Oscillatory model of attention-guided object selection and novelty detection

Authors:
Roman M. Borisyuk;Yakov B. Kazanovich
Affiliations:
Centre for Theoretical & Computational Neuroscience, University of Plymouth, Plymouth PL4 8AA, UK and Institute of Mathematical Problems in Biology, Russian Academy of Sciences, Pushchino, Moscow ...;Centre for Theoretical & Computational Neuroscience, University of Plymouth, Plymouth PL4 8AA, UK and Institute of Mathematical Problems in Biology, Russian Academy of Sciences, Pushchino, Moscow ...
Venue:
Neural Networks
Year:
2004

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Abstract

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.