Interactions between the default network and dorsal attention network vary across default subsystems, time, and cognitive states

ABSTRACT Anticorrelation between the default network (DN) and dorsal attention network (DAN) is thought to be an intrinsic aspect of functional brain organization reflecting competing functions. However, the effect size of functional connectivity (FC) between the DN and DAN has yet to be established. Furthermore, the stability of anticorrelations across distinct DN subsystems, different contexts, and time, remains unexplored. In study 1 we summarize effect sizes of DN‐DAN FC from 20 studies, and in study 2 we probe the variability of DN‐DAN interactions across six different cognitive states in a new data set. We show that: (i) the DN and DAN have an independent rather than anticorrelated relationship when global signal regression is not used (median effect size across studies: r=−.06; 95% CI: −.15 to .08); (ii) the DAN exhibits weak negative FC with the DN Core subsystem but is uncorrelated with the dorsomedial prefrontal and medial temporal lobe subsystems; (iii) DN‐DAN interactions vary significantly across different cognitive states; (iv) DN‐DAN FC fluctuates across time between periods of anticorrelation and periods of positive correlation; and (v) changes across time in the strength of DN‐DAN coupling are coordinated with interactions involving the frontoparietal control network (FPCN). Overall, the observed weak effect sizes related to DN‐DAN anticorrelation suggest the need to re‐conceptualize the nature of interactions between these networks. Furthermore, our findings demonstrate that DN‐DAN interactions are not stable, but rather, exhibit substantial variability across time and context, and are coordinated with broader network dynamics involving the FPCN.

[1]  Hang Joon Jo,et al.  Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression , 2012, Brain Connect..

[2]  B. T. Thomas Yeo,et al.  Cerebral functional connectivity periodically (de)synchronizes with anatomical constraints , 2015, Brain Structure and Function.

[3]  J. Haxby,et al.  The representation of self and person knowledge in the medial prefrontal cortex. , 2012, Wiley interdisciplinary reviews. Cognitive science.

[4]  R. Nathan Spreng,et al.  The wandering brain: Meta-analysis of functional neuroimaging studies of mind-wandering and related spontaneous thought processes , 2015, NeuroImage.

[5]  S. Petersen,et al.  Brain Networks and Cognitive Architectures , 2015, Neuron.

[6]  Susan L. Whitfield-Gabrieli,et al.  Conn: A Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks , 2012, Brain Connect..

[7]  Danielle S Bassett,et al.  Cross-linked structure of network evolution. , 2013, Chaos.

[8]  Catie Chang,et al.  Effects of model-based physiological noise correction on default mode network anti-correlations and correlations , 2009, NeuroImage.

[9]  Jonathan D. Power,et al.  Intrinsic and Task-Evoked Network Architectures of the Human Brain , 2014, Neuron.

[10]  M. Fox,et al.  The global signal and observed anticorrelated resting state brain networks. , 2009, Journal of neurophysiology.

[11]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Dinggang Shen,et al.  Cerebral Cortex doi:10.1093/cercor/bhs043 Cerebral Cortex Advance Access published February 24, 2012 The Synchronization within and Interaction between the Default and Dorsal Attention Networks in Early Infancy , 2022 .

[13]  Danielle S. Bassett,et al.  Explicitly Linking Regional Activation and Function Connectivity: Community Structure of Weighted Networks with Continuous Annotation , 2016, 1611.07962.

[14]  J. Andrews-Hanna,et al.  The neurobiology of self-generated thought from cells to systems: Integrating evidence from lesion studies, human intracranial electrophysiology, neurochemistry, and neuroendocrinology , 2016, Neuroscience.

[15]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[16]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.

[17]  Susanne Walitza,et al.  Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis. , 2014, Schizophrenia bulletin.

[18]  Olaf Sporns,et al.  Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks , 2015, NeuroImage.

[19]  I. Cuthill,et al.  Effect size, confidence interval and statistical significance: a practical guide for biologists , 2007, Biological reviews of the Cambridge Philosophical Society.

[20]  C. Kelly,et al.  The extrinsic and intrinsic functional architectures of the human brain are not equivalent. , 2013, Cerebral cortex.

[21]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[22]  R. Buckner,et al.  Functional-Anatomic Fractionation of the Brain's Default Network , 2010, Neuron.

[23]  Archana Venkataraman,et al.  Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. , 2010, Journal of neurophysiology.

[24]  A. Nobre,et al.  Orienting Attention Based on Long-Term Memory Experience , 2006, Neuron.

[25]  M. Raichle,et al.  Searching for a baseline: Functional imaging and the resting human brain , 2001, Nature Reviews Neuroscience.

[26]  Michael W. L. Chee,et al.  Sleep deprivation reduces default mode network connectivity and anti-correlation during rest and task performance , 2012, NeuroImage.

[27]  Daniel L. Schacter,et al.  Intrinsic Architecture Underlying the Relations among the Default, Dorsal Attention, and Frontoparietal Control Networks of the Human Brain , 2013, Journal of Cognitive Neuroscience.

[28]  B. T. Thomas Yeo,et al.  Functional connectivity during rested wakefulness predicts vulnerability to sleep deprivation , 2015, NeuroImage.

[29]  Daniel L. Schacter,et al.  Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition , 2010, NeuroImage.

[30]  R. Buckner,et al.  Evidence for the Default Network's Role in Spontaneous Cognition , 2010 .

[31]  A. Damasio,et al.  Neural correlates of different self domains , 2015, Brain and behavior.

[32]  Demis Hassabis,et al.  Imagine all the people: how the brain creates and uses personality models to predict behavior. , 2014, Cerebral cortex.

[33]  Leonardo L. Gollo,et al.  Time-resolved resting-state brain networks , 2014, Proceedings of the National Academy of Sciences.

[34]  S. Baron-Cohen,et al.  The "Reading the Mind in the Eyes" Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism. , 2001, Journal of child psychology and psychiatry, and allied disciplines.

[35]  Matthew L. Dixon,et al.  The Decision to Engage Cognitive Control Is Driven by Expected Reward-Value: Neural and Behavioral Evidence , 2012, PloS one.

[36]  Charles Dobson,et al.  Evaluative and generative modes of thought during the creative process , 2012, NeuroImage.

[37]  M. Fox,et al.  Individual Variability in Functional Connectivity Architecture of the Human Brain , 2013, Neuron.

[38]  Ravi S. Menon,et al.  Resting‐state networks show dynamic functional connectivity in awake humans and anesthetized macaques , 2013, Human brain mapping.

[39]  Rafael Malach,et al.  Extrinsic and intrinsic systems in the posterior cortex of the human brain revealed during natural sensory stimulation. , 2007, Cerebral cortex.

[40]  Mark G. Meekan,et al.  Effects of Ocean Acidification on Learning in Coral Reef Fishes , 2012, PloS one.

[41]  N. Farb,et al.  Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference. , 2007, Social cognitive and affective neuroscience.

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

[43]  William W. Graves,et al.  Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. , 2009, Cerebral cortex.

[44]  Janice Chen,et al.  Dynamic reconfiguration of the default mode network during narrative comprehension , 2016, Nature Communications.

[45]  Sterling C. Johnson,et al.  Relevance to self: A brief review and framework of neural systems underlying appraisal , 2007, Neuroscience & Biobehavioral Reviews.

[46]  Bharat B. Biswal,et al.  Competition between functional brain networks mediates behavioral variability , 2008, NeuroImage.

[47]  Laura C. Buchanan,et al.  Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns , 2015, Proceedings of the National Academy of Sciences.

[48]  Catie Chang,et al.  Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.

[49]  Michael W. Cole,et al.  Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence , 2012, The Journal of Neuroscience.

[50]  Erik D. Reichle,et al.  Meta-awareness, perceptual decoupling and the wandering mind , 2011, Trends in Cognitive Sciences.

[51]  B T Thomas Yeo,et al.  Reconfigurable task-dependent functional coupling modes cluster around a core functional architecture , 2014, Philosophical Transactions of the Royal Society B: Biological Sciences.

[52]  Kathy D. Gerlach,et al.  Future planning: default network activity couples with frontoparietal control network and reward-processing regions during process and outcome simulations. , 2014, Social cognitive and affective neuroscience.

[53]  Matthew L. Dixon,et al.  A framework for understanding the relationship between externally and internally directed cognition , 2014, Neuropsychologia.

[54]  E. Miller,et al.  Response to Comment on "Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices" , 2007, Science.

[55]  Earl K Miller,et al.  Cortical circuits for the control of attention , 2012, Current Opinion in Neurobiology.

[56]  E. Balteau,et al.  Valuing one's self: medial prefrontal involvement in epistemic and emotive investments in self-views. , 2012, Cerebral cortex.

[57]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[58]  David C. Van Essen,et al.  Application of Information Technology: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex , 2001, J. Am. Medical Informatics Assoc..

[59]  Darya L. Zabelina,et al.  Dynamic network interactions supporting internally-oriented cognition , 2016, Current Opinion in Neurobiology.

[60]  Jonathan D. Power,et al.  Multi-task connectivity reveals flexible hubs for adaptive task control , 2013, Nature Neuroscience.

[61]  Y. Miyashita,et al.  Top-down signal from prefrontal cortex in executive control of memory retrieval , 1999, Nature.

[62]  David J. Heeger,et al.  Influence of meditation on anti-correlated networks in the brain , 2012, Front. Hum. Neurosci..

[63]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[64]  Scott R Sponheim,et al.  Prefrontal neurons transmit signals to parietal neurons that reflect executive control of cognition , 2013, Nature Neuroscience.

[65]  Bruce R. Rosen,et al.  Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measures , 2015, Scientific Data.

[66]  Walter Schneider,et al.  The cognitive control network: Integrated cortical regions with dissociable functions , 2007, NeuroImage.

[67]  Joseph W. Kable,et al.  The valuation system: A coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value , 2013, NeuroImage.

[68]  D. Bassett,et al.  Dynamic reconfiguration of frontal brain networks during executive cognition in humans , 2015, Proceedings of the National Academy of Sciences.

[69]  宁北芳,et al.  疟原虫var基因转换速率变化导致抗原变异[英]/Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A , 2005 .

[70]  Danielle S. Bassett,et al.  Brain Network Adaptability across Task States , 2014, PLoS Comput. Biol..

[71]  Jessica R. Andrews-Hanna,et al.  The Brain’s Default Network and Its Adaptive Role in Internal Mentation , 2012, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[72]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[73]  David A. Leopold,et al.  Dynamic functional connectivity: Promise, issues, and interpretations , 2013, NeuroImage.

[74]  M. Greicius,et al.  Decoding subject-driven cognitive states with whole-brain connectivity patterns. , 2012, Cerebral cortex.

[75]  K. Christoff,et al.  Undirected thought: Neural determinants and correlates , 2012, Brain Research.

[76]  Paula Tavares,et al.  Paying attention to social meaning: an FMRI study. , 2008, Cerebral cortex.

[77]  Mathew L. Dixon,et al.  Hierarchical Organization of Frontoparietal Control Networks Underlying Goal-Directed Behavior , 2017 .

[78]  Fenna M. Krienen,et al.  Opportunities and limitations of intrinsic functional connectivity MRI , 2013, Nature Neuroscience.

[79]  Kevin N. Ochsner,et al.  A Meta-analysis of Functional Neuroimaging Studies of Self- and Other Judgments Reveals a Spatial Gradient for Mentalizing in Medial Prefrontal Cortex , 2012, Journal of Cognitive Neuroscience.

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

[81]  Zachary C. Irving,et al.  Mind-wandering as spontaneous thought: a dynamic framework , 2016, Nature Reviews Neuroscience.

[82]  Jeffrey S. Anderson,et al.  Connectivity Gradients Between the Default Mode and Attention Control Networks , 2011, Brain Connect..

[83]  Elizabeth Jefferies,et al.  Down but not out in posterior cingulate cortex: Deactivation yet functional coupling with prefrontal cortex during demanding semantic cognition , 2016, NeuroImage.

[84]  Evan M. Gordon,et al.  Long-term neural and physiological phenotyping of a single human , 2015, Nature Communications.

[85]  J. Duncan The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour , 2010, Trends in Cognitive Sciences.

[86]  Kieran C. R. Fox,et al.  Metacognitive Facilitation of Spontaneous Thought Processes: When Metacognition Helps the Wandering Mind Find Its Way , 2014 .

[87]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

[88]  John D. E. Gabrieli,et al.  Selective Development of Anticorrelated Networks in the Intrinsic Functional Organization of the Human Brain , 2014, Journal of Cognitive Neuroscience.

[89]  Linda Geerligs,et al.  State and Trait Components of Functional Connectivity: Individual Differences Vary with Mental State , 2015, The Journal of Neuroscience.

[90]  Justin L. Vincent,et al.  Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. , 2008, Journal of neurophysiology.

[91]  Todd W. Thompson,et al.  Resting-state anticorrelations between medial and lateral prefrontal cortex: Association with working memory, aging, and individual differences , 2014, Cortex.

[92]  M. Raichle The brain's default mode network. , 2015, Annual review of neuroscience.

[93]  Rebecca M. Todd,et al.  Dynamics of neural recruitment surrounding the spontaneous arising of thoughts in experienced mindfulness practitioners , 2016, NeuroImage.

[94]  E. Thompson,et al.  The Kantian brain: brain dynamics from a neurophenomenological perspective , 2015, Current Opinion in Neurobiology.

[95]  Jonathan D. Power,et al.  Prediction of Individual Brain Maturity Using fMRI , 2010, Science.

[96]  C. Pennartz,et al.  The Hippocampus Is Coupled with the Default Network during Memory Retrieval but Not during Memory Encoding , 2011, PloS one.

[97]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[98]  Dimitri Van De Ville,et al.  On spurious and real fluctuations of dynamic functional connectivity during rest , 2015, NeuroImage.

[99]  Kevin S. Brown,et al.  Cooperation between the default mode network and the frontal–parietal network in the production of an internal train of thought , 2012, Brain Research.

[100]  R. N. Spreng,et al.  The default network and self‐generated thought: component processes, dynamic control, and clinical relevance , 2014, Annals of the New York Academy of Sciences.

[101]  M. Hasselmo,et al.  High acetylcholine levels set circuit dynamics for attention and encoding and low acetylcholine levels set dynamics for consolidation. , 2004, Progress in brain research.

[102]  Bernard Ng,et al.  Identification of Mood-Relevant Brain Connections Using a Continuous, Subject-Driven Rumination Paradigm. , 2016, Cerebral cortex.

[103]  Marie Schaer,et al.  Degrees of separation: A quantitative neuroimaging meta-analysis investigating self-specificity and shared neural activation between self- and other-reflection , 2012, Neuroscience & Biobehavioral Reviews.

[104]  R. N. Spreng,et al.  Attenuated anticorrelation between the default and dorsal attention networks with aging: evidence from task and rest , 2016, Neurobiology of Aging.

[105]  Krzysztof J. Gorgolewski,et al.  The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance , 2015, Neuron.

[106]  P. Fransson Spontaneous low‐frequency BOLD signal fluctuations: An fMRI investigation of the resting‐state default mode of brain function hypothesis , 2005, Human brain mapping.

[107]  Michael W. Cole,et al.  Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration , 2016, The Journal of Neuroscience.

[108]  Thomas T. Liu,et al.  A component based noise correction method (CompCor) for BOLD and perfusion based fMRI , 2007, NeuroImage.

[109]  M. Chun,et al.  Interactions between attention and memory , 2007, Current Opinion in Neurobiology.

[110]  David C. Van Essen,et al.  A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex , 2005, NeuroImage.

[111]  Elliot T. Berkman,et al.  Evidence for social working memory from a parametric functional MRI study , 2012, Proceedings of the National Academy of Sciences.

[112]  R. Malach,et al.  Data-driven clustering reveals a fundamental subdivision of the human cortex into two global systems , 2008, Neuropsychologia.

[113]  E. Thompson,et al.  Specifying the self for cognitive neuroscience , 2011, Trends in Cognitive Sciences.

[114]  Kieran C. R. Fox,et al.  Evidence for rostro-caudal functional organization in multiple brain areas related to goal-directed behavior , 2014, Brain Research.

[115]  S. Gallagher Philosophical conceptions of the self: implications for cognitive science , 2000, Trends in Cognitive Sciences.

[116]  R. Buckner,et al.  Parcellating Cortical Functional Networks in Individuals , 2015, Nature Neuroscience.

[117]  Haakon G. Engen,et al.  Shaped by the Past: The Default Mode Network Supports Cognition that Is Independent of Immediate Perceptual Input , 2015, PloS one.

[118]  Steve Majerus,et al.  The Neural Basis of Personal Goal Processing When Envisioning Future Events , 2010, Journal of Cognitive Neuroscience.

[119]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[120]  Michael W. Cole,et al.  The Behavioral Relevance of Task Information in Human Prefrontal Cortex. , 2016, Cerebral cortex.

[121]  Marc Joliot,et al.  The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state , 2010, Brain Research Bulletin.

[122]  Matthew L. Dixon,et al.  The lateral prefrontal cortex and complex value-based learning and decision making , 2014, Neuroscience & Biobehavioral Reviews.

[123]  Danielle S. Bassett,et al.  Cognitive Network Neuroscience , 2015, Journal of Cognitive Neuroscience.

[124]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[125]  Danielle S. Bassett,et al.  Structurally-Constrained Relationships between Cognitive States in the Human Brain , 2014, PLoS Comput. Biol..

[126]  Kevin Murphy,et al.  The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced? , 2009, NeuroImage.

[127]  Wen-Ming Luh,et al.  Goal-Congruent Default Network Activity Facilitates Cognitive Control , 2014, The Journal of Neuroscience.

[128]  F. Castellanos,et al.  Spontaneous attentional fluctuations in impaired states and pathological conditions: A neurobiological hypothesis , 2007, Neuroscience & Biobehavioral Reviews.

[129]  K. Christoff,et al.  Experience sampling during fMRI reveals default network and executive system contributions to mind wandering , 2009, Proceedings of the National Academy of Sciences.

[130]  Markus Hofmann,et al.  RapidMiner: Data Mining Use Cases and Business Analytics Applications , 2013 .

[131]  Carl D. Hacker,et al.  Clustering of Resting State Networks , 2012, PloS one.

[132]  R. Poldrack,et al.  Temporal metastates are associated with differential patterns of time-resolved connectivity, network topology, and attention , 2016, Proceedings of the National Academy of Sciences.

[133]  Dost Öngür,et al.  Anticorrelations in resting state networks without global signal regression , 2012, NeuroImage.

[134]  Rebecca Saxe,et al.  Contributions of episodic retrieval and mentalizing to autobiographical thought: Evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses , 2014, NeuroImage.

[135]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[136]  D. V. van Essen,et al.  A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex. , 2005, NeuroImage.

[137]  Kristina M. Visscher,et al.  A Core System for the Implementation of Task Sets , 2006, Neuron.

[138]  Eswar Damaraju,et al.  Tracking whole-brain connectivity dynamics in the resting state. , 2014, Cerebral cortex.

[139]  Wei Gao,et al.  Frontal parietal control network regulates the anti‐correlated default and dorsal attention networks , 2012, Human brain mapping.

[140]  Douglas M. Bates,et al.  Nonlinear Mixed-Effects Models: Basic Concepts and Motivating Examples , 2000 .

[141]  M. Corbetta,et al.  Common Blood Flow Changes across Visual Tasks: II. Decreases in Cerebral Cortex , 1997, Journal of Cognitive Neuroscience.

[142]  Cheryl L. Grady,et al.  Age differences in the neural correlates of distraction regulation: A network interaction approach , 2016, NeuroImage.

[143]  R. Marois,et al.  Capacity limits of information processing in the brain , 2005, Trends in Cognitive Sciences.

[144]  Rodrigo M. Braga,et al.  Echoes of the Brain within the Posterior Cingulate Cortex , 2012, The Journal of Neuroscience.

[145]  Michael J. Hove,et al.  Dynamic Brain Network Correlates of Spontaneous Fluctuations in Attention , 2016, Cerebral cortex.

[146]  Bernard Mazoyer,et al.  Patterns of hemodynamic low-frequency oscillations in the brain are modulated by the nature of free thought during rest , 2012, NeuroImage.

[147]  M. Masson,et al.  Using confidence intervals in within-subject designs , 1994, Psychonomic bulletin & review.

[148]  Howard Bowman,et al.  I Tried a Bunch of Things: The Dangers of Unexpected Overfitting in Classification , 2016, bioRxiv.