Separating Inhibitory and Excitatory Responses of Epileptic Brain to Single-Pulse Electrical Stimulation.

IF 6.6 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
International Journal of Neural Systems Pub Date : 2023-02-01 Epub Date: 2022-12-10 DOI:10.1142/S0129065723500089
Sepehr Shirani, Antonio Valentin, Gonzalo Alarcon, Farhana Kazi, Saeid Sanei
{"title":"Separating Inhibitory and Excitatory Responses of Epileptic Brain to Single-Pulse Electrical Stimulation.","authors":"Sepehr Shirani,&nbsp;Antonio Valentin,&nbsp;Gonzalo Alarcon,&nbsp;Farhana Kazi,&nbsp;Saeid Sanei","doi":"10.1142/S0129065723500089","DOIUrl":null,"url":null,"abstract":"<p><p>To enable an accurate recognition of neuronal excitability in an epileptic brain for modeling or localization of epileptic zone, here the brain response to single-pulse electrical stimulation (SPES) has been decomposed into its constituent components using adaptive singular spectrum analysis (SSA). Given the response at neuronal level, these components are expected to be the inhibitory and excitatory components. The prime objective is to thoroughly investigate the nature of delayed responses (elicited between 100[Formula: see text]ms-1 s after SPES) for localization of the epileptic zone. SSA is a powerful subspace signal analysis method for separation of single channel signals into their constituent uncorrelated components. The consistency in the results for both early and delayed brain responses verifies the usability of the approach.</p>","PeriodicalId":50305,"journal":{"name":"International Journal of Neural Systems","volume":null,"pages":null},"PeriodicalIF":6.6000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Neural Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1142/S0129065723500089","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/12/10 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1

Abstract

To enable an accurate recognition of neuronal excitability in an epileptic brain for modeling or localization of epileptic zone, here the brain response to single-pulse electrical stimulation (SPES) has been decomposed into its constituent components using adaptive singular spectrum analysis (SSA). Given the response at neuronal level, these components are expected to be the inhibitory and excitatory components. The prime objective is to thoroughly investigate the nature of delayed responses (elicited between 100[Formula: see text]ms-1 s after SPES) for localization of the epileptic zone. SSA is a powerful subspace signal analysis method for separation of single channel signals into their constituent uncorrelated components. The consistency in the results for both early and delayed brain responses verifies the usability of the approach.

癫痫脑对单脉冲电刺激的抑制和兴奋反应的分离。
为了能够准确识别癫痫脑中的神经元兴奋性,以便对癫痫区进行建模或定位,本文使用自适应奇异谱分析(SSA)将大脑对单脉冲电刺激(SPES)的反应分解为其组成成分。考虑到神经元水平的反应,这些成分被认为是抑制性和兴奋性成分。主要目的是彻底研究癫痫区定位的延迟反应(在SPES后100[公式:见正文]ms-1 s之间引发)的性质。SSA是一种强大的子空间信号分析方法,用于将单通道信号分离为其组成的不相关分量。早期和延迟大脑反应结果的一致性验证了该方法的可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
International Journal of Neural Systems
International Journal of Neural Systems 工程技术-计算机:人工智能
CiteScore
11.30
自引率
28.80%
发文量
116
审稿时长
24 months
期刊介绍: The International Journal of Neural Systems is a monthly, rigorously peer-reviewed transdisciplinary journal focusing on information processing in both natural and artificial neural systems. Special interests include machine learning, computational neuroscience and neurology. The journal prioritizes innovative, high-impact articles spanning multiple fields, including neurosciences and computer science and engineering. It adopts an open-minded approach to this multidisciplinary field, serving as a platform for novel ideas and enhanced understanding of collective and cooperative phenomena in computationally capable systems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信