Differences in Disrupted Dynamic Functional Network Connectivity Among Children, Adolescents, and Adults With Attention Deficit/Hyperactivity Disorder: A Resting-State fMRI Study

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.

Structural differences among children, adolescents, and adults with attention-deficit/hyperactivity disorder and abnormal Granger causality of the right pallidum and whole-brain

“…The amygdala is said to be involved in emotional regulation especially negative emotions (Bonnet et al, 2015 ); hence, the activation of the left amygdala caused by the right pallidum might suggest emotional impairment in ADHD patients. Previous structural and functional studies have reported abnormal connectivity in the cerebellum of ADHD patients (Valera et al, 2007 ; Agoalikum et al, 2021 ). Deficits in gray matter volume and cerebellum activation further provide evidence of the cerebellum’s implication in ADHD.…”

“…This activation of the bilateral fusiform was caused by the neural activity in the right pallidum. The occipital cortex and the fusiform gyri are part of the visual network, suggested to be responsible for processing information about static and moving objects, spatial awareness and guidance of action, and object recognition (James et al, 2003 ; Nassi and Callaway, 2009 ) and have been reported to show abnormal connectivity in several ADHD studies (Benli et al, 2018 ; Agoalikum et al, 2021 ). Our results also showed that the neural activity in the seed region could predict the neural activity in the left postcentral gyrus and the left paracentral lobule, which are part of the somatosensory system reported to be implicated in ADHD (Parush et al, 1997 ).…”

“…The prevalence of ADHD in children, adolescents, and adults is said to be 9.5%, 11.4%, and 4.4%, respectively (Gimpel and Kuhn, 2000 ; Barbaresi et al, 2002 ; Kessler et al, 2006 ; Wolraich et al, 2011 ), with symptoms varying across different age groups (Katragadda and Schubiner, 2007 ). There has been accumulated pathophysiological evidence from structural and functional neuroimaging studies of ADHD (Seidman et al, 2005 ; Frodl and Skokauskas, 2012 ; Agoalikum et al, 2021 ).…”

Multiple measurement analysis of resting-state fMRI for ADHD classification in adolescent brain from the ABCD study

“…Concerning ADHD, a study [ 55 ] built a diagnostic model based on the temporal variability of dynamic functional connectivity, but it did not depend on sliding windows. Another study [ 56 ] utilized dynamic functional network connectivity (dFNC) to access FC differences among child, adolescent, and adult ADHD patients rather than between patients and healthy controls. Moreover, the dFNC analysis process is different from dHOFC.…”

Multiple Measurement Analysis of Resting-State fMRI for ADHD Classification in Adolescent Brain from the ABCD Study

“…Another study utilized dynamic functional network connectivity (dFNC) to access FC differences among child, adolescent, and adult ADHD patients rather than between patients and healthy controls. Moreover, the dFNC analysis process is different from dHOFC 54 . To our knowledge, no other study applies tHOFC, dHOFC, and three SR-derived FC (GSR, SSGSR, and SLR) to the classi cation of ADHD.…”