Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types

被引:5
作者
Saad, Jacqueline F. [1 ,2 ]
Griffiths, Kristi R. [1 ]
Kohn, Michael R. [1 ,3 ]
Braund, Taylor A. [1 ,2 ,4 ,5 ]
Clarke, Simon [1 ,3 ]
Williams, Leanne M. [6 ,7 ]
Korgaonkar, Mayuresh S. [1 ,2 ]
机构
[1] Univ Sydney, Westmead Inst Med Res, Brain Dynam Ctr, Sydney, NSW, Australia
[2] Univ Sydney, Fac Med & Hlth, Sch Med, Sydney, NSW, Australia
[3] Westmead Hosp, Ctr Res Adolescents Hlth, Dept Adolescent & Young Adult Med, Sydney, NSW, Australia
[4] Univ New South Wales, Black Dog Inst, Sydney, NSW, Australia
[5] Univ New South Wales, Sch Psychiat, Sydney, NSW, Australia
[6] Stanford Univ, Dept Psychiat & Behav Sci, Stanford, CA USA
[7] VA Palo Alto Hlth Care Syst, Sierra Pacific Mental Illness Res Educ & Clin Ctr, Palo Alto, CA USA
来源
FRONTIERS IN HUMAN NEUROSCIENCE | 2022年 / 16卷
基金
澳大利亚国家健康与医学研究理事会;
关键词
ADHD combined; ADHD inattentive; brain functional connectivity; functional connectome; network-based statistics; default mode network; DEFICIT/HYPERACTIVITY DISORDER; BRAIN NETWORKS; INHIBITORY CONTROL; MOTION ARTIFACT; CHILDREN; ARCHITECTURE; SYMPTOMS; ADHD; FMRI; MRI;
D O I
10.3389/fnhum.2022.859538
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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 (n = 15) or combined (ADHD-C) type (n = 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.
引用
收藏
页数:14
相关论文
共 86 条
  • [1] Resting state dynamic functional connectivity in children with attention deficit/hyperactivity disorder
    Ahmadi, Maliheh
    Kazemi, Kamran
    Kuc, Katarzyna
    Cybulska-Klosowicz, Anita
    Helfroush, Mohammad Sadegh
    Aarabi, Ardalan
    [J]. JOURNAL OF NEURAL ENGINEERING, 2021, 18 (04)
  • [2] [Anonymous], 2013, Diagnostic and statistical manual of mental disorders: DSM-5, VFifth
  • [3] Controlling the false discovery rate in behavior genetics research
    Benjamini, Y
    Drai, D
    Elmer, G
    Kafkafi, N
    Golani, I
    [J]. BEHAVIOURAL BRAIN RESEARCH, 2001, 125 (1-2) : 279 - 284
  • [4] Hippocampal Volume as a Putative Marker of Resilience or Compensation to Minor Depressive Symptoms in a Nonclinical Sample
    Besteher, Bianca
    Squarcina, Letizia
    Spalthoff, Robert
    Bellani, Marcella
    Gaser, Christian
    Brambilla, Paolo
    Nenadic, Igor
    [J]. FRONTIERS IN PSYCHIATRY, 2019, 10
  • [5] Age-dependent decline of symptoms of attention deficit hyperactivity disorder: Impact of remission definition and symptom type
    Biederman, J
    Mick, E
    Faraone, SV
    [J]. AMERICAN JOURNAL OF PSYCHIATRY, 2000, 157 (05) : 816 - 818
  • [6] Structural and functional connectivity in children and adolescents with and without attention deficit/hyperactivity disorder
    Bos, Dienke J.
    Oranje, Bob
    Achterberg, Michelle
    Vlaskamp, Chantal
    Ambrosino, Sara
    de Reus, Marcel A.
    van den Heuvel, Martijn P.
    Rombouts, Serge A. R. B.
    Durston, Sarah
    [J]. JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY, 2017, 58 (07) : 810 - 818
  • [7] Default mode network connectivity and attention-deficit/hyperactivity disorder in adolescence: Associations with delay aversion and temporal discounting, but not mind wandering
    Broulidakis, M. John
    Golm, Dennis
    Cortese, Samuele
    Fairchild, Graeme
    Sonuga-Barke, Edmund
    [J]. INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2022, 173 : 38 - 44
  • [8] The brain's default network - Anatomy, function, and relevance to disease
    Buckner, Randy L.
    Andrews-Hanna, Jessica R.
    Schacter, Daniel L.
    [J]. YEAR IN COGNITIVE NEUROSCIENCE 2008, 2008, 1124 : 1 - 38
  • [9] Complex brain networks: graph theoretical analysis of structural and functional systems
    Bullmore, Edward T.
    Sporns, Olaf
    [J]. NATURE REVIEWS NEUROSCIENCE, 2009, 10 (03) : 186 - 198
  • [10] Attention-Deficit/Hyperactivity Disorder and Attention Networks
    Bush, George
    [J]. NEUROPSYCHOPHARMACOLOGY, 2010, 35 (01) : 278 - 300