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注意力引导的对象选择与新奇性检测的振荡模型。

Oscillatory model of attention-guided object selection and novelty detection.

作者信息

Borisyuk Roman M, Kazanovich Yakov B

机构信息

Centre for Theoretical & Computational Neuroscience, University of Plymouth, Plymouth PL4 8AA, UK.

出版信息

Neural Netw. 2004 Sep;17(7):899-915. doi: 10.1016/j.neunet.2004.03.005.

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.

摘要

我们开发了一种新的振荡模型,该模型结合了对象的连续选择以及新对象与熟悉对象之间的区分。该模型处理视觉信息并执行以下操作:(1) 根据空间连通性分离不同对象;(2) 将视野中定位的对象连续选择到注意力焦点;(3) 特征提取;(4) 在工作记忆中表示对象;(5) 对象的新颖性检测。该模型的运行基于两个主要原则:通过锁相实现振荡器同步,以及如果振荡器与其他振荡器同相工作则振荡器振幅共振增加。针对表示印刷文字的视觉刺激描述了该模型的计算机模拟结果。

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