Spatiotemporal characteristics of cortical activities of REM sleep behavior disorder revealed by explainable machine learning using 3D convolutional neural network

Author:

Kim Hyun,Seo Pukyeong,Byun Jung-Ick,Jung Ki-Young,Kim Kyung Hwan

Abstract

AbstractIsolated rapid eye movement sleep behavior disorder (iRBD) is a sleep disorder characterized by dream enactment behavior without any neurological disease and is frequently accompanied by cognitive dysfunction. The purpose of this study was to reveal the spatiotemporal characteristics of abnormal cortical activities underlying cognitive dysfunction in patients with iRBD based on an explainable machine learning approach. A convolutional neural network (CNN) was trained to discriminate the cortical activities of patients with iRBD and normal controls based on three-dimensional input data representing spatiotemporal cortical activities during an attention task. The input nodes critical for classification were determined to reveal the spatiotemporal characteristics of the cortical activities that were most relevant to cognitive impairment in iRBD. The trained classifiers showed high classification accuracy, while the identified critical input nodes were in line with preliminary knowledge of cortical dysfunction associated with iRBD in terms of both spatial location and temporal epoch for relevant cortical information processing for visuospatial attention tasks.

Funder

the Ministry of Science, ICT & Future Planning

the Korea Institute of Science and Technology

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. REM sleep behaviour disorder (RBD): Personal perspectives and research priorities;Journal of Sleep Research;2024-05-23

2. Enhancing Accuracy of Sleep Disorder with Logistic Regression Model;2023 IEEE 2nd International Conference on Industrial Electronics: Developments & Applications (ICIDeA);2023-09-29

3. Update on Rapid-Eye-Movement Sleep Behavior Disorder (RBD): Focus on Its Strong Association with α-Synucleinopathies;Clinical and Translational Neuroscience;2023-07-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3