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. 2021 Nov-Dec;50(6):746-762.
doi: 10.1080/15374416.2020.1796680. Epub 2020 Aug 18.

Resting-state EEG Connectivity in Young Children with ADHD

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Resting-state EEG Connectivity in Young Children with ADHD

Sarah Furlong et al. J Clin Child Adolesc Psychol. 2021 Nov-Dec.

Abstract

Objective: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and impairing neurodevelopmental disorder. While early childhood is a crucial time for early intervention, it is characterized by instability of ADHD diagnosis. Neural correlates of ADHD have potential to improve diagnostic accuracy; however, minimal research has focused on early childhood. Research indicates that disrupted neural connectivity is associated with ADHD in older children. Here, we explore network connectivity as a potential neural correlate of ADHD diagnosis in early childhood.Method: We collected EEG data in 52 medication-naïve children with ADHD and in 77 typically developing controls (3-7 years). Data was collected with the EGI 128 HydroCel Sensor Net System, but to optimize the ICA, the data was down sampled to the 10-10 system. Connectivity was measured as the synchronization of the time series of each pair of electrodes. Subsequent analyses utilized graph theoretical methods to further characterize network connectivity.Results: Increased global efficiency, which measures the efficiency of information transfer across the entire brain, was associated with increased inattentive symptom severity. Further, this association was robust to controls for age, IQ, SES, and internalizing psychopathology.Conclusions: Overall, our findings indicate that increased global efficiency, which suggests a hyper-connected neural network, is associated with elevated ADHD symptom severity. These findings extend previous work reporting disruption of neural network connectivity in older children with ADHD into early childhood.

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Conflict of interest statement

Conflict of Interest

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1. Average Power Spectra Across All Participants
Note. The average power spectra, calculated across all participants to confirm that the data used in the current analysis include the expected peak in the alpha band.
Figure 2
Figure 2. Global Efficiency in Eyes-open Condition and Inattentive Symptoms at Individual Network Costs
Note. A plot of the relationship of global efficiency in alpha in EO and inattention at each network cost. The x-axis has each network cost value, and the y-axis contains the β values of the relationship of global efficiency and inattentive symptoms. An * indicates a significant (p<0.05) association of global efficiency and inattentive symptoms.
Figure 3
Figure 3. Global Efficiency in Eyes-closed and Inattentive Symptoms at Individual Network Costs
Note. A plot of the relationship of global efficiency in alpha in EC and inattentive symptoms at each network cost. The x-axis has each network cost value, and the y-axis contains β values of the relationship of global efficiency and inattentive symptoms. An * indicates a significant (p<0.05) association of global efficiency and inattentive symptoms.

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