CASIA OpenIR  > 中国科学院分子影像重点实验室
Aberrant brain dynamics and spectral power in children with ADHD and its subtypes
Luo, Na1,2,3; Luo, Xiangsheng4,5,6,7; Zheng, Suli4,5,6,7; Yao, Dongren8,9; Zhao, Min1,2,3; Cui, Yue1,2,3; Zhu, Yu4,5,6,7; Calhoun, Vince D.10,11; Sun, Li4,5,6,7; Sui, Jing10,11,12
Source PublicationEUROPEAN CHILD & ADOLESCENT PSYCHIATRY
ISSN1018-8827
2022-08-22
Pages12
Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three subtypes, predominant inattention (ADHD-I), predominant hyperactivity-impulsivity (ADHD-HI), and a combined subtype (ADHD-C). Yet, common and unique abnormalities of electroencephalogram (EEG) across different subtypes remain poorly understood. Here, we leveraged microstate characteristics and power features to investigate temporal and frequency abnormalities in ADHD and its subtypes using high-density EEG on 161 participants (54 ADHD-Is and 53 ADHD-Cs and 54 healthy controls). Four EEG microstates were identified. The coverage of salience network (state C) were decreased in ADHD compared to HC (p = 1.46e-3), while the duration and contribution of frontal-parietal network (state D) were increased (p = 1.57e-3; p = 1.26e-4). Frequency power analysis also indicated that higher delta power in the fronto-central area (p = 6.75e-4) and higher power of theta/beta ratio in the bilateral fronto-temporal area (p = 3.05e-3) were observed in ADHD. By contrast, remarkable subtype differences were found primarily on the visual network (state B), of which ADHD-C have higher occurrence and coverage than ADHD-I (p = 9.35e-5; p = 1.51e-8), suggesting that children with ADHD-C might exhibit impulsivity of opening their eyes in an eye-closed experiment, leading to hyper-activated visual network. Moreover, the top discriminative features selected from support vector machine model with recursive feature elimination (SVM-RFE) well replicated the above results, which achieved an accuracy of 72.7% and 73.8% separately in classifying ADHD and two subtypes. To conclude, this study highlights EEG microstate dynamics and frequency features may serve as sensitive measurements to detect the subtle differences in ADHD and its subtypes, providing a new window for better diagnosis of ADHD.

KeywordADHD Subtypes EEG Microstate dynamics Spectral power
DOI10.1007/s00787-022-02068-6
WOS KeywordATTENTION-DEFICIT/HYPERACTIVITY DISORDER ; EEG THETA/BETA RATIO ; DEFICIT HYPERACTIVITY DISORDER ; GAMMA-OSCILLATIONS ; FMRI ; NETWORK ; SYSTEMS
Indexed BySCI
Language英语
Funding ProjectNational Natural Sciences Foundation of China[81971284] ; National Natural Sciences Foundation of China[81771479] ; National Natural Sciences Foundation of China[82022035] ; National Natural Sciences Foundation of China[61773380] ; National Natural Sciences Foundation of China[82001450] ; China Postdoctoral Science Foundation[BX20200364] ; Key scientific research projects of capital health development[2020-1-4111] ; National Institute of Health[R01MH117107] ; National Institute of Health[R01EB005846] ; National Science Foundation[2112455] ; Beijing Municipal Science and Technology Commission[Z181100001518005]
Funding OrganizationNational Natural Sciences Foundation of China ; China Postdoctoral Science Foundation ; Key scientific research projects of capital health development ; National Institute of Health ; National Science Foundation ; Beijing Municipal Science and Technology Commission
WOS Research AreaPsychology ; Pediatrics ; Psychiatry
WOS SubjectPsychology, Developmental ; Pediatrics ; Psychiatry
WOS IDWOS:000842912700001
PublisherSPRINGER
Sub direction classification医学影像处理与分析
planning direction of the national heavy laboratory其他
Paper associated data
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Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/49877
Collection中国科学院分子影像重点实验室
Corresponding AuthorSun, Li; Sui, Jing
Affiliation1.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Peking Univ Sixth Hosp, Beijing 100191, Peoples R China
5.Peking Univ, Inst Mental Hlth, Beijing 100191, Peoples R China
6.Peking Univ, NHC Key Lab Mental Hlth, Beijing 100191, Peoples R China
7.Peking Univ Sixth Hosp, Natl Clin Res Ctr Mental Disorders, Beijing 100191, Peoples R China
8.Massachusetts Eye & Ear Infirm, Boston, MA 02114 USA
9.Harvard Med Sch, Boston, MA 02114 USA
10.Georgia State Univ, Georgia Inst Technol, Triinst Ctr Translat Res Neuroimaging & Data Sci, Atlanta, GA 30303 USA
11.Emory Univ, Atlanta, GA 30303 USA
12.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Luo, Na,Luo, Xiangsheng,Zheng, Suli,et al. Aberrant brain dynamics and spectral power in children with ADHD and its subtypes[J]. EUROPEAN CHILD & ADOLESCENT PSYCHIATRY,2022:12.
APA Luo, Na.,Luo, Xiangsheng.,Zheng, Suli.,Yao, Dongren.,Zhao, Min.,...&Sui, Jing.(2022).Aberrant brain dynamics and spectral power in children with ADHD and its subtypes.EUROPEAN CHILD & ADOLESCENT PSYCHIATRY,12.
MLA Luo, Na,et al."Aberrant brain dynamics and spectral power in children with ADHD and its subtypes".EUROPEAN CHILD & ADOLESCENT PSYCHIATRY (2022):12.
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