Examination of the brain areas related to cognitive performance during the stroop task using deep neural network

Tomohiro Nishikawa*, Yushi Hashimoto, Kosei Minami, Keiichi Watanuki, Kazunori Kaede, Keiichi Muramatsu

*この研究の対応する著者

研究成果: Conference contribution

抄録

To examine brain areas related to the cognitive load condition during the Stroop task, we proposed a method using a Deep Neural Network (DNN). We acquired cerebral blood flow data in congruent and incongruent tasks by near-infrared spectroscopy (NIRS) equipped with 22 ch. The data were used to train a DNN, and the influence of each factor on the output was evaluated. Our DNN model consists of independent input layers for each channel of NIRS, as well as fully-connected hidden layers and output layers. Our results suggest that the medial prefrontal cortex (focusing on cognition) and the left inferior frontal gyrus (focusing on language processing) were involved in the cognitive load during the Stroop task. These results in the Stroop task were consistent. Therefore, the proposed method’s utility was confirmed.

本文言語English
ホスト出版物のタイトルAdvances in Affective and Pleasurable Design - Proceedings of the AHFE 2018 International Conference on Affective and Pleasurable Design, 2018
編集者Shuichi Fukuda
出版社Springer Verlag
ページ94-101
ページ数8
ISBN(印刷版)9783319949437
DOI
出版ステータスPublished - 2019
外部発表はい
イベントAHFE International Conference on Affective and Pleasurable Design, 2018 - Orlando, United States
継続期間: 2018 7 212018 7 25

出版物シリーズ

名前Advances in Intelligent Systems and Computing
774
ISSN(印刷版)2194-5357

Conference

ConferenceAHFE International Conference on Affective and Pleasurable Design, 2018
国/地域United States
CityOrlando
Period18/7/2118/7/25

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンス(全般)

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