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Visual Abstract
Electroencephalogram aperiodic power spectral slope can be reliably measured and predicts ADHD risk in early development
EEG Aperiodic Power Spectral Slope and ADHD Risk
December 9, 2024
author
Karalunas SL, Ostlund BD, Alperin BR, Figuracion M, Gustafsson HC, Deming EM, Foti D, Antovich D, Dude J, Nigg J, Sullivan E
journal
Dev Psychobiol
Date Published
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Study Summary
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What They Studied
The researchers studied the reliability of the aperiodic EEG power spectrum slope as a marker for ADHD risk in infants and adolescents.
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What They Found
They found that the aperiodic exponent showed high internal consistency in both infants and adolescents, with different patterns related to family history and ADHD diagnosis influenced by stimulant treatment.
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What This Means
These findings suggest that EEG power spectrum analysis can potentially detect ADHD-related cortical development issues early in life, differing from other studies by emphasizing changes over time and treatment effects.
Study Overview
Background & Objectives
Recent research explores the potential of EEG, a brain wave measurement tool, to shed light on ADHD risk. The focus is on the aperiodic exponent, a specific aspect of brain wave patterns, which could serve as a marker for ADHD, especially in its early stages.
The study delves into how this marker might indicate ADHD risk from infancy. Researchers look at its reliability amidst difficulties in connecting brain wave measures over time and understanding treatment effects.
The study delves into how this marker might indicate ADHD risk from infancy. Researchers look at its reliability amidst difficulties in connecting brain wave measures over time and understanding treatment effects.
Abstract: background
The aperiodic exponent of the electroencephalogram (EEG) power spectrum has received growing attention as a physiological marker of neu...more
Study Summary
Methods
The researchers assessed the consistency of the EEG power spectrum's aperiodic slope, and its ties to ADHD risk. The study looked at two groups: infants and adolescents. 69 infants around 1 month and 262 adolescents aged 11-17 were included.
By analyzing both age groups, they aimed to understand how consistent this marker is over time and across different stages in life. The study ensures reliability by comparing the EEG traits across these distinct developmental periods.
By analyzing both age groups, they aimed to understand how consistent this marker is over time and across different stages in life. The study ensures reliability by comparing the EEG traits across these distinct developmental periods.
Abstract: methods
Here, we investigate the internal consistency of the aperiodic EEG power spectrum slope and its association with ADHD risk in both infa...more
Study Results
Results
For infants, the study found that a larger aperiodic exponent indicated a higher family history of ADHD. This suggests early epilepsy markers could exist. In contrast, results showed that adolescents with ADHD had a smaller aperiodic exponent. This pattern, however, was observed only in adolescents who didn't receive stimulant medications. These variations suggest that ADHD risk can be detected early, possibly indicating disruptions in brain development.
Thus, the analysis reveals how untreated and treated ADHD influences EEG patterns, differing by age and medication status.
Thus, the analysis reveals how untreated and treated ADHD influences EEG patterns, differing by age and medication status.
Abstract: results
In infancy, a larger aperiodic exponent was associated with greater family history of ADHD. In contrast, in adolescence, ADHD diagnosis...more
Study Summary
Conclusions
The research indicates a developmental change in the EEG power spectrum associated with ADHD, particularly a flattening. This abnormality might represent brain excitation and inhibition imbalances, potentially leading to ongoing connectivity differences in the brain.
The findings offer insights into how ADHD affects brain growth and how changes in EEG patterns could become an early detection tool. Understanding these shifts could help researchers and clinicians address ADHD more effectively across different life stages.
The findings offer insights into how ADHD affects brain growth and how changes in EEG patterns could become an early detection tool. Understanding these shifts could help researchers and clinicians address ADHD more effectively across different life stages.
Abstract: conclusions
Together, findings imply a dynamic developmental shift in which the developmentally normative flattening of the EEG power spectrum is exaggerated in ADHD, potentially reflecting imbalances in cortical excitation and inhibition that could contribute t...more
Clinical Guidelines
Guidelines suggest that ADHD can be diagnosed in preschool-aged children and that behavioral interventions, such as PTBM, are primary for this age group. Screening for comorbid conditions should be included in ADHD evaluations.
Stimulant medications are effective in treating ADHD but commonly cause appetite loss, headaches, and sleep disturbances.
ADHD-specific scales, with over 90% sensitivity and specificity, support diagnosis in appropriate populations.
Stimulant medications are effective in treating ADHD but commonly cause appetite loss, headaches, and sleep disturbances.
ADHD-specific scales, with over 90% sensitivity and specificity, support diagnosis in appropriate populations.
Literature Review
[Robertson] et al.
Core Insight:Both papers examine EEG power spectrum features in ADHD, highlighting its role in identifying neurodevelopmental patterns.
What It Adds:
Age-specific EEG insights: This paper focuses on EEG features in young children, complementing age scope of the main paper.
Medication effects on EEG: Identifies how stimulants affect EEG measures in ADHD, a contrast to the main paper's findings.
Shared Themes:Both studies explore EEG markers in ADHD, suggesting interactions between EEG traits and ADHD symptoms.
Literature Review
[Ostlund] et al.
Core Insight:Both papers explore the aperiodic EEG exponent as an indicator of ADHD but report different age-related manifestations.
What It Adds:
Cognitive Correlates: This paper links EEG exponent to reaction times and processing.
Inhibition Imbalance: Suggests EEG exponent relates to excitation/inhibition issues.
Key Differences:The main paper examines lifespan differences; this paper focuses on cognitive efficiency in adolescents.
Literature Review
Dakwar-Kawar et al.
Core Insight:The comparison paper identifies neural oscillations, both periodic and aperiodic, as factors in processing speed deficits in ADHD.
What It Adds:
Processing Speed and ADHD: Link between aperiodic exponent and slower processing speed.
Complementary Metrics: Highlights different roles of periodic and aperiodic.
