Lifespan associations of resting-state brain functional networks with ADHD symptoms
Rong Wang,
Yongchen Fan,
Ying Wu,
Yu-Feng Zang,
Changsong Zhou
Affiliations
Rong Wang
State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an 710049, China; Department of Physics, Centre for Nonlinear Studies, Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong; College of Science, Xi’an University of Science and Technology, Xi’an 710054, China; Corresponding author
Yongchen Fan
College of Science, Xi’an University of Science and Technology, Xi’an 710054, China
Ying Wu
College of Science, Xi’an University of Science and Technology, Xi’an 710054, China
Yu-Feng Zang
Center for Cognition and Brain Disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
Changsong Zhou
Department of Physics, Centre for Nonlinear Studies, Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong; Department of Physics, Zhejiang University, Hangzhou 310027, China; Corresponding author
Summary: Attention-deficit/hyperactivity disorder (ADHD) is increasingly being diagnosed in both children and adults, but the neural mechanisms that underlie its distinct symptoms and whether children and adults share the same mechanism remain poorly understood. Here, we used a nested-spectral partition approach to study resting-state brain networks of ADHD patients (n = 97) and healthy controls (HCs, n = 97) across the lifespan (7–50 years). Compared to the linear lifespan associations of brain segregation and integration with age in HCs, ADHD patients have a quadratic association in the whole-brain and in most functional systems, whereas the limbic system dominantly affected by ADHD has a linear association. Furthermore, the limbic system better predicts hyperactivity, and the salient attention system better predicts inattention. These predictions are shared in children and adults with ADHD. Our findings reveal a lifespan association of brain networks with ADHD and provide potential shared neural bases of distinct ADHD symptoms in children and adults.
