Patterns of brain dynamic functional connectivity are linked with attention-deficit/hyperactivity disorder-related behavioral and cognitive dimensions

BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established. METHODS We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors. RESULTS We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811-0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity. CONCLUSIONS These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.

[1]  Lizhou Chen,et al.  Brain alterations in sensorimotor and emotional regions associated with temporomandibular disorders. , 2022, Oral diseases.

[2]  Q. Gong,et al.  Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia , 2022, Schizophrenia bulletin.

[3]  L. Yao,et al.  Impaired dynamic functional brain properties and their relationship to symptoms in never treated first-episode patients with schizophrenia , 2022, Schizophrenia.

[4]  Q. Gong,et al.  Recent advances in psychoradiology , 2022, Physics in medicine and biology.

[5]  J. Sweeney,et al.  Cortical Thickness Abnormalities at Different Stages of the Illness Course in Schizophrenia , 2022, JAMA psychiatry.

[6]  J. Sweeney,et al.  Altered brain functional network dynamics in obsessive–compulsive disorder , 2021, Human brain mapping.

[7]  E. Rolls,et al.  Brain dynamics: the temporal variability of connectivity, and differences in schizophrenia and ADHD , 2021, Translational Psychiatry.

[8]  Jessica R. Cohen,et al.  Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis , 2021, NeuroImage.

[9]  F. Castellanos,et al.  Systematic Review and Meta-analysis: Resting State Functional Magnetic Resonance Imaging Studies of Attention-Deficit/Hyperactivity Disorder. , 2020, Journal of the American Academy of Child and Adolescent Psychiatry.

[10]  Peter Fransson,et al.  Dynamic synergetic configurations of resting-state networks in ADHD , 2019, NeuroImage.

[11]  S. Eickhoff,et al.  Brain alterations in children/adolescents with ADHD revisited: A neuroimaging meta-analysis of 96 structural and functional studies , 2019, Neuroscience & Biobehavioral Reviews.

[12]  Ivanei E. Bramati,et al.  Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples. , 2019, The American journal of psychiatry.

[13]  C. Büchel,et al.  Pubertal maturation and sex effects on the default-mode network connectivity implicated in mood dysregulation , 2019, Translational Psychiatry.

[14]  Danielle S Bassett,et al.  Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity , 2019, Network Neuroscience.

[15]  Vince D Calhoun,et al.  Dynamic connectivity and the effects of maturation in youth with attention deficit hyperactivity disorder , 2018, Network Neuroscience.

[16]  F. Castellanos,et al.  Research Review: Diffusion tensor imaging studies of attention‐deficit/hyperactivity disorder meta‐analyses and reflections on head motion , 2018, Journal of child psychology and psychiatry, and allied disciplines.

[17]  Kaustubh Supekar,et al.  Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits. , 2017, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[18]  R. Lewis‐Fernández,et al.  Three Approaches to Understanding and Classifying Mental Disorder: ICD-11, DSM-5, and the National Institute of Mental Health’s Research Domain Criteria (RDoC) , 2017, Psychological science in the public interest : a journal of the American Psychological Society.

[19]  Dimitri Van De Ville,et al.  The dynamic functional connectome: State-of-the-art and perspectives , 2017, NeuroImage.

[20]  Richard F. Betzel,et al.  Linked dimensions of psychopathology and connectivity in functional brain networks , 2017, bioRxiv.

[21]  Dongrong Xu,et al.  Altered resting-state intra- and inter- network functional connectivity in patients with persistent somatoform pain disorder , 2017, PloS one.

[22]  T. Kaufmann,et al.  Increased default-mode variability is related to reduced task-performance and is evident in adults with ADHD , 2017, NeuroImage: Clinical.

[23]  Evan M. Gordon,et al.  On the Stability of BOLD fMRI Correlations , 2016, Cerebral cortex.

[24]  A. Tickle,et al.  The Efficacy of Cognitive Behavioral Therapy for Adults With ADHD: A Systematic Review and Meta-Analysis of Randomized Controlled Trials , 2020, Journal of attention disorders.

[25]  P. Fox,et al.  Functional Decoding and Meta-analytic Connectivity Modeling in Adult Attention-Deficit/Hyperactivity Disorder , 2016, Biological Psychiatry.

[26]  Olaf Sporns,et al.  Integration and segregation of large-scale brain networks during short-term task automatization , 2016, Nature Communications.

[27]  R. Silberstein,et al.  Dopaminergic modulation of default mode network brain functional connectivity in attention deficit hyperactivity disorder , 2016, Brain and behavior.

[28]  F. Castellanos,et al.  Intrinsic Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Science in Development. , 2016, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[29]  Barbara J. Sahakian,et al.  Default mode network connectivity during task execution , 2015, NeuroImage.

[30]  Yasuyuki Taki,et al.  Degree centrality and fractional amplitude of low-frequency oscillations associated with Stroop interference , 2015, NeuroImage.

[31]  Thomas E. Nichols,et al.  A positive-negative mode of population covariation links brain connectivity, demographics and behavior , 2015, Nature Neuroscience.

[32]  Lucina Q. Uddin,et al.  Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience , 2015, Trends in Neurosciences.

[33]  Efstathios D. Gennatas,et al.  Connectome-Wide Network Analysis of Youth with Psychosis Spectrum Symptoms , 2015, Molecular Psychiatry.

[34]  P. Asherson,et al.  Attention-deficit/hyperactivity disorder is the extreme and impairing tail of a continuum. , 2015, Journal of the American Academy of Child and Adolescent Psychiatry.

[35]  A. Meyer,et al.  What do verbal fluency tasks measure? Predictors of verbal fluency performance in older adults , 2014, Front. Psychol..

[36]  Qiyong Gong,et al.  Intrinsic brain abnormalities in attention deficit hyperactivity disorder: a resting-state functional MR imaging study. , 2014, Radiology.

[37]  Brian B. Avants,et al.  Sparse canonical correlation analysis relates network-level atrophy to multivariate cognitive measures in a neurodegenerative population , 2014, NeuroImage.

[38]  Peter Henningsen,et al.  Functional network connectivity of pain-related resting state networks in somatoform pain disorder: an exploratory fMRI study. , 2013, Journal of psychiatry & neuroscience : JPN.

[39]  Stephen M. Rao,et al.  Propofol disrupts functional interactions between sensory and high‐order processing of auditory verbal memory , 2012, Human brain mapping.

[40]  Michael P Milham,et al.  Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. , 2012, The American journal of psychiatry.

[41]  A. Zalesky,et al.  Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection , 2012, Proceedings of the National Academy of Sciences.

[42]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[43]  Adam Gazzaley,et al.  Differential coupling of visual cortex with default network or frontal-parietal network based on goals , 2011, Nature Neuroscience.

[44]  Alan C. Evans,et al.  Cortical development in typically developing children with symptoms of hyperactivity and impulsivity: support for a dimensional view of attention deficit hyperactivity disorder. , 2011, The American journal of psychiatry.

[45]  T. Insel,et al.  Wesleyan University From the SelectedWorks of Charles A . Sanislow , Ph . D . 2010 Research Domain Criteria ( RDoC ) : Toward a New Classification Framework for Research on Mental Disorders , 2018 .

[46]  W. Dillo,et al.  Neuronal correlates of ADHD in adults with evidence for compensation strategies – a functional MRI study with a Go/No-Go paradigm , 2010, German medical science : GMS e-journal.

[47]  N. Rose,et al.  Biomarkers in psychiatry , 2009, Nature.

[48]  R. Tibshirani,et al.  A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. , 2009, Biostatistics.

[49]  J L Bradshaw,et al.  Right parietal dysfunction in children with attention deficit hyperactivity disorder, combined type: a functional MRI study , 2007, Molecular Psychiatry.

[50]  James T. McCracken,et al.  Atypical Brain Activation During Simple & Complex Levels of Processing in Adult ADHD , 2007, Journal of attention disorders.

[51]  Jennifer D. Davis,et al.  Differential Impact of Executive Function on Visual Memory Tasks , 2006, The Clinical neuropsychologist.

[52]  Kristina M. Visscher,et al.  The neural bases of momentary lapses in attention , 2006, Nature Neuroscience.

[53]  Brian Toone,et al.  Task-specific hypoactivation in prefrontal and temporoparietal brain regions during motor inhibition and task switching in medication-naive children and adolescents with attention deficit hyperactivity disorder. , 2006, The American journal of psychiatry.

[54]  B. Pennington,et al.  Validity of the Executive Function Theory of Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Review , 2005, Biological Psychiatry.

[55]  C. Karatekin.  A test of the integrity of the components of Baddeley's model of working memory in attention-deficit/hyperactivity disorder (ADHD). , 2004, Journal of child psychology and psychiatry, and allied disciplines.

[56]  F. Castellanos,et al.  Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes , 2002, Nature Reviews Neuroscience.

[57]  M. Mintun,et al.  Positron emission tomography study of voluntary saccadic eye movements and spatial working memory. , 1996, Journal of neurophysiology.

[58]  A. Jensen,et al.  The Stroop color-word test: a review. , 1966, Acta psychologica.