Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI

Normal aging is accompanied by various cognitive functional declines. Recent studies have revealed disruptions in the coordination of large-scale functional brain networks such as the default mode network in advanced aging. However, organizational alterations of the structural brain network at the system level in aging are still poorly understood. Here, using cortical thickness, we investigated the modular organization of the cortical structural networks in 102 young and 97 normal aging adults. Brain networks for both cohorts displayed a modular organization overlapping with functional domains such as executive and auditory/language processing. However, compared with the modular organization of young adults, the aging group demonstrated a significantly reduced modularity that might be indicative of reduced functional segregation in the aging brain. More importantly, the aging brain network exhibited reduced intra-/inter-module connectivity in modules corresponding to the executive function and the default mode network of young adults, which might be associated with the decline of cognitive functions in aging. Finally, we observed age-associated alterations in the regional characterization in terms of their intra/inter-module connectivity. Our results indicate that aging is associated with an altered modular organization in the structural brain networks and provide new evidence for disrupted integrity in the large-scale brain networks that underlie cognition.

[1]  Yong He,et al.  Age-related changes in topological patterns of large-scale brain functional networks during memory encoding and recognition , 2010, NeuroImage.

[2]  J. Price,et al.  Mild cognitive impairment represents early-stage Alzheimer disease. , 2001, Archives of neurology.

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

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

[5]  S. Fortunato,et al.  Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.

[6]  Edward T. Bullmore,et al.  Age-related changes in modular organization of human brain functional networks , 2009, NeuroImage.

[7]  Hod Lipson,et al.  Networks, dynamics, and modularity. , 2004, Physical review letters.

[8]  M. Carulla,et al.  Transforming growth factor-α immunoreactivity in the developing and adult brain , 1995, Neuroscience.

[9]  Roberto Cabeza,et al.  Adult Age Differences in Functional Connectivity during Executive Control Nih Public Access Materials and Methods Cue-related Activation Functional Connectivity of Switch-related Activation on Cue-only Trials , 2022 .

[10]  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.

[11]  John A. E. Anderson,et al.  A multivariate analysis of age-related differences in default mode and task-positive networks across multiple cognitive domains. , 2010, Cerebral cortex.

[12]  Thomas E. Nichols,et al.  Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.

[13]  S. Black,et al.  Evidence from Functional Neuroimaging of a Compensatory Prefrontal Network in Alzheimer's Disease , 2003, The Journal of Neuroscience.

[14]  Roberto Cabeza,et al.  Assessing the effects of age on long white matter tracts using diffusion tensor tractography , 2009, NeuroImage.

[15]  Denise C. Park,et al.  The adaptive brain: aging and neurocognitive scaffolding. , 2009, Annual review of psychology.

[16]  Martin Suter,et al.  Small World , 2002 .

[17]  Klaas E. Stephan,et al.  Network participation indices: characterizing component roles for information processing in neural networks , 2003, Neural Networks.

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

[19]  M. Corbetta,et al.  Top-down modulation of early sensory cortex. , 1997 .

[20]  J. Morris.  The Clinical Dementia Rating (CDR) , 1993, Neurology.

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

[22]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[23]  Roberto Cabeza,et al.  Aging Gracefully: Compensatory Brain Activity in High-Performing Older Adults , 2002, NeuroImage.

[24]  Suzanne E. Welcome,et al.  Mapping cortical change across the human life span , 2003, Nature Neuroscience.

[25]  John G. Csernansky,et al.  Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults , 2007, Journal of Cognitive Neuroscience.

[26]  M P Young,et al.  Hierarchical organization of macaque and cat cortical sensory systems explored with a novel network processor. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[27]  Alan C. Evans,et al.  Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification , 2005, NeuroImage.

[28]  B. Miller,et al.  Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.

[29]  Liang Wang,et al.  Parcellation‐dependent small‐world brain functional networks: A resting‐state fMRI study , 2009, Human brain mapping.

[30]  Yong He,et al.  Changing topological patterns in normal aging using large-scale structural networks , 2012, Neurobiology of Aging.

[31]  Rodrigo Quian Quiroga,et al.  Selectivity and invariance for visual object perception. , 2008, Frontiers in bioscience : a journal and virtual library.

[32]  E. Bullmore,et al.  Neurophysiological architecture of functional magnetic resonance images of human brain. , 2005, Cerebral cortex.

[33]  D. Collins,et al.  Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space , 1994, Journal of computer assisted tomography.

[34]  S. Rombouts,et al.  Hierarchical functional modularity in the resting‐state human brain , 2009, Human brain mapping.

[35]  I Ferrer,et al.  Transforming growth factor-alpha immunoreactivity in the developing and adult brain. , 1995, Neuroscience.

[36]  A. Dale,et al.  Age-related alterations in white matter microstructure measured by diffusion tensor imaging , 2005, Neurobiology of Aging.

[37]  A. Dale,et al.  High consistency of regional cortical thinning in aging across multiple samples. , 2009, Cerebral cortex.

[38]  M. O’Sullivan,et al.  Activate your online subscription , 2001, Neurology.

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

[40]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[41]  R. Cabeza.  Hemispheric asymmetry reduction in older adults: the HAROLD model. , 2002, Psychology and aging.

[42]  Alan C. Evans,et al.  Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. , 2007, Cerebral cortex.

[43]  D. Louis Collins,et al.  Tuning and Comparing Spatial Normalization Methods , 2003, MICCAI.

[44]  K. Grill-Spector.  The neural basis of object perception , 2003, Current Opinion in Neurobiology.

[45]  U. Alon,et al.  Spontaneous evolution of modularity and network motifs. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[46]  Alan C. Evans,et al.  Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[47]  Meng Li,et al.  Gender consistency and difference in healthy adults revealed by cortical thickness , 2010, NeuroImage.

[48]  Anthony Randal McIntosh,et al.  Age-related Changes in Brain Activity across the Adult Lifespan , 2006, Journal of Cognitive Neuroscience.

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

[50]  Alan C. Evans,et al.  Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans , 2009, PloS one.

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

[52]  Karl J. Friston,et al.  Structural Covariance in the Human Cortex , 2005, The Journal of Neuroscience.

[53]  M. Newman.  Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[54]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[55]  Tyrone D. Cannon,et al.  Genetic influences on brain structure , 2001, Nature Neuroscience.

[56]  O. Sporns,et al.  Organization, development and function of complex brain networks , 2004, Trends in Cognitive Sciences.

[57]  Changsong Zhou,et al.  Hierarchical organization unveiled by functional connectivity in complex brain networks. , 2006, Physical review letters.

[58]  M. A. O'Neil,et al.  The connectional organization of the cortico-thalamic system of the cat. , 1999, Cerebral cortex.

[59]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[60]  R. Guimerà,et al.  The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[61]  J Martinerie,et al.  Complex modular structure of large-scale brain networks. , 2009, Chaos.

[62]  Roger Guimerà,et al.  Extracting the hierarchical organization of complex systems , 2007, Proceedings of the National Academy of Sciences.

[63]  D. Weinberger,et al.  Anatomical abnormalities in the brains of monozygotic twins discordant for schizophrenia. , 1990, The New England journal of medicine.

[64]  Alan C. Evans,et al.  Cortical thickness analysis examined through power analysis and a population simulation , 2005, NeuroImage.

[65]  D. Louis Collins,et al.  Automatic 3‐D model‐based neuroanatomical segmentation , 1995 .

[66]  Leon Danon,et al.  The effect of size heterogeneity on community identification in complex networks , 2006, physics/0601144.

[67]  Alan C. Evans,et al.  Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. , 2009, Cerebral cortex.

[68]  Alan C. Evans,et al.  Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.

[69]  J. Morris,et al.  Functional deactivations: Change with age and dementia of the Alzheimer type , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[70]  J. Duncan,et al.  Common regions of the human frontal lobe recruited by diverse cognitive demands , 2000, Trends in Neurosciences.

[71]  John Suckling,et al.  Global, voxel, and cluster tests, by theory and permutation, for a difference between two groups of structural MR images of the brain , 1999, IEEE Transactions on Medical Imaging.

[72]  P. Reuter-Lorenz,et al.  Neurocognitive Aging and the Compensation Hypothesis , 2008 .

[73]  Roger Guimerà,et al.  Cartography of complex networks: modules and universal roles , 2005, Journal of statistical mechanics.

[74]  Edward T. Bullmore,et al.  Efficiency and Cost of Economical Brain Functional Networks , 2007, PLoS Comput. Biol..

[75]  P. Pietrini,et al.  Altered brain functional connectivity and impaired short-term memory in Alzheimer's disease. , 2001, Brain : a journal of neurology.

[76]  Anthony R. McIntosh,et al.  Age-related Changes in Brain Activity across the Adult Lifespan , 2006 .

[77]  M P Young,et al.  Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[78]  Abraham Z. Snyder,et al.  A default mode of brain function: A brief history of an evolving idea , 2007, NeuroImage.

[79]  D. Drachman.  Aging of the brain, entropy, and Alzheimer disease , 2006, Neurology.

[80]  R. Guimerà,et al.  Functional cartography of complex metabolic networks , 2005, Nature.

[81]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[82]  Alan C. Evans,et al.  Revealing modular architecture of human brain structural networks by using cortical thickness from MRI. , 2008, Cerebral cortex.

[83]  P. Greenwood.  Functional plasticity in cognitive aging: review and hypothesis. , 2007, Neuropsychology.

[84]  G Tononi,et al.  Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. , 2000, Cerebral cortex.

[85]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[86]  Alan C. Evans,et al.  Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis , 2002, IEEE Transactions on Medical Imaging.

[87]  M M Mesulam,et al.  Large‐scale neurocognitive networks and distributed processing for attention, language, and memory , 1990, Annals of neurology.

[88]  Jacob Cohen,et al.  Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .

[89]  R. Buckner.  Memory and Executive Function in Aging and AD Multiple Factors that Cause Decline and Reserve Factors that Compensate , 2004, Neuron.