The Analysis and Decoding of Swallowing-related Neural Activities Using Intracranial Electrodes

• Hashimoto Hiroaki

  Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University Department of Neurosurgery, Otemae Hospital Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University

• Kameda Seiji

  Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University

• Maezawa Hitoshi

  Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University

• Oshino Satoru

  Department of Neurosurgery, Graduate School of Medicine, Osaka University

• Tani Naoki

  Department of Neurosurgery, Graduate School of Medicine, Osaka University

• Khoo Hui Ming

  Department of Neurosurgery, Graduate School of Medicine, Osaka University

• Yanagisawa Takufumi

  Department of Neurosurgery, Graduate School of Medicine, Osaka University

• Yoshimine Toshiki

  Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University

• Kishima Haruhiko

  Department of Neurosurgery, Graduate School of Medicine, Osaka University

• Hirata Masayuki

  Department of Neurological Diagnosis and Restoration, Graduate School of Medicine, Osaka University Endowed Research Department of Clinical Neuroengineering, Global Center for Medical Engineering and Informatics, Osaka University Department of Neurosurgery, Graduate School of Medicine, Osaka University

Bibliographic Information

Other Title

• 頭蓋内電極を用いた嚥下関連脳活動の解析と解読

Abstract

The present study clarified the swallowing-related neural activities using human intracranial electrodes. Eight epileptic participants fitted with intracranial electrodes on the orofacial cortex were asked to swallow a water bolus, and cortical oscillatory changes were investigated. High γ (75-150 Hz) power increases associated with swallowing were observed in the subcentral area. To decode swallowing intention, ECoG signals were converted into images whose vertical axes were the electrode’s contacts and whose horizontal axis was the time in milliseconds; these findings were used as training data. Deep transfer learning was carried out using AlexNet, and the power in the high-γ band was used to create the training image set. The accuracy reached 74%, and the sensitivity reached 83%. We showed that a version of AlexNet pre-trained with visually meaningful images can be used for transfer learning of visually meaningless images made up of ECoG signals. This study demonstrated that swallowing-related high γ activities were observed in the subcentral area, and deep transfer learning using high γ activities enabled us to decode the swallowing-related neural activities.

Journal

• Koutou (THE LARYNX JAPAN)

  Koutou (THE LARYNX JAPAN) 32 (02), 165-171, 2020-12-01

  THE JAPAN LARYNGOLOGICAL ASSOCIATION

Keywords

• swallowing-related neural activity
• high γ band
• deep transfer learning
• intracranial electrodes

Details

• CRID: 1390850932918182016
• NII Article ID: 130008036947
• DOI: 10.5426/larynx.32.165
• ISSN: 21854696
• ISSN: 09156127
• Web Site: https://www.jstage.jst.go.jp/article/larynx/32/02/32_165/_pdf
• Web Site: https://search.jamas.or.jp/link/ui/2021119409
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed