A spiking neural network based cortex-like mechanism and application to facial expression recognition.
A spiking neural network based cortex-like mechanism and application to facial expression recognition.
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DOI：
10.1155/2012/946589
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发表时间：
2012
影响因子：
--
通讯作者：
Kuai XK
中科院分区：
文献类型：
--
作者：
Fu SY;Yang GS;Kuai XK
在本文中，我们提出了一个定量的、高度结构化的皮层模拟模型，它可以简单地描述为使用生物学上可信的、计算方便的脉冲神经网络系统来前馈、分层地模拟视觉皮质腹侧流。其动机直接来自于最近对视觉皮层腹侧流前馈通路的详细功能分解分析的开创性工作，以及人工放电神经网络(SNN)的发展。通过结合皮层层次的逻辑结构和脉冲神经元模型的计算能力，提出了一个实用的框架。作为原则的证明，我们在几个面部表情识别任务上演示了我们的系统。提出的皮质样前向层次结构框架具有处理复杂模式识别问题的能力，这表明，通过将认知模型与现代神经计算方法相结合，研究皮质样机制的神经系统方法有可能扩展我们对认知分析背后的大脑机制的认识，并推进我们如何在丰富、动态和复杂的环境中识别人脸或者更具体地说，感知他人面部表情的理论模型，为改进视觉皮质样机制模型提供了一个新的起点。
In this paper, we present a quantitative, highly structured cortex-simulated model, which can be simply described as feedforward, hierarchical simulation of ventral stream of visual cortex using biologically plausible, computationally convenient spiking neural network system. The motivation comes directly from recent pioneering works on detailed functional decomposition analysis of the feedforward pathway of the ventral stream of visual cortex and developments on artificial spiking neural networks (SNNs). By combining the logical structure of the cortical hierarchy and computing power of the spiking neuron model, a practical framework has been presented. As a proof of principle, we demonstrate our system on several facial expression recognition tasks. The proposed cortical-like feedforward hierarchy framework has the merit of capability of dealing with complicated pattern recognition problems, suggesting that, by combining the cognitive models with modern neurocomputational approaches, the neurosystematic approach to the study of cortex-like mechanism has the potential to extend our knowledge of brain mechanisms underlying the cognitive analysis and to advance theoretical models of how we recognize face or, more specifically, perceive other people's facial expression in a rich, dynamic, and complex environment, providing a new starting point for improved models of visual cortex-like mechanism.
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DOI：
10.1126/science.1194908
发表时间：
2010-11-05
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Freiwald WA;Tsao DY
通讯作者：
Tsao DY
影响因子：
25
作者：
Freiwald, Winrich A.;Tsao, Doris Y.;Livingstone, Margaret S.
通讯作者：
Livingstone, Margaret S.
影响因子：
4.1
作者：
Jack, Rachael E.;Caldara, Roberto;Schyns, Philippe G.
通讯作者：
Schyns, Philippe G.
影响因子：
2.9
作者：
Hyvärinen, A;Hoyer, PO;Inki, M
通讯作者：
Inki, M
影响因子：
1.8
作者：
Bell, AJ;Sejnowski, TJ
通讯作者：
Sejnowski, TJ