Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study.

Ardalan Aarabi,Anita Cybulska-Klosowicz,Mohammad Sadegh Helfroush,Maliheh Ahmadi,Kamran Kazemi,Katarzyna Kuc

doi:10.3390/brainsci11070938

Abstract

Growing evidence indicates that disruptions in the brain’s functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

Highlights

Attention deficit hyperactivity disorder (ADHD), as one of the most common neurodevelopmental disorders, affects 2.2–17.8% of all school-aged children and adolescents [1,2].ADHD is categorized into three subtypes: a rarely identified hyperactive-impulsive subtype, an inattentive subtype (ADHDI ) and the most common combined subtype (ADHDC ), characterized by both inattention and hyperactivity (according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV)) [3]
We found a significant widespread decrease in the alpha source power for ADHDC children compared with typically developing children (TD) individuals [5]
We used exact Low Resolution Electric Tomography software (eLORETA) and lagged phase synchronization (LPS) to assess alterations in functional connectivity in ADHD children compared to healthy controls in different frequency bands using high-density EEG data under resting-state, eyes-closed conditions

Summary

Introduction

Attention deficit hyperactivity disorder (ADHD), as one of the most common neurodevelopmental disorders, affects 2.2–17.8% of all school-aged children and adolescents [1,2]. ADHD is categorized into three subtypes: a rarely identified hyperactive-impulsive subtype, an inattentive subtype (ADHDI ) and the most common combined subtype (ADHDC ), characterized by both inattention and hyperactivity (according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV)) [3]. Since children with ADHD are unable to sustain attention on tasks, they may have greater difficulties with learning and academic success, their social lives and professional achievement [4]. The neural mechanism underlying the pathophysiology of ADHDC and ADHDI is still not well understood. Having a high temporal resolution (milliseconds), EEG can provide important information about the neural dynamics underlying functional network dysfunction in ADHD

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