近10年脑电图应用于孤独症谱系障碍领域研究的文献计量分析

doi:10.3969/j.issn.1006-9771.2024.06.009

《中国康复理论与实践》 ›› 2024, Vol. 30 ›› Issue (6): 693-700.doi: 10.3969/j.issn.1006-9771.2024.06.009

近10年脑电图应用于孤独症谱系障碍领域研究的文献计量分析

张哲¹^,²^,³, 董献文¹^,²(), 徐成铭¹^,², 胡文静¹^,²^,³, 贺婷丽¹^,²^,³, 崔鑫鑫¹^,²^,³, 徐红艳¹^,²^,³, 周章盈¹^,²^,³, 韩雅男¹

1.郑州大学第五附属医院，河南郑州市 450052
2.河南省康复医学重点实验室，河南郑州市 450052
3.郑州大学医学科学院，河南郑州市 450052

收稿日期:2024-01-11 出版日期:2024-06-25 发布日期:2024-07-03
通讯作者: 董献文(1980-)，男，汉族，博士，讲师，硕士研究生导师，主要研究方向：脑功能康复，E-mail： xianwen.2004@163.com。
作者简介:张哲(2001-)，男，汉族，安徽淮南市人，硕士研究生，主要研究方向：孤独症的康复治疗。
基金资助:
河南省卫健委省部共建重点项目(SBGJ202002123);河南省高等学校重点科研项目(21A320058)

Electroencephalography applied in autism spectrum disorder research in decade: a bibliometrics analysis

ZHANG Zhe¹^,²^,³, DONG Xianwen¹^,²(), XU Chengming¹^,², HU Wenjing¹^,²^,³, HE Tingli¹^,²^,³, CUI Xinxin¹^,²^,³, XU Hongyan¹^,²^,³, ZHOU Zhangying¹^,²^,³, HAN Ya'nan¹

1. The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
2. Key Laboratory of Rehabilitation Medicine, Zhengzhou, Henan 450052, China
3. School of Medical Sciences, Zhengzhou University, Zhengzhou, Henan 450052, China

Received:2024-01-11 Published:2024-06-25 Online:2024-07-03
Supported by:
Key Project of Henan Provincial Health Commission(SBGJ202002123);Key Research Project of Higher Education Institutions in Henan Province(21A320058)

摘要/Abstract

摘要：

目的分析脑电图应用于孤独症谱系障碍(ASD)领域的研究现状、研究热点和发展趋势。

方法检索2014年1月至2024年1月Web of Science核心合集相关文献，采用CiteSpace 6.2.R4进行可视化分析。

结果最终纳入文献1 509篇，发文量呈逐年上升趋势。发文量和节点中心性最高的国家为美国。该领域发文期刊主要集中于临床医学、免疫学、心理学等学科。关键词共现和聚类结果表明，研究主要聚焦于ASD核心症状与脑电图指标的相关性研究、ASD及其共患病的鉴别诊断、脑功能连接以及康复疗效的评估。近3年突现的关键词主要为人工智能和机器学习。

结论脑电图应用于ASD领域的研究热度呈上升趋势，未来可以重点关注利用脑电图联合多模态神经成像及机器学习技术探索ASD脑网络机制。

关键词: 孤独症谱系障碍, 脑电图, 文献计量学

Abstract:

Objective To analyze the current state, research hotspots, and development trends of electroencephalography (EEG) applied in the field of autism spectrum disorder (ASD).

Methods Relevant literature from the Web of Science core collection database from January, 2014 to January, 2024 were retrieved and analyzed using CiteSpace 6.2.R4.

Results A total of 1 509 articles were included, with an increasing trend in publication volume over the years. The United States ranked highest in both publication volume and node centrality. The primary journals in this field were concentrated in clinical medicine, immunology and psychology. Keyword co-occurrence and clustering indicated that research primarily focused on the correlation between core symptoms of ASD and EEG indicators, differential diagnosis of ASD and its comorbidities, brain functional connectivity, and assessment of rehabilitation efficacy. Keywords bursted in the past three years mainly included artificial intelligence and machine learning.

Conclusion The researches in EEG technology in the field of ASD is generally increasing. Future researches may focus on exploring the brain network mechanisms of ASD using EEG combined with multimodal neuroimaging, and machine learning technologies.

Key words: autism spectrum disorder, electroencephalography, bibliometrics

中图分类号:

R749.9

张哲, 董献文, 徐成铭, 胡文静, 贺婷丽, 崔鑫鑫, 徐红艳, 周章盈, 韩雅男. 近10年脑电图应用于孤独症谱系障碍领域研究的文献计量分析[J]. 《中国康复理论与实践》, 2024, 30(6): 693-700.

ZHANG Zhe, DONG Xianwen, XU Chengming, HU Wenjing, HE Tingli, CUI Xinxin, XU Hongyan, ZHOU Zhangying, HAN Ya'nan. Electroencephalography applied in autism spectrum disorder research in decade: a bibliometrics analysis[J]. Chinese Journal of Rehabilitation Theory and Practice, 2024, 30(6): 693-700.

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参考文献 52

[1]	HIROTA T, KING B H. Autism spectrum disorder: a review[J]. JAMA, 2023, 329(2): 157-168. doi: 10.1001/jama.2022.23661 pmid: 36625807
[2]	HUGHES H K, MORENO R J, ASHWOOD P. Innate immune dysfunction and neuroinflammation in autism spectrum disorder (ASD)[J]. Brain Behav Immun, 2023, 108: 245-254.
[3]	胡嘉铨, 祝丽玲, 姜志梅. 近20年有关孤独症谱系障碍早期筛查工具研究的可视化分析[J]. 中国康复理论与实践, 2023, 29(11): 1304-1315. doi: 10.3969/j.issn.1006-9771.2023.11.008
	HU J Q, ZHU L L, JIANG Z M. Early screening tools for autism spectrum disorder in the past two decades: a visualized analysis[J]. Chin J Rehabil Theory Pract, 2023, 29(11): 1304-1315
[4]	MAENNER M J, SHAW K A, BAKIAN A V, et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years: autism and developmental disabilities monitoring network, 11 sites, United States, 2018[J]. MMWR Surveill Summ, 2021, 70(11): 1-16.
[5]	MAENNER M J, WARREN Z, WILLIAMS A R, et al. Prevalence and characteristics of autism spectrum disorder among children aged 8 years: autism and developmental disabilities monitoring network, 11 sites, United States, 2020[J]. MMWR Surveill Summ, 2023, 72(2): 1-14.
[6]	YU Y, OZONOFF S, MILLER M. Assessment of autism spectrum disorder[J]. Assessment, 2024, 31(1): 24-41.
[7]	汤翔嵘, 王晓刚, 陈桃林, 等. 精神障碍的神经电生理循证医学证据[J]. 生物化学与生物物理进展, 2021, 48(10): 1157-1176.
	TANG X R, WANG X G, CHEN T L, et al. Evidence-based medicine biomarkers of neuroelectrophysiology for mental disorders[J]. Adv Biochem Biophys, 2021, 48(10): 1157-1176.
[8]	JESTE S S, FROHLICH J, LOO S K. Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders[J]. Curr Opin Neurol, 2015, 28(2): 110-116. doi: 10.1097/WCO.0000000000000181 pmid: 25710286
[9]	韩长明, 彭福来, 陈财, 等. 基于脑电信号的癫痫发作预测研究进展[J]. 生物医学工程学杂志, 2021, 38(6): 1193-1202.
	HAN C M, PENG F L, CHEN C, et al. Research progress of epileptic seizure predictions based on electroencephalogram signals[J]. J Biomed Eng, 2021, 38(6): 1193-1202.
[10]	SHARMA V, SAINI A G, MALHI P, et al. Epilepsy and EEG abnormalities in children with autism spectrum disorders[J]. Indian J Pediatr, 2022, 89(10): 975-982.
[11]	GENG X, FAN X, ZHONG Y, et al. Abnormalities of EEG functional connectivity and effective connectivity in children with autism spectrum disorder[J]. Brain Sci, 2023, 13(1): 130.
[12]	SHAN J, GU Y, ZHANG J, et al. A scoping review of physiological biomarkers in autism[J]. Front Neurosci, 2023, 17: 1269880.
[13]	吴君琳, 董明新, 黄国宁, 等. 基于VOSviewer和Citespace的基因多态性对药动学影响的文献可视化分析[J]. 医药导报, 2023, 42(10): 1583-1588. doi: 10.3870/j.issn.1004-0781.2023.10.031
	WU J L, DONG M X, HUANG G N, et al. Literature visualization analysis of the effect of gene polymorphisms on pharmacokinetics based on VOSviewer and Citespace[J]. Herald Med, 2023, 42(10): 1583-1588. doi: 10.3870/j.issn.1004-0781.2023.10.031
[14]	HYMAN S L, LEVY S E, MYERS S M. Identification, evaluation, and management of children with autism spectrum disorder[J]. Pediatrics, 2020, 145(1): e20193447.
[15]	HARSTAD E, HANSON E, BREWSTER S J, et al. Persistence of autism spectrum disorder from early childhood through school age[J]. JAMA Pediatr, 2023, 177(11): 1197-1205. doi: 10.1001/jamapediatrics.2023.4003 pmid: 37782510
[16]	ANUKIRTHIGA B, MISHRA D, PANDEY S, et al. Prevalence of epilepsy and inter-ictal epileptiform discharges in children with autism and attention-deficit hyperactivity disorder[J]. Indian J Pediatr, 2019, 86(10): 897-902. doi: 10.1007/s12098-019-02977-6 pmid: 31123917
[17]	KWON C S, WIRRELL E C, JETTE N. Autism spectrum disorder and epilepsy[J]. Neurol Clin, 2022, 40(4): 831-847.
[18]	STEFANSKI A, CALLE-LOPEZ Y, LEU C, et al. Clinical sequencing yield in epilepsy, autism spectrum disorder, and intellectual disability: a systematic review and meta-analysis[J]. Epilepsia, 2021, 62(1): 143-151. doi: 10.1111/epi.16755 pmid: 33200402
[19]	陈文雄. 儿童孤独症谱系障碍共患癫痫的诊治及管理[J]. 中国儿童保健杂志, 2019, 27(4): 351-354. doi: 10.11852/zgetbjzz2019-0373
	CHEN W X. Diagnosis, treatment and management of epilepsy in children with autism spectrum disorder[J]. Chin J Child Health Care, 2019, 27(4): 351-354.
[20]	KIM H L, DONNELLY J H, TOURNAY A E, et al. Absence of seizures despite high prevalence of epileptiform EEG abnormalities in children with autism monitored in a tertiary care center[J]. Epilepsia, 2006, 47(2): 394-398. pmid: 16499766
[21]	LOUSSOUARN A, DOZIÈRES-PUYRAVEL B, AUVIN S. Autistic spectrum disorder and epilepsy: diagnostic challenges[J]. Expert Rev Neurother, 2019, 19(6): 579-585. doi: 10.1080/14737175.2019.1617699 pmid: 31081698
[22]	梁安迪, 张芫, 张越, 等. 抑郁症大学生静息态脑电图脑功能连接特征研究[J]. 生理学报, 2022, 74(4): 574-584.
	LIANG A D, ZHANG Y, ZHANG Y, et al. Study on the EEG functional brain connectivity characteristics of college students with depression[J]. Acta Physiologica Sinica, 2022, 74(4): 574-584.
[23]	HAARTSEN R, JONES E, OREKHOVA E V, et al. Functional EEG connectivity in infants associates with later restricted and repetitive behaviours in autism; a replication study[J]. Transl Psychiatry, 2019, 9(1): 66.
[24]	ZHANG D, ALLEN J. A comparison of nomothetic and individualized alpha frequency approaches to measuring frontal EEG alpha asymmetry[J]. Psychophysiology, 2023, 60(1): e14149.
[25]	CARTER L V, TOMLINSON S B, CHANG S A, et al. Resting-state alpha power is selectively associated with autistic traits reflecting behavioral rigidity[J]. Sci Rep, 2018, 8(1): 11982.
[26]	NEUHAUS E, SANTHOSH M, KRESSE A, et al. Frontal EEG alpha asymmetry in youth with autism: sex differences and social-emotional correlates[J]. Autism Res, 2023, 16(12): 2364-2377. doi: 10.1002/aur.3032 pmid: 37776030
[27]	BERNIER R, DAWSON G, WEBB S, et al. EEG mu rhythm and imitation impairments in individuals with autism spectrum disorder[J]. Brain Cogn, 2007, 64(3): 228-237.
[28]	LAMARCA K, GEVIRTZ R, LINCOLN A J, et al. Brain-computer interface training of mu EEG rhythms in intellectually impaired children with autism: a feasibility case series[J]. Appl Psychophysiol Biofeedback, 2023, 48(2): 229-245.
[29]	LIU S, TANG F, DOU H, et al. The relationship between autistic traits and empathy in adolescents: an ERP study[J]. Neurosci Lett, 2023, 802: 137173.
[30]	DEPRIEST J, GLUSHKO A, STEINHAUER K, et al. Language and music phrase boundary processing in autism spectrum disorder: an ERP study[J]. Sci Rep, 2017, 7(1): 14465.
[31]	CANIGUERAL R, PALMER J, ASHWOOD K L, et al. Alpha oscillatory activity during attentional control in children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and ASD+ADHD[J]. J Child Psychol Psychiatry, 2022, 63(7): 745-761.
[32]	NOWPARAST R H, HILDEBRANDT A, SOMMER W. Sex-specific relationships between face memory and the N170 component in event-related potentials[J]. Soc Cogn Affect Neurosci, 2020, 15(5): 587-597. doi: 10.1093/scan/nsaa059 pmid: 32367139
[33]	DALLE NOGARE L, PROVERBIO A M. Emojis vs. facial expressions: an electrical neuroimaging study on perceptual recognition[J]. Soc Neurosci, 2023, 18(1): 46-64.
[34]	MASON L, MOESSNANG C, CHATHAM C, et al. Stratifying the autistic phenotype using electrophysiological indices of social perception[J]. Sci Transl Med, 2022, 14(658): eabf8987.
[35]	KALA S, ROLISON M J, TREVISAN D A, et al. Brief report: preliminary evidence of the N170 as a biomarker of response to treatment in autism spectrum disorder[J]. Front Psychiatry, 2021, 12: 709382.
[36]	YEN C, LIN C L, CHIANG M C. Exploring the frontiers of neuroimaging: a review of recent advances in understanding brain functioning and disorders[J]. Life (Basel), 2023, 13(7): 1472.
[37]	MASH L E, KEEHN B, LINKE A C, et al. Atypical relationships between spontaneous EEG and fMRI activity in autism[J]. Brain Connect, 2020, 10(1): 18-28. doi: 10.1089/brain.2019.0693 pmid: 31884804
[38]	O'REILLY C, LEWIS J D, ELSABBAGH M. Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies[J]. PLoS One, 2017, 12(5): e175870.
[39]	LIU M, LIU B, YE Z, et al. Bibliometric analysis of electroencephalogram research in mild cognitive impairment from 2005 to 2022[J]. Front Neurosci, 2023, 17: 1128851.
[40]	STANCIN I, CIFREK M, JOVIC A. A review of EEG signal features and their application in driver drowsiness detection systems[J]. Sensors (Basel), 2021, 21(11): 3786.
[41]	CRAIK A, HE Y, CONTRERAS-VIDAL J L. Deep learning for electroencephalogram (EEG) classification tasks: a review[J]. J Neural Eng, 2019, 16(3): 31001.
[42]	DAS S, ZOMORRODI R, MIRJALILI M, et al. Machine learning approaches for electroencephalography and magnetoencephalography analyses in autism spectrum disorder: a systematic review[J]. Prog Neuropsychopharmacol Biol Psychiatry, 2023, 123: 110705.
[43]	ROGALA J, ZYGIEREWICZ J, MALINOWSKA U, et al. Enhancing autism spectrum disorder classification in children through the integration of traditional statistics and classical machine learning techniques in EEG analysis[J]. Sci Rep, 2023, 13(1): 21748.
[44]	ARI B, SOBAHI N, ALCIN O F, et al. Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals[J]. Comput Biol Med, 2022, 143: 105311.
[45]	王亚鹏. 神经反馈训练及其在孤独症儿童中的应用[J]. 教育生物学杂志, 2022, 10(2): 148-154.
	WANG Y P. Neurofeedback training and its application to children with autism spectrum disorder[J]. J Bio Educ, 2022, 10(2): 148-154.
[46]	KONICAR L, RADEV S, PRILLINGER K, et al. Volitional modification of brain activity in adolescents with autism spectrum disorder: a Bayesian analysis of slow cortical potential neurofeedback[J]. Neuroimage Clin, 2021, 29: 102557.
[47]	SALEEM S, HABIB S H. Neurofeedback recuperates cognitive functions in children with autism spectrum disorders (ASD)[J]. [ahead of print] J Autism Dev Disord, 2023. DOI: 10.1007/s10803-023-06037-z.
[48]	WANG Y, SOKHADZE E M, EL-BAZ A S, et al. Relative power of specific EEG bands and their ratios during neurofeedback training in children with autism spectrum disorder[J]. Front Hum Neurosci, 2015, 9: 723. doi: 10.3389/fnhum.2015.00723 pmid: 26834615
[49]	KOUIJZER M E J, DE MOOR J M H, GERRITS B J L, et al. Neurofeedback improves executive functioning in children with autism spectrum disorders[J]. Res Autism Spectrum Disord, 2009, 3(1): 145-162.
[50]	KOUIJZER M E J, DE MOOR J M H, GERRITS B J L, et al. Long-term effects of neurofeedback treatment in autism[J]. Res Autism Spectrum Disord, 2009, 3(2): 496-501.
[51]	MCPARTLAND J C, LERNER M D, BHAT A, et al. Looking back at the next 40 years of ASD neuroscience research[J]. J Autism Develop Disord, 2021, 51(12): 4333-4353.
[52]	GURAU O, BOSL W J, NEWTON C R. How useful is electroencephalography in the diagnosis of autism spectrum disorders and the delineation of subtypes: a systematic review[J]. Front Psychiatry, 2017, 8: 121. doi: 10.3389/fpsyt.2017.00121 pmid: 28747892

序号	年份	轮廓	主要关键词
0	2017	0.602	ERP; mismatch negativity; epilepsy; auditory processing; predictive coding
1	2016	0.676	epilepsy; seizures; infantile spasms; intellectual disability; regression
2	2017	0.708	autism spectrum disorder; functional connectivity; patterns; risk; brain connectivity
3	2016	0.716	μ rhythm; mirror neuron system; mirror neurons; action observation; autism spectrum disorders
4	2016	0.689	EEG coherence; ADHD; executive function; power spectrum; transcranial magnetic stimulation
5	2020	0.652	machine learning; deep learning; artificial intelligence; entropy; electroencephalogram
6	2018	0.643	alpha; magnetic resonance imaging; resting state; virtual reality
7	2019	0.802	fragile X syndrome; sensory hypersensitivity; auditory cortex; multielectrode array; working memory

近10年脑电图应用于孤独症谱系障碍领域研究的文献计量分析

Electroencephalography applied in autism spectrum disorder research in decade: a bibliometrics analysis

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