Targeting age‐related differences in brain and cognition with multimodal imaging and connectome topography profiling

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open‐access healthy cohort (n = 102, age range = 30–89 years) with MRI and Aβ PET data, we estimated age‐related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface‐based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting‐state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory‐motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long‐axis. While age‐related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher‐order transmodal regions. Age‐related atrophy was greater toward the posterior end of the hippocampal long‐axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography‐specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain‐based biomarkers of aging.

[1]  Boris C. Bernhardt,et al.  Targeting Age-Related Differences in Brain and Cognition with Multimodal Imaging and Connectome Topography Profiling , 2019, bioRxiv.

[2]  Denise C. Park,et al.  Actual memory as a mediator of the amyloid-subjective cognitive decline relationship , 2019, Alzheimer's & dementia.

[3]  Katrin Amunts,et al.  Multimodal Parcellations and Extensive Behavioral Profiling Tackling the Hippocampus Gradient. , 2019, Cerebral cortex.

[4]  Serge A. R. B. Rombouts,et al.  Aberrant memory system connectivity and working memory performance in subjective cognitive decline , 2019, NeuroImage.

[5]  John A. E. Anderson,et al.  Intrinsic neurocognitive network connectivity differences between normal aging and mild cognitive impairment are associated with cognitive status and age , 2019, Neurobiology of Aging.

[6]  Alan C. Evans,et al.  Microstructural and functional gradients are increasingly dissociated in transmodal cortices , 2019, PLoS biology.

[7]  Raymond P. Viviano,et al.  Subjective Cognitive Decline Is Associated with Greater White Matter Hyperintensity Volume , 2018, Journal of Alzheimer's disease : JAD.

[8]  B. Yeo,et al.  Imaging-based parcellations of the human brain , 2018, Nature Reviews Neuroscience.

[9]  Reinder Vos de Wael,et al.  Anatomical and microstructural determinants of hippocampal subfield functional connectome embedding , 2018, Proceedings of the National Academy of Sciences.

[10]  L. Ferrucci,et al.  Effects of amyloid pathology and neurodegeneration on cognitive change in cognitively normal adults , 2018, Brain : a journal of neurology.

[11]  Ming-Jang Chiu,et al.  Diminution of context association memory structure in subjects with subjective cognitive decline , 2018, Human brain mapping.

[12]  Reinder Vos de Wael,et al.  Atypical functional connectome hierarchy in autism , 2018, Nature Communications.

[13]  Hao-Ting Wang,et al.  Distant from input: Evidence of regions within the default mode network supporting perceptually-decoupled and conceptually-guided cognition , 2018, NeuroImage.

[14]  David T. Jones,et al.  Joint associations of β-amyloidosis and cortical thickness with cognition , 2018, Neurobiology of Aging.

[15]  A. Herlitz,et al.  Structural whole‐brain covariance of the anterior and posterior hippocampus: Associations with age and memory , 2018, Hippocampus.

[16]  W. M. van der Flier,et al.  Subjective Cognitive Decline Is Associated With Altered Default Mode Network Connectivity in Individuals With a Family History of Alzheimer's Disease. , 2017, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[17]  Sahil Bajaj,et al.  Brain Aging: Uncovering Cortical Characteristics of Healthy Aging in Young Adults , 2017, Front. Aging Neurosci..

[18]  D. Louis Collins,et al.  A clinical-anatomical signature of Parkinson's disease identified with partial least squares and magnetic resonance imaging , 2017, NeuroImage.

[19]  G. Chételat,et al.  Distinct influence of specific versus global connectivity on the different Alzheimer’s disease biomarkers , 2017, Brain : a journal of neurology.

[20]  Raymond P. Viviano,et al.  Subjective memory complaints are associated with brain activation supporting successful memory encoding , 2017, Neurobiology of Aging.

[21]  Fraser Olsen,et al.  Differential vulnerability of hippocampal subfields and anteroposterior hippocampal subregions in healthy cognitive aging , 2017, Neurobiology of Aging.

[22]  W. Jagust,et al.  Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity , 2017, Nature Communications.

[23]  Reinder Vos de Wael,et al.  Preferential susceptibility of limbic cortices to microstructural damage in temporal lobe epilepsy: A quantitative T1 mapping study , 2017, NeuroImage.

[24]  Denise C. Park,et al.  Association of Longitudinal Cognitive Decline With Amyloid Burden in Middle-aged and Older Adults , 2017, JAMA neurology.

[25]  J. Kaye,et al.  Detecting cognitive changes in preclinical Alzheimer's disease: A review of its feasibility , 2017, Alzheimer's & Dementia.

[26]  P. Snyder,et al.  Cognitive impairment and decline in cognitively normal older adults with high amyloid-β: A meta-analysis , 2016, Alzheimer's & dementia.

[27]  Elizabeth Jefferies,et al.  Situating the default-mode network along a principal gradient of macroscale cortical organization , 2016, Proceedings of the National Academy of Sciences.

[28]  Boris C. Bernhardt,et al.  A Surface Patch-Based Segmentation Method for Hippocampal Subfields , 2016, MICCAI.

[29]  A. McIntosh,et al.  Aging Effects on Whole-Brain Functional Connectivity in Adults Free of Cognitive and Psychiatric Disorders. , 2016, Cerebral cortex.

[30]  Jason B. Mattingley,et al.  Functional brain networks related to individual differences in human intelligence at rest , 2016, Scientific Reports.

[31]  Neda Bernasconi,et al.  The spectrum of structural and functional imaging abnormalities in temporal lobe epilepsy , 2016, Annals of neurology.

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

[33]  P. Sachdev,et al.  Age-associated differences on structural brain MRI in nondemented individuals from 71 to 103 years , 2016, Neurobiology of Aging.

[34]  Nicolas Cherbuin,et al.  Age-related cortical thinning in cognitively healthy individuals in their 60s: the PATH Through Life study , 2016, Neurobiology of Aging.

[35]  A. Krainik,et al.  Functional MRI evidence for the decline of word retrieval and generation during normal aging , 2015, AGE.

[36]  M. Yassa,et al.  Neurocognitive Aging and the Hippocampus across Species , 2015, Trends in Neurosciences.

[37]  C. Pan,et al.  Cognitive dysfunction and health-related quality of life among older Chinese , 2015, Scientific Reports.

[38]  G. Chételat,et al.  Structural imaging of hippocampal subfields in healthy aging and Alzheimer’s disease , 2015, Neuroscience.

[39]  Andrea Bernasconi,et al.  Multi-contrast submillimetric 3 Tesla hippocampal subfield segmentation protocol and dataset , 2015, Scientific Data.

[40]  S. Lithfous,et al.  Episodic memory in normal aging and Alzheimer disease: Insights from imaging and behavioral studies , 2015, Ageing Research Reviews.

[41]  Alan C. Evans,et al.  Age‐related changes in the topological organization of the white matter structural connectome across the human lifespan , 2015, Human brain mapping.

[42]  Frank Jessen,et al.  Subjective Cognitive Decline , 2021, Encyclopedia of Gerontology and Population Aging.

[43]  D. Y. Lee,et al.  Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. , 2015, JAMA.

[44]  Nicolas Cherbuin,et al.  A systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing , 2015, NeuroImage.

[45]  Y. Sheline,et al.  Imaging Biomarkers Associated With Cognitive Decline: A Review , 2015, Biological Psychiatry.

[46]  Keith A. Johnson,et al.  Amyloid-β deposition in mild cognitive impairment is associated with increased hippocampal activity, atrophy and clinical progression. , 2015, Brain : a journal of neurology.

[47]  C. Rowe,et al.  Beta-amyloid imaging with florbetaben , 2015, Clinical and Translational Imaging.

[48]  Anna Rieckmann,et al.  Neuromodulation and aging: implications of aging neuronal gain control on cognition , 2014, Current Opinion in Neurobiology.

[49]  W. Klunk,et al.  Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects. , 2014, Brain : a journal of neurology.

[50]  Cindee M. Madison,et al.  Effects of Beta-Amyloid on Resting State Functional Connectivity Within and Between Networks Reflect Known Patterns of Regional Vulnerability. , 2014, Cerebral cortex.

[51]  N. Bargalló,et al.  Changes in whole-brain functional networks and memory performance in aging , 2014, Neurobiology of Aging.

[52]  Boris C. Bernhardt,et al.  Multivariate Hippocampal Subfield Analysis of Local MRI Intensity and Volume: Application to Temporal Lobe Epilepsy , 2014, MICCAI.

[53]  Denise C. Park,et al.  How Does it STAC Up? Revisiting the Scaffolding Theory of Aging and Cognition , 2014, Neuropsychology Review.

[54]  Chunshui Yu,et al.  Abnormal salience network in normal aging and in amnestic mild cognitive impairment and Alzheimer's disease , 2014, Human brain mapping.

[55]  A. Dale,et al.  What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus , 2014, Progress in Neurobiology.

[56]  G. Ferrigno,et al.  Validation of FreeSurfer-Estimated Brain Cortical Thickness: Comparison with Histologic Measurements , 2014, Neuroinformatics.

[57]  C. Sorg,et al.  Within-patient correspondence of amyloid-β and intrinsic network connectivity in Alzheimer’s disease , 2014, Alzheimer's & Dementia.

[58]  D. Burns,et al.  Hippocampal sclerosis in dementia, epilepsy, and ischemic injury: differential vulnerability of hippocampal subfields. , 2014, Journal of neuropathology and experimental neurology.

[59]  Ferath Kherif,et al.  Impact of brain aging and neurodegeneration on cognition: evidence from MRI. , 2013, Current opinion in neurology.

[60]  Randy L. Buckner,et al.  The evolution of distributed association networks in the human brain , 2013, Trends in Cognitive Sciences.

[61]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[62]  Yaakov Stern,et al.  Cerebral blood flow and gray matter volume covariance patterns of cognition in aging , 2013, Human brain mapping.

[63]  Ali Kashif Bashir,et al.  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2013, ICIRA 2013.

[64]  M. P. van den Heuvel,et al.  The Ontogeny of the Human Connectome , 2013, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[65]  R. N. Spreng,et al.  Structural Covariance of the Default Network in Healthy and Pathological Aging , 2013, The Journal of Neuroscience.

[66]  Cindee M. Madison,et al.  Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer’s disease , 2013, Proceedings of the National Academy of Sciences.

[67]  Manuel Serrano,et al.  The Hallmarks of Aging , 2013, Cell.

[68]  Hallvard Røe Evensmoen,et al.  Long-axis specialization of the human hippocampus , 2013, Trends in Cognitive Sciences.

[69]  D. Bennett,et al.  The influence of cognitive decline on well-being in old age. , 2013, Psychology and aging.

[70]  A. McIntosh,et al.  Multivariate statistical analyses for neuroimaging data. , 2013, Annual review of psychology.

[71]  Bin Hu,et al.  A Longitudinal Study of Atrophy in Amnestic Mild Cognitive Impairment and Normal Aging Revealed by Cortical Thickness , 2012, PloS one.

[72]  Jean-François Gagnon,et al.  The impact of aging on gray matter structural covariance networks , 2012, NeuroImage.

[73]  L. Nyberg,et al.  Opposing Effects of Aging on Large-Scale Brain Systems for Memory Encoding and Cognitive Control , 2012, The Journal of Neuroscience.

[74]  C. Degueldre,et al.  Attention supports verbal short-term memory via competition between dorsal and ventral attention networks. , 2012, Cerebral cortex.

[75]  J M Starr,et al.  APOE E4 status predicts age-related cognitive decline in the ninth decade: longitudinal follow-up of the Lothian Birth Cohort 1921 , 2012, Molecular Psychiatry.

[76]  Michael I. Miller,et al.  Fornix integrity and hippocampal volume predict memory decline and progression to Alzheimer’s disease , 2012, Alzheimer's & Dementia.

[77]  Denise C. Park,et al.  &bgr;-Amyloid burden in healthy aging: Regional distribution and cognitive consequences , 2012, Neurology.

[78]  E. Mohammadi,et al.  Barriers and facilitators related to the implementation of a physiological track and trigger system: A systematic review of the qualitative evidence , 2017, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[79]  Steen Moeller,et al.  The Human Connectome Project: A data acquisition perspective , 2012, NeuroImage.

[80]  W. Klunk Amyloid imaging as a biomarker for cerebral β-amyloidosis and risk prediction for Alzheimer dementia , 2011, Neurobiology of Aging.

[81]  B. Dickerson,et al.  Age-Related Changes in the Thickness of Cortical Zones in Humans , 2011, Brain Topography.

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

[83]  N. Volkow,et al.  Aging and Functional Brain Networks , 2011, Molecular Psychiatry.

[84]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[85]  Jee Hoon Roh,et al.  Neuronal activity regulates the regional vulnerability to amyloid-β deposition , 2011, Nature Neuroscience.

[86]  K. Hawkins,et al.  The effects of apolipoprotein E on non-impaired cognitive functioning: A meta-analysis , 2011, Neurobiology of Aging.

[87]  David H. Salat,et al.  Cognition in healthy aging is related to regional white matter integrity, but not cortical thickness , 2010, Neurobiology of Aging.

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

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

[90]  E. Salmon,et al.  18F‐flutemetamol amyloid imaging in Alzheimer disease and mild cognitive impairment: A phase 2 trial , 2010, Annals of neurology.

[91]  R. N. Spreng,et al.  Reliable differences in brain activity between young and old adults: A quantitative meta-analysis across multiple cognitive domains , 2010, Neuroscience & Biobehavioral Reviews.

[92]  H. Abdi,et al.  Principal component analysis , 2010 .

[93]  J. Callicott,et al.  Age-related alterations in default mode network: Impact on working memory performance , 2010, Neurobiology of Aging.

[94]  L. Ferrucci,et al.  Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB , 2010, Neurology.

[95]  John G. Lynch,et al.  Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis , 2010 .

[96]  A. Dale,et al.  One-Year Brain Atrophy Evident in Healthy Aging , 2009, The Journal of Neuroscience.

[97]  Mark A Mintun,et al.  Cognitive decline and brain volume loss as signatures of cerebral amyloid-beta peptide deposition identified with Pittsburgh compound B: cognitive decline associated with Abeta deposition. , 2009, Archives of neurology.

[98]  Truman R Brown,et al.  Linking hippocampal structure and function to memory performance in an aging population. , 2009, Archives of neurology.

[99]  Bruce Fischl,et al.  Accurate and robust brain image alignment using boundary-based registration , 2009, NeuroImage.

[100]  Keith A. Johnson,et al.  Amyloid Deposition Is Associated with Impaired Default Network Function in Older Persons without Dementia , 2009, Neuron.

[101]  KJ Worsley,et al.  SurfStat: A Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric data using linear mixed effects models and random field theory , 2009, NeuroImage.

[102]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[103]  Brigitte Landeau,et al.  Structural and Metabolic Correlates of Episodic Memory in Relation to the Depth of Encoding in Normal Aging , 2009, Journal of Cognitive Neuroscience.

[104]  Jean-Marc Constans,et al.  Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging , 2009, Neurobiology of Aging.

[105]  Jeffrey A. James,et al.  Frequent amyloid deposition without significant cognitive impairment among the elderly. , 2008, Archives of neurology.

[106]  Karl J. Friston,et al.  A Hierarchy of Time-Scales and the Brain , 2008, PLoS Comput. Biol..

[107]  Damien A. Fair,et al.  Defining functional areas in individual human brains using resting functional connectivity MRI , 2008, NeuroImage.

[108]  R. Cabeza,et al.  Que PASA? The posterior-anterior shift in aging. , 2008, Cerebral cortex.

[109]  C. Jack,et al.  11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment. , 2008, Brain : a journal of neurology.

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

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

[112]  Michael W Weiner,et al.  Memory in the aging brain: Doubly dissociating the contribution of the hippocampus and entorhinal cortex , 2007, Hippocampus.

[113]  Kuncheng Li,et al.  Altered functional connectivity in early Alzheimer's disease: A resting‐state fMRI study , 2007, Human brain mapping.

[114]  Anders M. Dale,et al.  Regional cortical thickness matters in recall after months more than minutes , 2006, NeuroImage.

[115]  Martin Styner,et al.  Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM. , 2006, The insight journal.

[116]  Robert C. Welsh,et al.  Decreased neural specialization in old adults on a working memory task , 2006, Neuroreport.

[117]  Anders M. Dale,et al.  Selective increase of cortical thickness in high-performing elderly—structural indices of optimal cognitive aging , 2006, NeuroImage.

[118]  Benjamin J. Shannon,et al.  Molecular, Structural, and Functional Characterization of Alzheimer's Disease: Evidence for a Relationship between Default Activity, Amyloid, and Memory , 2005, The Journal of Neuroscience.

[119]  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.

[120]  Anthony Randal McIntosh,et al.  Partial least squares analysis of neuroimaging data: applications and advances , 2004, NeuroImage.

[121]  C. Petten Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis , 2004, Neuropsychologia.

[122]  Lars Bäckman,et al.  Apolipoprotein E and cognitive performance: a meta-analysis. , 2004, Psychology and aging.

[123]  A M Dale,et al.  Size does matter in the long run , 2004, Neurology.

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

[125]  D. Dickson,et al.  Hippocampal sclerosis dementia , 2004, Neurology.

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

[127]  Marianna D. Eddy,et al.  Regionally localized thinning of the cerebral cortex in schizophrenia , 2003, Schizophrenia Research.

[128]  C. Chabris,et al.  Neural mechanisms of general fluid intelligence , 2003, Nature Neuroscience.

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

[130]  P. Rabbitt,et al.  Apolipoprotein E genotype does not predict decline in intelligence in healthy older adults , 2002, Neuroscience Letters.

[131]  A. Dale,et al.  Regional and progressive thinning of the cortical ribbon in Huntington’s disease , 2002, Neurology.

[132]  S. Sikström,et al.  Aging cognition: from neuromodulation to representation , 2001, Trends in Cognitive Sciences.

[133]  Yaakov Stern,et al.  Memory performance in healthy elderly without Alzheimer’s disease: effects of time and apolipoprotein-E , 2001, Neurobiology of Aging.

[134]  Alan C. Evans,et al.  Age and Gender Predict Volume Decline in the Anterior and Posterior Hippocampus in Early Adulthood , 2001, The Journal of Neuroscience.

[135]  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.

[136]  J. Mortimer,et al.  Is APOE-ε4 a risk factor for cognitive impairment in normal aging? , 2000, Neurology.

[137]  G. Pearlson,et al.  Elucidating the contributions of processing speed, executive ability, and frontal lobe volume to normal age-related differences in fluid intelligence , 2000, Journal of the International Neuropsychological Society.

[138]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[139]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[140]  M. Mesulam,et al.  From sensation to cognition. , 1998, Brain : a journal of neurology.

[141]  L. Bäckman,et al.  Three-year changes in cognitive performance as a function of apolipoprotein E genotype: evidence from very old adults without dementia. , 1998, Psychology and aging.

[142]  E G Tangalos,et al.  Apolipoprotein E genotype influences cognitive ‘phenotype’ in patients with Alzheimer's disease but not in healthy control subjects , 1998, Neurology.

[143]  P. Scheltens,et al.  Visual assessment of medial temporal lobe atrophy on magnetic resonance imaging: Interobserver reliability , 1995, Journal of Neurology.

[144]  P. Rabbitt,et al.  Cambridge Neuropsychological Test Automated Battery (CANTAB): a factor analytic study of a large sample of normal elderly volunteers. , 1994, Dementia.

[145]  Leslie G. Ungerleider,et al.  Age-related changes in cortical blood flow activation during visual processing of faces and location , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[146]  T. Salthouse,et al.  Decomposing adult age differences in working memory. , 1991 .

[147]  S. Rapoport Hypothesis: Alzheimer's disease is a phylogenetic disease. , 1989, Medical hypotheses.

[148]  R. Engle,et al.  Is working memory capacity task dependent , 1989 .

[149]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[150]  H. Harman Modern factor analysis , 1961 .

[151]  H. B. Heywood,et al.  On finite sequences of real numbers , 1931 .

[152]  E. Ross The Organization of Will , 1916, American Journal of Sociology.

[153]  Subjective Memory Complaints , 2021, Encyclopedia of Gerontology and Population Aging.

[154]  D. Y. Lee,et al.  Association of Cerebral Amyloid-&bgr; Aggregation With Cognitive Functioning in Persons Without Dementia , 2018, JAMA psychiatry.

[155]  Julia M. Huntenburg,et al.  Large-Scale Gradients in Human Cortical Organization , 2018, Trends in Cognitive Sciences.

[156]  Mark A. Tipton Wechsler adult intelligence scale (4th edition) and the validity of supplementary/core subtest substitution , 2014 .

[157]  David C. Van Essen,et al.  Human Connectome Project , 2014, Encyclopedia of Computational Neuroscience.

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

[159]  Jenny Caesar,et al.  Segmentation of the Brain from MR Images , 2005 .

[160]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[161]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[162]  J. Brandt The Hopkins Verbal Learning Test: Development of a new memory test with six equivalent forms. , 1991 .