Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
33rd (2019)
Session ID : 3G3-OS-18a-04
Conference information

Extraction of Neuroscientific Findings by Visualization of Deep Neural Network
*Kazuki SAKUMAJunya MORITATaiki NOMURATakatsugu HIRAYAMAYu ENOKIBORIKenji MASE
Author information
Keywords: EEG, emotion, DNN
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract

Recently, research using deep learning has been conducted in various fields. Additionally, research on visualization methods learned by deep learning has also been actively conducted. Furthermore, the relationship between the human subjective state and electroencephalogram (EEG) has been clarified in the psychophysiological field. In this research, we apply the visualization method developed in the image field to the analysis of EEG. Using this method, we examine whether we can abstract physiologically reasonable structure of brain activity from the network visualizing EEG signals.The result of our experiment indicated the two important brain structures showing consistency with the previous neuroscience studies. We consider that our proposed method has some utilities as a tool to progress scientific understanding of human mind.

Content from these authors
© 2019 The Japanese Society for Artificial Intelligence
Previous article Next article
feedback
Top