Saad Jacqueline F, Griffiths Kristi R, Kohn Michael R, Braund Taylor A, Clarke Simon, Williams Leanne M, Korgaonkar Mayuresh S
Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, NSW, Australia.
School of Medicine, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
Front Hum Neurosci. 2022 Jun 9;16:859538. doi: 10.3389/fnhum.2022.859538. eCollection 2022.
Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8-17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type ( = 15) or combined (ADHD-C) type ( = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.
神经影像学研究揭示了注意缺陷多动障碍（ADHD）中的神经生物学差异，特别是那些研究连接中断和解剖网络组织的研究。然而，ADHD各类型的潜在病理生理学仍然难以捉摸，因为尚不清楚功能失调的网络连接是否是区分ADHD各类型的潜在临床症状的特征。在此，我们研究了内在功能网络连接性，以识别区分合并型（ADHD-C）和注意力不集中型（ADHD-I）表现类型的神经特征。将基于网络的统计（NBS）和图论分析应用于来自完成的功能磁共振成像（fMRI）扫描的任务衍生内在连接性数据，我们评估了34名ADHD参与者（年龄8 - 17岁）队列中的默认模式网络（DMN）和全脑功能网络拓扑结构，这些参与者根据《精神疾病诊断与统计手册》第四版（DSM-IV）标准被定义为主要是注意力不集中型（ADHD-I）（n = 15）或合并型（ADHD-C）（n = 19），以及39名年龄和性别匹配的发育正常的对照组。ADHD-C与ADHD-I的区别在于DMN内网络连接性差异减少。此外，DMN内连接性降低与ADHD评定量表（ADHD-RS）多动-冲动分量表得分呈负相关。与对照组相比，ADHD-C而非ADHD-I在DMN内连接性降低；DMN与躯体运动网络之间的网络间连接性；DMN与边缘系统网络之间的连接性；以及躯体运动与扣带回-额顶叶之间、与腹侧注意和背侧注意网络之间的连接性存在差异。然而，图论测量在各组之间没有显著差异。这些发现为ADHD各类型之间表型差异的内在网络提供了见解。此外，这些内在功能连接组特征支持了ADHD表现临床变异背后的神经生物学差异，特别是ADHD-C型中DMN功能连接性在内部和之间的降低。
