• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism.自闭症电生理数据收集、分析及报告的指南与最佳实践
J Autism Dev Disord. 2015 Feb;45(2):425-43. doi: 10.1007/s10803-013-1916-6.
2
Magnetoencephalographic patterns of epileptiform activity in children with regressive autism spectrum disorders.退行性自闭症谱系障碍儿童癫痫样活动的脑磁图模式
Pediatrics. 1999 Sep;104(3 Pt 1):405-18. doi: 10.1542/peds.104.3.405.
3
NREM sleep EEG activity and procedural memory: A comparison between young neurotypical and autistic adults without sleep complaints.非快速眼动睡眠 EEG 活动与程序性记忆:无睡眠问题的年轻神经典型和自闭症成年人之间的比较。
Autism Res. 2018 Apr;11(4):613-623. doi: 10.1002/aur.1933. Epub 2018 Jan 30.
4
Self-regulation of brain oscillations as a treatment for aberrant brain connections in children with autism.自我调节脑电波以治疗自闭症儿童异常的大脑连接。
Med Hypotheses. 2012 Dec;79(6):790-8. doi: 10.1016/j.mehy.2012.08.031. Epub 2012 Sep 20.
5
EEG Biomarkers for Autism: Rational, Support, and the Qualification Process.脑电图生物标志物在自闭症中的应用:原理、依据和资格认证流程。
Adv Neurobiol. 2024;40:545-576. doi: 10.1007/978-3-031-69491-2_19.
6
Diagnosis of autism through EEG processed by advanced computational algorithms: A pilot study.通过先进计算算法处理脑电图诊断自闭症:一项初步研究。
Comput Methods Programs Biomed. 2017 Apr;142:73-79. doi: 10.1016/j.cmpb.2017.02.002. Epub 2017 Feb 20.
7
EEG and neurophysiological studies of early infantile autism.早期婴儿自闭症的脑电图及神经生理学研究。
Biol Psychiatry. 1975 Aug;10(4):385-97.
8
Modeling intra-individual inter-trial EEG response variability in autism.自闭症个体内试验间 EEG 反应变异性建模。
Stat Med. 2024 Jul 30;43(17):3239-3263. doi: 10.1002/sim.10131. Epub 2024 Jun 1.
9
Autism, spectrum or clusters? An EEG coherence study.自闭症,谱系还是集群?一项脑电图相干性研究。
BMC Neurol. 2019 Feb 14;19(1):27. doi: 10.1186/s12883-019-1254-1.
10
Investigating neural dynamics in autism spectrum conditions outside of the laboratory using mobile electroencephalography.使用移动脑电图技术在实验室之外研究自闭症谱系障碍中的神经动力学。
Psychophysiology. 2022 Apr;59(4):e13995. doi: 10.1111/psyp.13995. Epub 2022 Jan 4.

引用本文的文献

1
Recommendations for Increasing Sample Diversity in Autism Research: Lessons from Multisensory Studies.提高自闭症研究样本多样性的建议:多感官研究的经验教训。
J Autism Dev Disord. 2025 Aug 23. doi: 10.1007/s10803-025-07022-4.
2
Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli.利用计算机视觉分析对伴有视觉刺激的脑电图记录中的注意力不集中时间段进行标记。
Sci Rep. 2025 Aug 22;15(1):30963. doi: 10.1038/s41598-025-10511-2.
3
The development of semantic integration in bilingual toddlers measured by N400.通过N400测量双语幼儿语义整合的发展。
Dev Cogn Neurosci. 2025 Jul 23;75:101599. doi: 10.1016/j.dcn.2025.101599.
4
Automatic and affective processing of faces as mechanisms of passing as non-autistic in adolescence.作为青少年伪装成非自闭症患者机制的面部自动和情感加工
Sci Rep. 2025 Jul 2;15(1):22850. doi: 10.1038/s41598-025-04801-y.
5
The GREENBEAN checklist for reporting studies evaluating the effectiveness of EEG-based biomarkers.用于报告评估基于脑电图生物标志物有效性研究的GREENBEAN清单。
Clin Neurophysiol. 2025 Jun 6;176:2110777. doi: 10.1016/j.clinph.2025.2110777.
6
Remote EEG acquisition in Angelman syndrome using PANDABox-EEG.使用PANDABox-EEG对天使综合征进行远程脑电图采集。
J Neurodev Disord. 2025 May 24;17(1):29. doi: 10.1186/s11689-025-09611-x.
7
Remote EEG Acquisition in Angelman Syndrome using PANDABox-EEG.使用PANDABox-EEG对天使综合征患者进行远程脑电图采集。
Res Sq. 2025 Apr 3:rs.3.rs-5112015. doi: 10.21203/rs.3.rs-5112015/v1.
8
Individuals with high autistic traits exhibit altered interhemispheric brain functional connectivity patterns.具有高自闭症特质的个体表现出半球间大脑功能连接模式的改变。
Cogn Neurodyn. 2025 Dec;19(1):9. doi: 10.1007/s11571-024-10213-x. Epub 2025 Jan 9.
9
It's all in the timing: delayed feedback in autism may weaken predictive mechanisms during contour integration.一切都在于时机:自闭症中的延迟反馈可能会削弱轮廓整合过程中的预测机制。
J Neurophysiol. 2024 Sep 1;132(3):628-642. doi: 10.1152/jn.00058.2024. Epub 2024 Jul 3.
10
Preliminary observations on the associations between sensory processing abnormalities and event-related potentials in adults with autism spectrum disorder.关于自闭症谱系障碍成人患者感觉加工异常与事件相关电位之间关联的初步观察
PCN Rep. 2024 Feb 14;3(1):e173. doi: 10.1002/pcn5.173. eCollection 2024 Mar.

本文引用的文献

1
How anatomical asymmetry of human auditory cortex can lead to a rightward bias in auditory evoked fields.人类听觉皮层的解剖学不对称如何导致听觉诱发电场的右偏。
Neuroimage. 2013 Jul 1;74:22-9. doi: 10.1016/j.neuroimage.2013.02.002. Epub 2013 Feb 13.
2
Multimodal emotion processing in autism spectrum disorders: an event-related potential study.自闭症谱系障碍的多模态情绪处理:一项事件相关电位研究。
Dev Cogn Neurosci. 2013 Jan;3:11-21. doi: 10.1016/j.dcn.2012.08.005. Epub 2012 Sep 1.
3
Mechanisms of change in psychosocial interventions for autism spectrum disorders.自闭症谱系障碍心理社会干预中的改变机制。
Dialogues Clin Neurosci. 2012 Sep;14(3):307-18. doi: 10.31887/DCNS.2012.14.3/mlerner.
4
Can EEG characteristics predict development of epilepsy in autistic children?脑电图特征能否预测自闭症儿童癫痫的发生?
Eur J Paediatr Neurol. 2013 May;17(3):232-7. doi: 10.1016/j.ejpn.2012.10.002. Epub 2012 Oct 31.
5
Early behavioral intervention is associated with normalized brain activity in young children with autism.早期行为干预与自闭症幼儿大脑活动的正常化有关。
J Am Acad Child Adolesc Psychiatry. 2012 Nov;51(11):1150-9. doi: 10.1016/j.jaac.2012.08.018.
6
Good practice for conducting and reporting MEG research.脑磁图(MEG)研究的良好实践。
Neuroimage. 2013 Jan 15;65:349-63. doi: 10.1016/j.neuroimage.2012.10.001. Epub 2012 Oct 6.
7
Social anxiety predicts aggression in children with ASD: clinical comparisons with socially anxious and oppositional youth.社交焦虑症预测 ASD 儿童的攻击行为:与社交焦虑和对立青少年的临床比较。
J Autism Dev Disord. 2013 May;43(5):1205-13. doi: 10.1007/s10803-012-1666-x.
8
Unreliable evoked responses in autism.自闭症患者的诱发电位反应不可靠。
Neuron. 2012 Sep 20;75(6):981-91. doi: 10.1016/j.neuron.2012.07.026.
9
Sleep in children with autism spectrum disorder.自闭症谱系障碍儿童的睡眠问题。
Pediatr Neurol. 2012 Oct;47(4):242-51. doi: 10.1016/j.pediatrneurol.2012.05.007.
10
Preserved reward outcome processing in ASD as revealed by event-related potentials.ASD 中与奖赏预期相关的事件相关电位研究
J Neurodev Disord. 2012 May 31;4(1):16. doi: 10.1186/1866-1955-4-16.

自闭症电生理数据收集、分析及报告的指南与最佳实践

Guidelines and best practices for electrophysiological data collection, analysis and reporting in autism.

作者信息

Webb Sara Jane, Bernier Raphael, Henderson Heather A, Johnson Mark H, Jones Emily J H, Lerner Matthew D, McPartland James C, Nelson Charles A, Rojas Donald C, Townsend Jeanne, Westerfield Marissa

机构信息

Department of Psychiatry and Behavioral Sciences, University of Washington, M/S CW8-6, SCRI Po Box 5371, Seattle, WA, 98145, USA,

出版信息

J Autism Dev Disord. 2015 Feb;45(2):425-43. doi: 10.1007/s10803-013-1916-6.

DOI:10.1007/s10803-013-1916-6
PMID:23975145
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4141903/
Abstract

The EEG reflects the activation of large populations of neurons that act in synchrony and propagate to the scalp surface. This activity reflects both the brain's background electrical activity and when the brain is being challenged by a task. Despite strong theoretical and methodological arguments for the use of EEG in understanding the neural correlates of autism, the practice of collecting, processing and evaluating EEG data is complex. Scientists should take into consideration both the nature of development in autism given the life-long, pervasive course of the disorder and the disability of altered or atypical social, communicative, and motor behaviors, all of which require accommodations to traditional EEG environments and paradigms. This paper presents guidelines for the recording, analyzing, and interpreting of EEG data with participants with autism. The goal is to articulate a set of scientific standards as well as methodological considerations that will increase the general field's understanding of EEG methods, provide support for collaborative projects, and contribute to the evaluation of results and conclusions.

摘要

脑电图(EEG)反映了大量同步活动并传播至头皮表面的神经元的激活情况。这种活动既反映了大脑的背景电活动,也反映了大脑在面对任务挑战时的状态。尽管有强有力的理论和方法学依据支持使用脑电图来理解自闭症的神经关联,但收集、处理和评估脑电图数据的实践过程很复杂。鉴于自闭症是一种终身性、广泛性的疾病,且存在社交、沟通和运动行为改变或异常的残疾情况,科学家们在考虑自闭症的发展本质时,所有这些都需要对传统脑电图环境和范式进行调整。本文提出了针对自闭症患者脑电图数据记录、分析和解读的指导方针。目标是阐明一套科学标准以及方法学考量,这将增进该领域对脑电图方法的总体理解,为合作项目提供支持,并有助于对结果和结论进行评估。