Abstract

Attention deficit hyperactivity disorder (ADHD) is one of the most widespread mental disorders and often persists from childhood to adulthood, and its symptoms vary with age. In this study, we aim to determine the disrupted dynamic functional network connectivity differences in adult, adolescent, and child ADHD using resting-state functional magnetic resonance imaging (rs-fMRI) data consisting of 35 children (8.64 ± 0.81 years), 40 adolescents (14.11 ± 1.83 years), and 39 adults (31.59 ± 10.13 years). We hypothesized that functional connectivity is time-varying and that there are within- and between-network connectivity differences among the three age groups. Nine functional networks were identified using group ICA, and three FC-states were recognized based on their dynamic functional network connectivity (dFNC) pattern. Fraction of time, mean dwell time, transition probability, degree-in, and degree-out were calculated to measure the state dynamics. Higher-order networks including the DMN, SN, and FPN, and lower-order networks comprising the SMN, VN, SC, and AUD were frequently distributed across all states and were found to show connectivity differences among the three age groups. Our findings imply abnormal dynamic interactions and dysconnectivity associated with different ADHD, and these abnormalities differ between the three ADHD age groups. Given the dFNC differences between the three groups in the current study, our work further provides new insights into the mechanism subserved by age difference in the pathophysiology of ADHD and may set the grounds for future case-control studies in the individual age groups, as well as serving as a guide in the development of treatment strategies to target these specific networks in each age group.

Highlights

  • Attention deficit hyperactivity disorder (ADHD) is one of the most common mental disorders worldwide, characterized by inattentive, hyperactive, or impulsive behaviors (American Psychiatric Association., 2000)

  • The selected 50 intrinsic component networks (ICNs) were further categorized into nine networks based on their anatomical and functional properties, including the sensorimotor network (SMN), visual network (VN), default-mode network (DMN), central executive network (CEN), cerebellum network (CBN), subcortical network (SC), auditory network (AUD), frontoparietal network (FPN), and salience network (SN)

  • States 1 and 3 showed positivity connectivity within the DMN, with state 1 distinguishing itself with negative connectivity between some ICNS of the CBN, AUD, and VN with other networks

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Summary

Introduction

Attention deficit hyperactivity disorder (ADHD) is one of the most common mental disorders worldwide, characterized by inattentive, hyperactive, or impulsive behaviors (American Psychiatric Association., 2000). Functional magnetic resonance imaging (fMRI) has become a popular technique for studying brain diseases or disorders such as ADHD. The majority of these ADHD fMRI studies have followed a task-based approach, aiming to examine how brain function may be modulated by group status during cognitive task performance. This approach is designed to isolate specific cognitive processes that may be linked to or modified by ADHD symptoms or treatment. There has been an overwhelming interest in an alternative method called resting-state functional magnetic resonance imaging (rs-fMRI). The discovery of the default mode network of brain structures, which is said to be active during the resting state and show dynamic negative correlations with task-related regions, has opened up new areas of investigation (Raichle et al, 2001; Greicius et al, 2003) and has raised interesting questions with regards to abnormal patterns of brain activation in patients with ADHD

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