{"title":"静息状态脑电图相幅耦合分析揭示ADHD亚型儿童脑功能差异。","authors":"Wanting Tang , Jiuchuan Jiang , Haixian Wang","doi":"10.1016/j.ijpsycho.2025.113222","DOIUrl":null,"url":null,"abstract":"<div><div>Phase-amplitude coupling (PAC) plays a critical role in attention, sensory processing, and working memory—domains often impaired in children with attention deficit/hyperactivity disorder (ADHD). Therefore, PAC is theoretically well-suited for ADHD research. However, the differences in PAC characteristics among children with ADHD subtypes have not yet been thoroughly investigated. This study recorded resting-state electroencephalographic (rsEEG) from 19 healthy controls (HCs), 33 children with predominantly inattentive type (ADHD-I), and 39 with combined type (ADHD-C). We examined intra- and inter-channel PAC differences across different spatial scales and further analyzed PAC-based brain network properties. The results showed that both ADHD subtypes had stronger α-γ PAC than HCs, with ADHD-C exceeding ADHD-I. ADHD-I showed mainly intrahemispheric changes, while ADHD-C involved the left hemisphere and occipital regions. In the α-β band, PAC was significantly higher in ADHD-C than in ADHD-I, mostly in the left brain. ADHD-I also showed increased inter-channel δ-β PAC compared to HCs, with widespread distribution. These findings suggest the presence of compensatory hyperactivation mechanisms in ADHD, particularly in the ADHD-C subtype. Further brain network analysis supported the “delayed maturation theory” of ADHD and indicated that ADHD-C may represent a shift from a typical small-world network architecture to a more regular network organization. Finally, the (Support Vector Machine) SVM classification results further validated the discriminative power of these features in differentiating HCs from ADHD subtypes. Overall, these findings indicate significant differences in PAC strength and brain network topology among ADHD subtypes, suggesting their potential as biomarkers for distinguishing HCs from ADHD subtypes.</div></div>","PeriodicalId":54945,"journal":{"name":"International Journal of Psychophysiology","volume":"215 ","pages":"Article 113222"},"PeriodicalIF":2.6000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Brain functional differences among ADHD subtypes in children revealed by phase-amplitude coupling analysis of resting-state EEG\",\"authors\":\"Wanting Tang , Jiuchuan Jiang , Haixian Wang\",\"doi\":\"10.1016/j.ijpsycho.2025.113222\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Phase-amplitude coupling (PAC) plays a critical role in attention, sensory processing, and working memory—domains often impaired in children with attention deficit/hyperactivity disorder (ADHD). Therefore, PAC is theoretically well-suited for ADHD research. However, the differences in PAC characteristics among children with ADHD subtypes have not yet been thoroughly investigated. This study recorded resting-state electroencephalographic (rsEEG) from 19 healthy controls (HCs), 33 children with predominantly inattentive type (ADHD-I), and 39 with combined type (ADHD-C). We examined intra- and inter-channel PAC differences across different spatial scales and further analyzed PAC-based brain network properties. The results showed that both ADHD subtypes had stronger α-γ PAC than HCs, with ADHD-C exceeding ADHD-I. ADHD-I showed mainly intrahemispheric changes, while ADHD-C involved the left hemisphere and occipital regions. In the α-β band, PAC was significantly higher in ADHD-C than in ADHD-I, mostly in the left brain. ADHD-I also showed increased inter-channel δ-β PAC compared to HCs, with widespread distribution. These findings suggest the presence of compensatory hyperactivation mechanisms in ADHD, particularly in the ADHD-C subtype. Further brain network analysis supported the “delayed maturation theory” of ADHD and indicated that ADHD-C may represent a shift from a typical small-world network architecture to a more regular network organization. Finally, the (Support Vector Machine) SVM classification results further validated the discriminative power of these features in differentiating HCs from ADHD subtypes. Overall, these findings indicate significant differences in PAC strength and brain network topology among ADHD subtypes, suggesting their potential as biomarkers for distinguishing HCs from ADHD subtypes.</div></div>\",\"PeriodicalId\":54945,\"journal\":{\"name\":\"International Journal of Psychophysiology\",\"volume\":\"215 \",\"pages\":\"Article 113222\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Psychophysiology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167876025007184\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Psychophysiology","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167876025007184","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Brain functional differences among ADHD subtypes in children revealed by phase-amplitude coupling analysis of resting-state EEG
Phase-amplitude coupling (PAC) plays a critical role in attention, sensory processing, and working memory—domains often impaired in children with attention deficit/hyperactivity disorder (ADHD). Therefore, PAC is theoretically well-suited for ADHD research. However, the differences in PAC characteristics among children with ADHD subtypes have not yet been thoroughly investigated. This study recorded resting-state electroencephalographic (rsEEG) from 19 healthy controls (HCs), 33 children with predominantly inattentive type (ADHD-I), and 39 with combined type (ADHD-C). We examined intra- and inter-channel PAC differences across different spatial scales and further analyzed PAC-based brain network properties. The results showed that both ADHD subtypes had stronger α-γ PAC than HCs, with ADHD-C exceeding ADHD-I. ADHD-I showed mainly intrahemispheric changes, while ADHD-C involved the left hemisphere and occipital regions. In the α-β band, PAC was significantly higher in ADHD-C than in ADHD-I, mostly in the left brain. ADHD-I also showed increased inter-channel δ-β PAC compared to HCs, with widespread distribution. These findings suggest the presence of compensatory hyperactivation mechanisms in ADHD, particularly in the ADHD-C subtype. Further brain network analysis supported the “delayed maturation theory” of ADHD and indicated that ADHD-C may represent a shift from a typical small-world network architecture to a more regular network organization. Finally, the (Support Vector Machine) SVM classification results further validated the discriminative power of these features in differentiating HCs from ADHD subtypes. Overall, these findings indicate significant differences in PAC strength and brain network topology among ADHD subtypes, suggesting their potential as biomarkers for distinguishing HCs from ADHD subtypes.
期刊介绍:
The International Journal of Psychophysiology is the official journal of the International Organization of Psychophysiology, and provides a respected forum for the publication of high quality original contributions on all aspects of psychophysiology. The journal is interdisciplinary and aims to integrate the neurosciences and behavioral sciences. Empirical, theoretical, and review articles are encouraged in the following areas:
• Cerebral psychophysiology: including functional brain mapping and neuroimaging with Event-Related Potentials (ERPs), Positron Emission Tomography (PET), Functional Magnetic Resonance Imaging (fMRI) and Electroencephalographic studies.
• Autonomic functions: including bilateral electrodermal activity, pupillometry and blood volume changes.
• Cardiovascular Psychophysiology:including studies of blood pressure, cardiac functioning and respiration.
• Somatic psychophysiology: including muscle activity, eye movements and eye blinks.