Understanding of Human Perceptual-Alternation Phenomena and its Neural Network Model

人类知觉交替现象及其神经网络模型的理解

• 批准号: 07680410
• 负责人: MATSUI Nobuyuki
• 金额: $ 1.41万
• 依托单位: HIMEJI INSTITUTE OF TECHNOLOGY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 1995
• 资助国家: 日本
• 起止时间: 1995 至 1996
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07680410/
• 关键词: ambiguous figure; visual perception; perceptual-alternation; neural network information processing; Gamma distribution; Chaos; neuron firing-rate; perceptual duration time

In this research, we dealt with the phenomena of human perceptual-alternation at the time one observes the ambiguous figures such as the "Rubin's face and vase". Using a primary model based on the multilayr neural network proposed by M.Riani et al. to represent the information processing in the higher level of brain for this phenomenon, we examined the input pattern-dependence of the firing-rate for the perceptual-alternation. In our approach, this alternation is interpreted as that of the rate of firing neurons for the pattern perceived. Experimentally, we could obtain the Gamma distribution of the perceptual duration of the alternating interpretations. We then regards this Gamma distribution as the universal character of the perceptual alternation. From our result of computer simulation we could show the efficiency of the model. In particular, we have shown the chaotic behavior of visual inputs corresponding to attention eye movement makes it possible to obtain clearer the Gamma distributions than those of the random and/or 1/f visual behavior. We also find some other efficiencies of the chaotic inputs, for example, such as the input pattern-dependence of the rate of firing neurons and discuss an other model, for example, the chaotic neural network.

在这项研究中，我们在人们观察到“鲁宾的脸和花瓶”等模棱两可的人物时处理了人类感知态度的现象。使用基于M.Riani等人提出的多层神经网络的主要模型。为了代表这种现象中大脑较高水平的信息处理，我们检查了感知抗性的发射率的输入模式依赖性。在我们的方法中，这种交替被解释为对所感知的模式发射神经元的速率。在实验上，我们可以获得交替解释的感知持续时间的伽马分布。然后，我们将此伽马分布视为感知交替的普遍特征。根据计算机模拟的结果，我们可以显示模型的效率。特别是，我们已经显示了与注意力转移相对应的视觉输入的混乱行为，使得比随机和/或1/F视觉行为的伽马分布更清晰。我们还发现了混乱输入的其他一些效率，例如，射击神经元的输入模式依赖性，并讨论其他模型，例如混乱的神经网络。

项目成果

Nobuyuki Matsui: "The Efficiency of the Chaotic Visual Behaviour in Modeling the Human Perceptual-Alternation by Artificial Neural Network" Proceedings of 1995 IEEE International Conference on Neural Networks. Vol.4. 1991-1994 (1995)

Nobuyuki Matsui：“通过人工神经网络模拟人类感知交替的混沌视觉行为的效率”1995 年 IEEE 国际神经网络会议论文集。

Nobuyuki Matsui, Takayuki Mori: "The Efficiency of the Chaotic Visual Behavior in Modeling the Human Perceptional-Alternation by Artificial Neural Network" Proceedings of the IEEE International Conference on Neural Networks. Vol.4. 1991-1994 (1995)

Nobuyuki Matsui、Takayuki Mori：“通过人工神经网络模拟人类感知交替的混沌视觉行为的效率”IEEE 国际神经网络会议论文集。

長尾夏樹,西村治彦,松井伸之: "カオス・ニューラルネットワークによる認知ゆらぎの検討" 情報処理学会第53回全国大会講演論文集. 分冊2. 207-208 (1996)

Natsuki Nagao、Haruhiko Nishimura、Nobuyuki Matsui：“利用混沌神经网络研究认知波动”第 53 届日本信息处理学会全国会议论文集第 2 卷 207-208（1996 年）。

Natsuki Nagao, Haruhiko Nishimura, Nobuyuki Matsui: "A perception model of ambiguous patterns based on the chaotic neural networks" Proceedings of the 53th Annual Conference of Infomation processing of Japan. Vol.2. 207-208 (1996)

Natsuki Nagao、Haruhiko Nishimura、Nobuyuki Matsui：“基于混沌神经网络的模糊模式感知模型”第 53 届日本信息处理年会论文集。

松井伸之,森 栄之: "交代想起のANN表現におけるカオス挙動入力の効果" 1997年電子情報通信学会総合大会講演論文集. 情報・システム1. D-2-4-23 (1997)

Nobuyuki Matsui、Hideyuki Mori：“交替回忆的 ANN 表示中混沌行为输入的影响”1997 年 IEICE 信息与系统大会记录 1. D-2-4-23 (1997)。