Structural core of the executive control network: A high angular resolution diffusion MRI study

Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high‐angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly‐connected “structural core” of the ECN comprising three components: interhemispheric frontal connections, a fronto‐parietal subnetwork and fronto‐striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post‐hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.

[1]  Jan Sijbers,et al.  Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data , 2014, NeuroImage.

[2]  Andrea Amerio,et al.  Cognitive Impairment in Bipolar Disorder and Schizophrenia: A Systematic Review , 2013, Front. Psychiatry.

[3]  Stefan Skare,et al.  How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging , 2003, NeuroImage.

[4]  Matthew J. Middione,et al.  Revealing the Hippocampal Connectome through Super-Resolution 1150-Direction Diffusion MRI , 2019, Scientific Reports.

[5]  Stamatios N. Sotiropoulos,et al.  An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging , 2016, NeuroImage.

[6]  Alexander Leemans,et al.  The B‐matrix must be rotated when correcting for subject motion in DTI data , 2009, Magnetic resonance in medicine.

[7]  P. Fox,et al.  Identification of a common neurobiological substrate for mental illness. , 2015, JAMA psychiatry.

[8]  Mark D'Esposito,et al.  Reconfiguration of brain network architecture to support executive control in aging , 2016, Neurobiology of Aging.

[9]  Maria Casagrande,et al.  Executive Functions in Alzheimer Disease: A Systematic Review , 2019, Front. Aging Neurosci..

[10]  L. Jäncke,et al.  Brain size, sex, and the aging brain , 2015, Human brain mapping.

[11]  Alan Connelly,et al.  Anatomically-constrained tractography: Improved diffusion MRI streamlines tractography through effective use of anatomical information , 2012, NeuroImage.

[12]  Pablo Villoslada,et al.  Reproducibility of the Structural Connectome Reconstruction across Diffusion Methods , 2016, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[13]  Hannah R. Snyder Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. , 2013, Psychological bulletin.

[14]  Edward T. Bullmore,et al.  Network-based statistic: Identifying differences in brain networks , 2010, NeuroImage.

[15]  E. Gordon,et al.  Development and validation of a World-Wide-Web-based neurocognitive assessment battery: WebNeuro , 2007, Behavior research methods.

[16]  Vince D. Calhoun,et al.  Measuring brain connectivity: Diffusion tensor imaging validates resting state temporal correlations , 2008, NeuroImage.

[17]  K. Luan Phan,et al.  A functional neuroimaging study of motivation and executive function , 2004, NeuroImage.

[18]  Lutz Jäncke,et al.  The hypothesis of neuronal interconnectivity as a function of brain size—a general organization principle of the human connectome , 2014, Front. Hum. Neurosci..

[19]  Bruce Fischl,et al.  FreeSurfer , 2012, NeuroImage.

[20]  B. Luo,et al.  Relationship between white matter integrity and post-traumatic cognitive deficits: a systematic review and meta-analysis , 2018, Journal of Neurology, Neurosurgery, and Psychiatry.

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

[22]  M. Banich,et al.  Neuroanatomical Correlates of the Unity and Diversity Model of Executive Function in Young Adults , 2018, Front. Hum. Neurosci..

[23]  Kimberly L. Ray,et al.  Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions , 2012, Cognitive, affective & behavioral neuroscience.

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

[25]  Ricardo Tarrasch,et al.  White matter correlates of cognitive domains in normal aging with diffusion tensor imaging , 2013, Front. Neurosci..

[26]  Alan Connelly,et al.  MRtrix: Diffusion tractography in crossing fiber regions , 2012, Int. J. Imaging Syst. Technol..

[27]  Stephen M. Smith,et al.  Investigations into resting-state connectivity using independent component analysis , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[28]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[29]  E. Gordon,et al.  THE TEST-RETEST RELIABILITY OF A STANDARDIZED NEUROCOGNITIVE AND NEUROPHYSIOLOGICAL TEST BATTERY: “NEUROMARKER” , 2005, The International journal of neuroscience.

[30]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[31]  M. Petrides,et al.  Wisconsin Card Sorting Revisited: Distinct Neural Circuits Participating in Different Stages of the Task Identified by Event-Related Functional Magnetic Resonance Imaging , 2001, The Journal of Neuroscience.

[32]  M. Greicius,et al.  Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity , 2009, Brain Structure and Function.

[33]  Yu Zhang,et al.  The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture , 2016, Cerebral cortex.

[34]  Marie T Banich,et al.  Functional connectivity at rest is sensitive to individual differences in executive function: A network analysis , 2016, Human brain mapping.

[35]  Michael D. Greicius,et al.  Distinct Cerebellar Contributions to Intrinsic Connectivity Networks , 2009, NeuroImage.

[36]  J. Cummings,et al.  Frontal-subcortical neuronal circuits and clinical neuropsychiatry: an update. , 2002, Journal of psychosomatic research.

[37]  Lutz Jäncke,et al.  Longitudinal reliability of tract‐based spatial statistics in diffusion tensor imaging , 2014, Human brain mapping.

[38]  Joshua W. Brown,et al.  A meta-analysis of executive components of working memory. , 2013, Cerebral cortex.

[39]  O Sporns,et al.  Predicting human resting-state functional connectivity from structural connectivity , 2009, Proceedings of the National Academy of Sciences.

[40]  Christine M. Walsh,et al.  Neuroanatomical substrates of executive functions: Beyond prefrontal structures , 2016, Neuropsychologia.

[41]  E. Gordon,et al.  Cognitive aging, executive function, and fractional anisotropy: a diffusion tensor MR imaging study. , 2007, AJNR. American journal of neuroradiology.

[42]  G. Glover,et al.  Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control , 2007, The Journal of Neuroscience.

[43]  Alan Connelly,et al.  SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography , 2015, NeuroImage.

[44]  P. Hall,et al.  Executive Function in Adults With Type 2 Diabetes: A Meta-Analytic Review , 2015, Psychosomatic medicine.

[45]  Dardo Tomasi,et al.  Structural and functional connectivity of the precuneus and thalamus to the default mode network , 2017, Human brain mapping.

[46]  Thomas Welton,et al.  Toward personalised diffusion MRI in psychiatry: improved delineation of fibre bundles with the highest-ever angular resolution in vivo tractography , 2018, Translational Psychiatry.

[47]  S. Wisniewski,et al.  Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial , 2013, Trials.

[48]  B. Crosson,et al.  Bilateral basal ganglia activity in verbal working memory , 2013, Brain and Language.

[49]  Karl J. Friston,et al.  Structural and Functional Brain Networks: From Connections to Cognition , 2013, Science.

[50]  A. C. Jaschke,et al.  Cardiac disease and cognitive impairment: a systematic review , 2012, Heart.

[51]  Michele T. Diaz,et al.  Sources of disconnection in neurocognitive aging: cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume , 2017, Neurobiology of Aging.

[52]  Hidenao Fukuyama,et al.  The neural basis of executive function in working memory: an fMRI study based on individual differences , 2004, NeuroImage.

[53]  Joe McCarthy,et al.  An integrated approach , 2001 .

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

[55]  O. Sporns,et al.  Mapping the Structural Core of Human Cerebral Cortex , 2008, PLoS biology.

[56]  Joseph M. Orr,et al.  Individual differences in regional prefrontal gray matter morphometry and fractional anisotropy are associated with different constructs of executive function , 2014, Brain Structure and Function.

[57]  M. White,et al.  A Systematic Review and Meta-analysis of Executive Function Performance in Type 1 Diabetes Mellitus , 2017, Psychosomatic medicine.

[58]  C. Smart,et al.  White matter and its relationship with cognition in subjective cognitive decline , 2018, Alzheimer's & dementia.

[59]  Stephen M. Smith,et al.  A Bayesian model of shape and appearance for subcortical brain segmentation , 2011, NeuroImage.

[60]  A. Song,et al.  Cerebral White Matter Integrity and Cognitive Aging: Contributions from Diffusion Tensor Imaging , 2009, Neuropsychology Review.

[61]  Donald T. Stuss,et al.  Executive functions and the frontal lobes: a conceptual view , 2000, Psychological research.

[62]  M. J. Emerson,et al.  The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis , 2000, Cognitive Psychology.

[63]  W. Tseng,et al.  Different neural substrates for executive functions in youths with ADHD: a diffusion spectrum imaging tractography study , 2016, Psychological Medicine.

[64]  E. Gordon,et al.  PRELIMINARY VALIDITY OF “INTEGNEUROTM”: A NEW COMPUTERIZED BATTERY OF NEUROCOGNITIVE TESTS , 2005, The International journal of neuroscience.

[65]  Lao Juan,et al.  Development and Validation of a Scale for Measuring Instructors' Attitudes toward Concept-Based or Reform-Oriented Teaching of Introductory Statistics in the Health and Behavioral Sciences , 2010, 1007.3219.

[66]  Markus H. Sneve,et al.  The Disconnected Brain and Executive Function Decline in Aging , 2016, Cerebral cortex.