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基于特征的空间选择的神经动力学模型。

A Neurodynamic Model of Feature-Based Spatial Selection.

作者信息

Marić Mateja, Domijan Dražen

机构信息

Department of Psychology, Faculty of Humanities and Social Sciences, University of Rijeka, Rijeka, Croatia.

出版信息

Front Psychol. 2018 Mar 28;9:417. doi: 10.3389/fpsyg.2018.00417. eCollection 2018.

DOI:10.3389/fpsyg.2018.00417
PMID:29643826
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5883145/
Abstract

Huang and Pashler (2007) suggested that feature-based attention creates a special form of spatial representation, which is termed a Boolean map. It partitions the visual scene into two distinct and complementary regions: selected and not selected. Here, we developed a model of a recurrent competitive network that is capable of state-dependent computation. It selects multiple winning locations based on a joint top-down cue. We augmented a model of the WTA circuit that is based on linear-threshold units with two computational elements: dendritic non-linearity that acts on the excitatory units and activity-dependent modulation of synaptic transmission between excitatory and inhibitory units. Computer simulations showed that the proposed model could create a Boolean map in response to a featured cue and elaborate it using the logical operations of intersection and union. In addition, it was shown that in the absence of top-down guidance, the model is sensitive to bottom-up cues such as saliency and abrupt visual onset.

摘要

黄和帕什勒（2007年）提出，基于特征的注意力会创建一种特殊形式的空间表征，即所谓的布尔地图。它将视觉场景划分为两个截然不同且互补的区域：被选中的和未被选中的。在此，我们开发了一种递归竞争网络模型，该模型能够进行状态依赖型计算。它基于联合的自上而下线索选择多个获胜位置。我们对基于线性阈值单元的胜者全得（WTA）电路模型进行了扩充，增加了两个计算元素：作用于兴奋性单元的树突非线性以及兴奋性和抑制性单元之间突触传递的活动依赖型调制。计算机模拟表明，所提出的模型能够响应特征线索创建布尔地图，并使用交集和并集的逻辑运算对其进行细化。此外，研究表明，在没有自上而下引导的情况下，该模型对自下而上的线索（如显著性和视觉突然出现）敏感。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/6a6f0d9288c1/fpsyg-09-00417-g0013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/dbe68939bd0a/fpsyg-09-00417-g0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/d1fe842ffef9/fpsyg-09-00417-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/5a258378cb6d/fpsyg-09-00417-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/abc410f817e6/fpsyg-09-00417-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/9c36975e2c5f/fpsyg-09-00417-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/97316b0df5ee/fpsyg-09-00417-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/8df72923822b/fpsyg-09-00417-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/4afbcaa58965/fpsyg-09-00417-g0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/a39f5c4c6880/fpsyg-09-00417-g0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/6a6f0d9288c1/fpsyg-09-00417-g0013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/dbe68939bd0a/fpsyg-09-00417-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/e6f29adb055c/fpsyg-09-00417-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/ad34f9bf534b/fpsyg-09-00417-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/09c03f290cc1/fpsyg-09-00417-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/d1fe842ffef9/fpsyg-09-00417-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/5a258378cb6d/fpsyg-09-00417-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/abc410f817e6/fpsyg-09-00417-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/9c36975e2c5f/fpsyg-09-00417-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/97316b0df5ee/fpsyg-09-00417-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/8df72923822b/fpsyg-09-00417-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/4afbcaa58965/fpsyg-09-00417-g0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/a39f5c4c6880/fpsyg-09-00417-g0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f347/5883145/6a6f0d9288c1/fpsyg-09-00417-g0013.jpg

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