Aperiodic components and aperiodic-adjusted alpha-band oscillations in children with ADHD
Ran Chen1, Wen-Juan Liu2, Jiu-Ju Wang3
1Mental Health Center, University-Town Hospital of Chongqing Medical University, Chongqing, China.
Insights
Children with Attention-Deficit/Hyperactivity Disorder (ADHD) exhibit a lower neural exponent, a potential biomarker for ADHD. This finding was consistent across various scalp regions and lateralization in EEG studies.
Area of Science:
- Neuroscience
- Developmental Psychology
- Biomarkers
Background:
- Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder affecting children.
- Understanding neural correlates like aperiodic properties and alpha-band oscillations is crucial for ADHD research.
- Previous research has not fully explored the influence of scalp region and lateralization on these neural measures in ADHD.
Purpose of the Study:
- To investigate aperiodic properties and aperiodic-adjusted alpha-band oscillations in children with ADHD.
- To examine the impact of scalp region and lateralization on these neural measures in ADHD.
- To identify potential neural biomarkers for ADHD in children aged 6-12 years.
Main Methods:
- Electroencephalography (EEG) recordings were obtained from 62 children with ADHD and 52 typically developing children (ages 6-12).
- The 'FOOOF' algorithm computed aperiodic parameters (exponent, offset) and aperiodic-adjusted alpha-band features (center frequency, adjusted power, bandwidth).
- Mixed-design ANOVAs and ANCOVAs were used to analyze the data, considering group, lateralization, scalp region, sex, and age.
Main Results:
- Children with ADHD showed a significantly lower exponent compared to controls, irrespective of lateralization, scalp region, or sex.
- No significant differences were found between groups for other measures (offset, adjusted power, bandwidth).
- Alpha-band center frequency increased with age; frontal adjusted power positively correlated with age; sex and lateralization affected offset and center frequency.
Conclusions:
- A lower neural exponent is a significant finding in children with ADHD, suggesting its potential as a biomarker.
- Age, sex, lateralization, and scalp region are important factors to consider in future research on these neural features.
- This study provides insights into the neural underpinnings of ADHD in children, highlighting specific quantifiable differences.
Abstract:
This study aimed to investigate the aperiodic properties and aperiodic-adjusted alpha-band oscillations in children with ADHD, focusing on the influence of different scalp regions and lateralization on these neural correlates. Sixty-two ADHD children and 52 typical developing children aged 6-12 years were enrolled. EEG recordings were made with eyes closed for a minimum of 6 min. The 'FOOOF' was used to compute aperiodic parameters (exponent and offset), and aperiodic-adjusted alpha-band features including center frequency (CF), adjusted power (AP), and bandwidth (BW). Mixed-design ANOVAs were conducted with two between-subjects levels (ADHD and control groups) and two within-subjects' factors (lateralization and scalp region). ANCOVAs were conducted after accounting for sex and age. The ADHD group showed a significantly lower exponent compared to the control group, and this difference was not influenced significantly by factors like lateralization, scalp region, or sex. There were no notable distinctions between the groups for other measures. We noticed alpha-band CF tends to increase with age, while only frontal AP shows a significant positive correlation with age. Significant main effects of sex and lateralization were observed for offset, along with an interaction effect between sex and lateralization for CF. Our findings indicate that children aged 6-12 with ADHD have a markedly lower exponent, suggesting that this measure could potentially serve as a biomarker for ADHD. Future studies should consider factors such as age, sex, lateralization, and scalp region when investigating aperiodic and aperiodic-adjusted features.
More Related Videos
13:09Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol
Published on: April 1, 2018
05:48The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
Published on: June 12, 2020
Related Concept Videos
01:30Attention-Deficit/Hyperactivity Disorder
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
01:30Oppositional Defiant Disorder
Diagnostic Criteria and...
01:23Brain Waves