基礎心理学研究
Online ISSN : 2188-7977
Print ISSN : 0287-7651
ISSN-L : 0287-7651
シンポジウム1 基礎心理学研究における深層学習の役割
深層ニューラルネットワークはヒトの視知覚理解に役立つか?
白石 祥之
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ジャーナル フリー

2022 年 41 巻 1 号 p. 43-48

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To understand the experience of seeing is difficult and is being pursued day and night, especially in psychology and neuroscience. However, there are hard areas to research, such as estimating the structure of receptive fields (RF) in the higher-order visual cortex with humans and animals as research targets. Deep neural networks (DNNs) are being reported that have similar properties to visual neurons and the possibility of using DNNs as alternative research targets to the biological brain has emerged. Therefore, in this paper, I discuss whether DNNs can be our research subject. In this research, I applied the reverse correlation method, which has revealed RF of visual neurons, to DNNs to estimate RF of units in well-trained VGG-16. As a result, the properties of the RF of VGG-16 units were similar to visual cortex neurons. The result suggested that DNNs may be a good alternative model for our research, but also suggested limitations of the method. To solve remaining problems, psychology research that develop the better methods and deep learning research that provides better alternative models must go hand in hand.

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