Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research.

Frontiers in network physiology Pub Date : 2023-11-30 eCollection Date: 2023-01-01 DOI:10.3389/fnetp.2023.1297345
Yulia Novitskaya, Matthias Dümpelmann, Andreas Schulze-Bonhage
{"title":"Physiological and pathological neuronal connectivity in the living human brain based on intracranial EEG signals: the current state of research.","authors":"Yulia Novitskaya, Matthias Dümpelmann, Andreas Schulze-Bonhage","doi":"10.3389/fnetp.2023.1297345","DOIUrl":null,"url":null,"abstract":"<p><p>Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.</p>","PeriodicalId":73092,"journal":{"name":"Frontiers in network physiology","volume":"3 ","pages":"1297345"},"PeriodicalIF":0.0000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10723837/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in network physiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fnetp.2023.1297345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Over the past decades, studies of human brain networks have received growing attention as the assessment and modelling of connectivity in the brain is a topic of high impact with potential application in the understanding of human brain organization under both physiological as well as various pathological conditions. Under specific diagnostic settings, human neuronal signal can be obtained from intracranial EEG (iEEG) recording in epilepsy patients that allows gaining insight into the functional organisation of living human brain. There are two approaches to assess brain connectivity in the iEEG-based signal: evaluation of spontaneous neuronal oscillations during ongoing physiological and pathological brain activity, and analysis of the electrophysiological cortico-cortical neuronal responses, evoked by single pulse electrical stimulation (SPES). Both methods have their own advantages and limitations. The paper outlines available methodological approaches and provides an overview of current findings in studies of physiological and pathological human brain networks, based on intracranial EEG recordings.

基于颅内脑电图信号的活体人脑生理性和病理性神经元连接:研究现状。
在过去的几十年里,人脑网络研究受到越来越多的关注,因为对大脑连接性的评估和建模是一个极具影响力的课题,在了解人脑在生理和各种病理条件下的组织结构方面具有潜在的应用价值。在特定的诊断环境下,可以从癫痫患者的颅内脑电图(iEEG)记录中获得人类神经元信号,从而深入了解活体人脑的功能组织。评估基于 iEEG 信号的大脑连接性有两种方法:评估正在进行的生理和病理大脑活动期间的自发神经元振荡,以及分析单脉冲电刺激(SPES)诱发的电生理皮质-皮质神经元反应。这两种方法各有其优势和局限性。本文概述了现有的方法论途径,并概述了目前基于颅内脑电图记录对生理和病理人脑网络进行研究的结果。
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
CiteScore
2.70
自引率
0.00%
发文量
0
×
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