Brain functional differences among ADHD subtypes in children revealed by phase-amplitude coupling analysis of
Wanting Tang1, Jiuchuan Jiang2, Haixian Wang1
1Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, PR China.
Insights
Children with attention deficit/hyperactivity disorder (ADHD) subtypes exhibit distinct phase-amplitude coupling (PAC) patterns compared to healthy controls. These differences in brain network activity may serve as biomarkers for ADHD subtypes.
Area of Science:
- Neuroscience
- Developmental Psychology
- Biomarkers
Background:
- Phase-amplitude coupling (PAC) is crucial for cognitive functions like attention and memory, often impaired in attention deficit/hyperactivity disorder (ADHD).
- Previous research has not fully explored PAC differences across ADHD subtypes (inattentive and combined types).
Purpose of the Study:
- To investigate and compare intra- and inter-channel PAC characteristics across different spatial scales in children with ADHD subtypes and healthy controls.
- To analyze PAC-based brain network properties and their potential as biomarkers for differentiating ADHD subtypes.
Main Methods:
- Resting-state electroencephalography (rsEEG) data were recorded from 19 healthy controls (HCs), 33 children with ADHD-predominantly inattentive type (ADHD-I), and 39 with ADHD-combined type (ADHD-C).
- Analysis included intra- and inter-channel PAC across various spatial scales and PAC-based brain network topology.
- Support Vector Machine (SVM) classification was used to assess the discriminative power of identified features.
Main Results:
- Both ADHD subtypes showed increased alpha-gamma (α-γ) PAC compared to HCs, with ADHD-C exhibiting higher levels than ADHD-I.
- ADHD-I primarily displayed intrahemispheric PAC changes, while ADHD-C involved the left hemisphere and occipital regions.
- ADHD-C showed higher alpha-beta (α-β) PAC than ADHD-I, predominantly in the left hemisphere. ADHD-I demonstrated increased delta-beta (δ-β) inter-channel PAC compared to HCs.
Conclusions:
- Findings suggest compensatory hyperactivation mechanisms in ADHD, particularly in the combined subtype.
- Brain network analysis supports the 'delayed maturation theory' of ADHD, indicating a shift towards a more regular network organization in ADHD-C.
- PAC features demonstrate significant discriminative power for distinguishing HCs from ADHD subtypes, highlighting their potential as neurobiomarkers.
Abstract:
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.
