Age-related differences in functional brain network segregation are consistent with a cascade of cerebrovascular, structural, and cognitive effects

Abstract Age-related declines in cognition are associated with widespread structural and functional brain changes, including changes in resting-state functional connectivity and gray and white matter status. Recently we have shown that the elasticity of cerebral arteries also explains some of the variance in cognitive and brain health in aging. Here, we investigated how network segregation, cerebral arterial elasticity (measured with pulse-DOT—the arterial pulse based on diffuse optical tomography) and gray and white matter status jointly account for age-related differences in cognitive performance. We hypothesized that at least some of the variance in brain and cognitive aging is linked to reduced cerebrovascular elasticity, leading to increased cortical atrophy and white matter abnormalities, which, in turn, are linked to reduced network segregation and decreases in cognitive performance. Pairwise comparisons between these variables are consistent with an exploratory hierarchical model linking them, especially when focusing on association network segregation (compared with segregation in sensorimotor networks). These findings suggest that preventing or slowing age-related changes in one or more of these factors may induce a neurophysiological cascade beneficial for preserving cognition in aging.

[1]  Monica Fabiani,et al.  Mapping cerebral pulse pressure and arterial compliance over the adult lifespan with optical imaging , 2017, PloS one.

[2]  Benjamin S. Aribisala,et al.  White matter hyperintensities and normal-appearing white matter integrity in the aging brain , 2015, Neurobiology of Aging.

[3]  Gagan S Wig,et al.  Functional Parcellation of the Cerebral Cortex Across the Human Adult Lifespan , 2018, Cerebral cortex.

[4]  Justin L. Vincent,et al.  Disruption of Large-Scale Brain Systems in Advanced Aging , 2007, Neuron.

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

[6]  J. Raven,et al.  Manual for Raven's progressive matrices and Mill Hill vocabulary scales , 1981 .

[7]  Kathleen Veizel,et al.  Wechsler Memory Scale–Fourth Edition , 2014 .

[8]  P. Baltes,et al.  Emergence of a powerful connection between sensory and cognitive functions across the adult life span: a new window to the study of cognitive aging? , 1997, Psychology and aging.

[9]  David Wechsler,et al.  Wechsler Memory scale. , 2005 .

[10]  A. Dale,et al.  Whole Brain Segmentation Automated Labeling of Neuroanatomical Structures in the Human Brain , 2002, Neuron.

[11]  Gabriele Gratton,et al.  Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data , 2016, Journal of biomedical optics.

[12]  R. Bonser,et al.  Cerebral perfusion. , 2007, The Annals of thoracic surgery.

[13]  C. Lebel,et al.  White Matter Structural Connectivity Is Not Correlated to Cortical Resting-State Functional Connectivity over the Healthy Adult Lifespan , 2017, Front. Aging Neurosci..

[14]  David H. Salat,et al.  Regional staging of white matter signal abnormalities in aging and Alzheimer's disease , 2017, NeuroImage: Clinical.

[15]  Gabriele Gratton,et al.  Individual differences in regional cortical volumes across the life span are associated with regional optical measures of arterial elasticity , 2017, NeuroImage.

[16]  Scott B. MacKenzie,et al.  Sources of method bias in social science research and recommendations on how to control it. , 2012, Annual review of psychology.

[17]  Nyaz Didehbani,et al.  Modular Brain Network Organization Predicts Response to Cognitive Training in Older Adults , 2016, PloS one.

[18]  Monica Fabiani,et al.  Neuroanatomical correlates of aging, cardiopulmonary fitness level, and education. , 2008, Psychophysiology.

[19]  Anders M. Dale,et al.  Correction of respiratory artifacts in MRI head motion estimates , 2018, bioRxiv.

[20]  R. Marshall,et al.  Altered cerebral hemodyamics and cortical thinning in asymptomatic carotid artery stenosis , 2017, PloS one.

[21]  Frini Karayanidis,et al.  Microstructural white matter changes mediate age-related cognitive decline on the Montreal Cognitive Assessment (MoCA). , 2016, Psychophysiology.

[22]  E. McAuley,et al.  Frontiers in Aging Neuroscience Aging Neuroscience , 2022 .

[23]  J. C. Torre.  Cardiovascular Risk Factors Promote Brain Hypoperfusion Leading to Cognitive Decline and Dementia , 2012 .

[24]  Victoria J. Williams,et al.  Cardiorespiratory fitness is differentially associated with cortical thickness in young and older adults , 2017, NeuroImage.

[25]  Karl J. Friston,et al.  Movement‐Related effects in fMRI time‐series , 1996, Magnetic resonance in medicine.

[26]  Monica Fabiani,et al.  Does White Matter Matter? Spatio-temporal Dynamics of Task Switching in Aging , 2009, Journal of Cognitive Neuroscience.

[27]  G. Gratton,et al.  The effects of cardiorespiratory fitness on brain and cognitive aging , 2021 .

[28]  J. Raven,et al.  Manual for Raven's progressive matrices and vocabulary scales , 1962 .

[29]  Sang Won Seo,et al.  Combined effects of physical exercise and education on age-related cortical thinning in cognitively normal individuals , 2016, Scientific Reports.

[30]  L. Fried,et al.  Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The Cardiovascular Health Study. , 1996, Stroke.

[31]  Eric E. Smith,et al.  Reduced Blood Flow in Normal White Matter Predicts Development of Leukoaraiosis , 2015, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[32]  A. Alkerwi,et al.  Cardiovascular Health and Cognitive Function: The Maine-Syracuse Longitudinal Study , 2014, PloS one.

[33]  S. Rombouts,et al.  Reduced resting-state brain activity in the "default network" in normal aging. , 2008, Cerebral cortex.

[34]  G. Busatto,et al.  Resting-state functional connectivity in normal brain aging , 2013, Neuroscience & Biobehavioral Reviews.

[35]  Kathy A. Low,et al.  Comparing Aging and Fitness Effects on Brain Anatomy , 2016, Front. Hum. Neurosci..

[36]  Abraham Z. Snyder,et al.  Emergent Functional Network Effects in Parkinson Disease. , 2019, Cerebral cortex.

[37]  J. Pillai.  Functional Connectivity. , 2017, Neuroimaging clinics of North America.

[38]  E Rostrup,et al.  Cerebral Perfusion and Cerebrovascular Reactivity Are Reduced in White Matter Hyperintensities , 2002, Stroke.

[39]  M. Fabiani.  It was the best of times, it was the worst of times: a psychophysiologist's view of cognitive aging. , 2012, Psychophysiology.

[40]  Nico Bunzeck,et al.  Reward Dependent Invigoration Relates to Theta Oscillations and Is Predicted by Dopaminergic Midbrain Integrity in Healthy Elderly , 2017, Front. Aging Neurosci..

[41]  Bradford C. Dickerson,et al.  The personalized Alzheimer's disease cortical thickness index predicts likely pathology and clinical progression in mild cognitive impairment , 2018, Alzheimer's & dementia.

[42]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[43]  Richard P. Heitz,et al.  An automated version of the operation span task , 2005, Behavior research methods.

[44]  Monica Fabiani,et al.  A kurtosis-based wavelet algorithm for motion artifact correction of fNIRS data , 2015, NeuroImage.

[45]  R. Mayeux,et al.  Depression, intellectual impairment, and Parkinson disease , 1981, Neurology.

[46]  A Hofman,et al.  Cerebral white matter lesions and atherosclerosis in the Rotterdam Study , 1993, The Lancet.

[47]  R. Hoge,et al.  The adverse effects of reduced cerebral perfusion on cognition and brain structure in older adults with cardiovascular disease , 2013, Brain and behavior.

[48]  Claudia L. Satizabal,et al.  Effects of Arterial Stiffness on Brain Integrity in Young Adults From the Framingham Heart Study , 2016, Stroke.

[49]  Carlo R. Laing,et al.  Taking the Pulse , 2014 .

[50]  Denise C. Park,et al.  Decreased segregation of brain systems across the healthy adult lifespan , 2014, Proceedings of the National Academy of Sciences.

[51]  K. Paulsen,et al.  Spatially varying optical property reconstruction using a finite element diffusion equation approximation. , 1995, Medical physics.

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

[53]  Sara M. Santos,et al.  Amidated and Ibuprofen-Conjugated Kyotorphins Promote Neuronal Rescue and Memory Recovery in Cerebral Hypoperfusion Dementia Model , 2016, Front. Aging Neurosci..

[54]  J. Haxby,et al.  The effect of white matter hyperintensity volume on brain structure, cognitive performance, and cerebral metabolism of glucose in 51 healthy adults , 1995, Neurology.

[55]  L J Whalley,et al.  Neuropsychologic correlates of brain white matter lesions depicted on MR images: 1921 Aberdeen Birth Cohort. , 2001, Radiology.

[56]  R. C. Oldfield.  The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[57]  H. Praag,et al.  Bridging animal and human models of exercise-induced brain plasticity , 2013, Trends in Cognitive Sciences.

[58]  Charles DeCarli,et al.  White matter hyperintensities and cognition: Testing the reserve hypothesis , 2011, Neurobiology of Aging.

[59]  Paige E. Scalf,et al.  Cardiovascular fitness, cortical plasticity, and aging. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[60]  J. Barnes.  Exercise, cognitive function, and aging. , 2015, Advances in physiology education.

[61]  J. Corrigan,et al.  Relationships between parts A and B of the Trail Making Test. , 1987, Journal of clinical psychology.

[62]  Richard F. Betzel,et al.  Modular Brain Networks. , 2016, Annual review of psychology.

[63]  Ulman Lindenberger,et al.  Trajectories of brain aging in middle-aged and older adults: Regional and individual differences , 2010, NeuroImage.

[64]  Y. Chagnon,et al.  GENETIC AND EPIGENETIC BLOOD SIGNATURE OF MILD COGNITIVE IMPAIRMENT IN PRODROMAL ALZHEIMER'S DISEASE , 2014, Alzheimer's & Dementia.

[65]  D. Webb,et al.  Noninvasive assessment of arterial stiffness and risk of atherosclerotic events. , 2003, Arteriosclerosis, thrombosis, and vascular biology.

[66]  P. Baltes,et al.  Intellectual functioning in old and very old age: cross-sectional results from the Berlin Aging Study. , 1997, Psychology and aging.

[67]  Jonathan D. Power,et al.  Studying Brain Organization via Spontaneous fMRI Signal , 2014, Neuron.

[68]  Mukhlesur Rahman,et al.  Noninvasive Assessment of Arterial Stiffness and Risk of Coronary Artery Disease , 2012 .

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

[70]  Yike Guo,et al.  Inferring Individual-Level Variations in the Functional Parcellation of the Cerebral Cortex , 2016, IEEE Trans. Biomed. Eng..

[71]  Abraham Z. Snyder,et al.  A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume , 2004, NeuroImage.

[72]  Timothy O. Laumann,et al.  Methods to detect, characterize, and remove motion artifact in resting state fMRI , 2014, NeuroImage.

[73]  O. Faergeman,et al.  Cardiovascular Health , 2018, Pediatric Clinical Practice Guidelines & Policies.

[74]  R. C. Oldfield.  THE ASSESSMENT AND ANALYSIS OF HANDEDNESS , 1971 .

[75]  R. Killiany,et al.  Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults , 2011, Neurology.

[76]  A. Pfefferbaum,et al.  Diffusion tensor imaging and aging , 2006, Neuroscience & Biobehavioral Reviews.

[77]  M. Filippi,et al.  Cardiovascular disease and brain health: Focus on white matter hyperintensities , 2018, International journal of cardiology. Heart & vasculature.

[78]  Iaira Boissevain,et al.  Implications of Research for Treatment: Ghb Latest Research Findings Adverse Effects , 2022 .

[79]  Monica Fabiani,et al.  Taking the pulse of aging: mapping pulse pressure and elasticity in cerebral arteries with optical methods. , 2014, Psychophysiology.

[80]  P. Wolf,et al.  Serum Brain–Derived Neurotrophic Factor and Vascular Endothelial Growth Factor Levels Are Associated With Risk of Stroke and Vascular Brain Injury: Framingham Study , 2013, Stroke.

[81]  Monica Fabiani,et al.  Optical measures of changes in cerebral vascular tone during voluntary breath holding and a Sternberg memory task , 2016, Biological Psychology.

[82]  V. Nikulin,et al.  Pre-stimulus Alpha Oscillations and Inter-subject Variability of Motor Evoked Potentials in Single- and Paired-Pulse TMS Paradigms , 2016, Front. Hum. Neurosci..

[83]  W. C. Shipley.  A Self-Administering Scale for Measuring Intellectual Impairment and Deterioration , 1940 .

[84]  Timothy J. Hohman,et al.  The role of vascular endothelial growth factor in neurodegeneration and cognitive decline: exploring interactions with biomarkers of Alzheimer disease. , 2015, JAMA neurology.

[85]  A Ishimaru,et al.  Diffusion of light in turbid material. , 1989, Applied optics.

[86]  P. Sachdev,et al.  Therapeutically relevant structural and functional mechanisms triggered by physical and cognitive exercise , 2016, Molecular psychiatry.

[87]  Patrick S. Cooper,et al.  Age‐related decline in task switching is linked to both global and tract‐specific changes in white matter microstructure , 2017, Human brain mapping.

[88]  Reisa A. Sperling,et al.  Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults , 2015, Brain Connect..

[89]  Akram Bakkour,et al.  The cortical signature of prodromal AD , 2009, Neurology.

[90]  Aaron Carass,et al.  Longitudinal changes in cortical thickness associated with normal aging , 2010, NeuroImage.

[91]  Notger G. Müller,et al.  Relationships of peripheral IGF-1, VEGF and BDNF levels to exercise-related changes in memory, hippocampal perfusion and volumes in older adults , 2016, NeuroImage.

[92]  Brian B. Avants,et al.  White matter hyperintensities are more highly associated with preclinical Alzheimer's disease than imaging and cognitive markers of neurodegeneration , 2016, Alzheimer's & dementia.

[93]  U. Lindenberger,et al.  Frontiers in Aging Neuroscience Aging Neuroscience Hundred Days of Cognitive Training Enhance Broad Cognitive Abilities in Adulthood: Findings from the Cogito Study Materials and Methods Participants and Procedure , 2022 .

[94]  H. Vrenken,et al.  White Matter Hyperintensity Volume and Cerebral Perfusion in Older Individuals with Hypertension Using Arterial Spin-Labeling , 2016, American Journal of Neuroradiology.

[95]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[96]  Richard Restak,et al.  The modular brain , 1994 .

[97]  Susan M. Resnick,et al.  Greater cortical thinning in normal older adults predicts later cognitive impairment , 2015, Neurobiology of Aging.

[98]  Chu-Chung Huang,et al.  The Association of Aging with White Matter Integrity and Functional Connectivity Hubs , 2016, Front. Aging Neurosci..

[99]  Akram Bakkour,et al.  The cortical signature of prodromal AD Regional thinning predicts mild AD dementia , 2009 .

[100]  Arthur F. Kramer,et al.  Brain Network Modularity Predicts Exercise-Related Executive Function Gains in Older Adults , 2018, Front. Aging Neurosci..

[101]  A. Dale,et al.  Thinning of the cerebral cortex in aging. , 2004, Cerebral cortex.

[102]  Kathy A. Low,et al.  Optical measures of cerebral arterial stiffness are associated with white matter signal abnormalities and cognitive performance in normal aging , 2019, Neurobiology of Aging.

[103]  Joaquín Goñi,et al.  Changes in structural and functional connectivity among resting-state networks across the human lifespan , 2014, NeuroImage.

[104]  J. Cohen‐Adad,et al.  Arterial stiffness and brain integrity: A review of MRI findings , 2019, Ageing Research Reviews.

[105]  N. Maurits,et al.  A Brain-Wide Study of Age-Related Changes in Functional Connectivity. , 2015, Cerebral cortex.

[106]  Timothy O. Laumann,et al.  Functional Brain Networks Are Dominated by Stable Group and Individual Factors, Not Cognitive or Daily Variation , 2018, Neuron.

[107]  W. Koenig,et al.  Noninvasive assessment of arterial stiffness and risk of atherosclerotic events , 2006 .

[108]  Arthur F. Kramer,et al.  Neurobiological markers of exercise-related brain plasticity in older adults , 2013, Brain, Behavior, and Immunity.

[109]  A. Kramer,et al.  Exercise, brain, and cognition across the life span. , 2011, Journal of applied physiology.