objects. The model works with visual information and fulfils the following operations: (1) separation of different objects according to their spatial connectivity: (2) consecutive selection of objects located in the visual field into the attention focus; (3) extraction of features; (4) representation of objects in working memory; (5) novelty detection of objects. The functioning of the model is based on two main principles: the synchronization of oscillators through phase-locking and resonant increase of the amplitudes of oscillators if they work in-phase with other oscillators. The results of computer simulation of the model are described for visual stimuli representing printed words. (C) 2004 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available