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• W2017022537 abstract "Brain aging is characterized by considerable heterogeneity, including varying degrees of dysfunction in specific brain systems, notably a medial temporal lobe memory system and a frontostriatal executive system. These same systems are also affected by neurodegenerative diseases. Recent work using techniques for presymptomatic detection of disease in cognitively normal older people has shown that some of the late life alterations in cognition, neural structure, and function attributed to aging probably reflect early neurodegeneration. However, it has become clear that these same brain systems are also vulnerable to aging in the absence of even subtle disease. Thus, fundamental systemic limitations appear to confer vulnerability of these neural systems to a variety of insults, including those recognized as typical disease and those that are attributed to age. By focusing on the fundamental causes of neural system vulnerability, the prevention or treatment of a wide range of late-life neural dysfunction might be possible. Brain aging is characterized by considerable heterogeneity, including varying degrees of dysfunction in specific brain systems, notably a medial temporal lobe memory system and a frontostriatal executive system. These same systems are also affected by neurodegenerative diseases. Recent work using techniques for presymptomatic detection of disease in cognitively normal older people has shown that some of the late life alterations in cognition, neural structure, and function attributed to aging probably reflect early neurodegeneration. However, it has become clear that these same brain systems are also vulnerable to aging in the absence of even subtle disease. Thus, fundamental systemic limitations appear to confer vulnerability of these neural systems to a variety of insults, including those recognized as typical disease and those that are attributed to age. By focusing on the fundamental causes of neural system vulnerability, the prevention or treatment of a wide range of late-life neural dysfunction might be possible. How does the brain age? The causes of the changes in cognition, neural function, and brain structure experienced by many older people are debated. Specifically, do the neurodegenerative diseases of older age often contribute to these problems, or is there a “pure” age-related form of neural decline that is clearly separate from disease? This question has occupied scientists involved in the study of aging for decades but is now becoming more tractable because of advances in techniques for studying the human brain during life. While heuristically useful, separating age and disease also creates problems. First, what is “aging”? There is no single mechanism that underlies age-related change other than the passage of time. Aging uncovers systemic limitations of human biology that may be susceptible to a variety of deleterious processes, some of which are related to frank disease and others not. Distinguishing age and disease has led to the concept of “normal aging,” which may be defined as what is left when disease is excluded. However, individuals in their seventh to ninth decades without significant disease (vascular, metabolic, or degenerative) are not statistically normal and are more aptly described as “supernormal” or optimally aged (Rowe and Kahn, 1987Rowe J.W. Kahn R.L. Human aging: usual and successful.Science. 1987; 237: 143-149Crossref PubMed Google Scholar). Studies of such individuals may provide insight into the intrinsic potential of human neural systems and could lead to ways of optimizing function in aging that are completely different from the methods for treating age-related disease. Is our conceptualization of normal aging in fact contaminated by the study of normal older people who are experiencing neurodegeneration? While for decades many studies of older people may have excluded those with manifest disease, it has become increasingly clear that neurodegeneration exists in subtle preclinical forms for many years prior to symptom onset. The use of norms to exclude individuals does not ameliorate these problems since many presymptomatic individuals will test in a normal range, and the norms themselves may have been contaminated by participants with preclinical symptoms. In fact, in-depth examination of many neural systems in older people reveals alterations that have been attributed to normal aging. But are such individuals “normal” in the sense of being free of disease, or do age-related deficits simply reflect undetected neurodegeneration? Over decades, considerable effort has been devoted to defining the cognitive profile of healthy (neurologically disease-free) older people. A frequent shortcoming of these studies is the use of cross-sectional as opposed to longitudinal data. Cross-sectional data do not permit the differentiation of lifelong or developmental subject characteristics from those that actually decline in older age. Nevertheless, many studies have characterized older individuals using two general approaches. One can be defined in terms of cognitive processes, while the other is more related to neural systems; these are not mutually incompatible, and both rely on examination of cognitive test performance. Regardless of the approach, there is wide agreement that older people are heterogeneous in their cognitive performance. Some older individuals have abilities typical of much younger people, while others show marked decrements (Wilson et al., 2002Wilson R.S. Beckett L.A. Barnes L.L. Schneider J.A. Bach J. Evans D.A. Bennett D.A. Individual differences in rates of change in cognitive abilities of older persons.Psychol. Aging. 2002; 17: 179-193Crossref PubMed Scopus (316) Google Scholar). Furthermore, there is good agreement that some cognitive abilities, particularly semantic memory or knowledge, are relatively preserved with age (Park et al., 2002Park D.C. Lautenschlager G. Hedden T. Davidson N.S. Smith A.D. Smith P.K. Models of visuospatial and verbal memory across the adult life span.Psychol. Aging. 2002; 17: 299-320Crossref PubMed Scopus (384) Google Scholar). The cognitive abilities that most consistently decline with age are processing speed, working memory, and episodic memory (Schaie, 1996Schaie K.W. Intellectual Development in Adulthood: The Seattle Longitudinal Study. Cambridge University Press, Cambridge, MA1996Google Scholar; Park et al., 2002Park D.C. Lautenschlager G. Hedden T. Davidson N.S. Smith A.D. Smith P.K. Models of visuospatial and verbal memory across the adult life span.Psychol. Aging. 2002; 17: 299-320Crossref PubMed Scopus (384) Google Scholar). Models of cognitive aging that attempt to define change in terms of fundamental cognitive processes that drive general decline propose a small number of underlying cognitive processes that are responsible for decline in multiple areas; such models generally include processing speed (Salthouse and Ferrer-Caja, 2003Salthouse T.A. Ferrer-Caja E. What needs to be explained to account for age-related effects on multiple cognitive variables?.Psychol. Aging. 2003; 18: 91-110Crossref PubMed Scopus (134) Google Scholar) or executive function (Hasher and Zachs, 1988Hasher L. Zachs R.T. Working memory, comprehension, and aging: A review and a new view.in: The Psychology of Learning and Motivation. 22. Academic Press, New York1988: 193-225Google Scholar) as key factors. A major theory of cognitive aging attributes many aspects of cognitive decline to loss of prefrontal cortical function (West, 1996West R.L. An application of prefrontal cortex function theory to cognitive aging.Psychol. Bull. 1996; 120: 272-292Crossref PubMed Google Scholar), although some aspects of episodic memory are not well accounted for by this model. Neural system-based conceptualizations define age-related cognitive decline in terms of two fundamental neural systems that support episodic memory and executive function (Buckner, 2004Buckner R.L. Memory and executive function in aging and AD: multiple factors that cause decline and reserve factors that compensate.Neuron. 2004; 44: 195-208Abstract Full Text Full Text PDF PubMed Scopus (436) Google Scholar; Hedden and Gabrieli, 2004Hedden T. Gabrieli J.D.E. Insights into the ageing mind: a view from cognitive neuroscience.Nat. Rev. Neurosci. 2004; 5: 87-96Crossref PubMed Google Scholar). Differential decline of these cognitive processes reflects varying degrees of involvement of the medial temporal lobe memory system and a prefrontal cortex/striatal executive system. The major late-life neurodegenerative disorders affect these two neural systems differently and thereby may explain some of the heterogeneity in brain aging. In addition, there are other neural systems that are affected by age and disease that will be discussed, and there are numerous other systems that are not the focus of this Review. Three common age-related diseases are the most likely culprits in producing neural alterations attributed to normal aging: Alzheimer’s disease (AD), cerebrovascular disease (CVD), and Parkinson’s disease (PD). Relationships between these disorders and aging could represent several different situations: manifest neurodegenerative disease, presymptomatic neurodegenerative disease, or a “phenocopy” of a neurodegenerative disease that is actually based in a different mechanism. Alzheimer’s disease is crucial to discussions of cognitive aging simply because it is so prevalent; at least 1% of people at age 65 have AD, with prevalence rising at least to 30% by age 80 (Hofman et al., 1991Hofman A. Rocca W.A. Brayne C. Breteler M.M. Clarke M. Cooper B. Copeland J.R. Dartigues J.F. da Silva Droux A. Hagnell O. et al.Eurodem Prevalence Research GroupThe prevalence of dementia in Europe: a collaborative study of 1980-1990 findings.Int. J. Epidemiol. 1991; 20: 736-748Crossref PubMed Google Scholar). These figures reflect the presence of dementia, a progressive diminution of cognitive abilities incompatible with independent functioning. AD usually begins with anterograde amnesia, although other cognitive disturbances can occur in the initial stage. AD evolves from more subtle syndromes, often referred to as mild cognitive impairment (MCI). While the strong age association of AD has at times resulted in the belief that it represented normative aging, it is amply clear that many individuals live to late life without dementia. Many recent reviews have summarized the molecular pathology, clinical features, and therapeutic approaches to AD (Querfurth and LaFerla, 2010Querfurth H.W. LaFerla F.M. Alzheimer’s disease.N. Engl. J. Med. 2010; 362: 329-344Crossref PubMed Scopus (761) Google Scholar; Golde et al., 2011Golde T.E. Schneider L.S. Koo E.H. Anti-aβ therapeutics in Alzheimer’s disease: the need for a paradigm shift.Neuron. 2011; 69: 203-213Abstract Full Text Full Text PDF PubMed Scopus (101) Google Scholar). The disease is defined by the association of cognitive symptoms with the neuropathological findings of neuritic or senile plaques and neurofibrillary tangles (NFTs) revealed on histological examination of the brain (Figure 1). Plaques are composed of the aggregated β-amyloid (Aβ) protein surrounded by dystrophic and degenerating neurites, while NFTs are composed of the microtubule-associated protein tau, which is hyperphosphorylated and aggregated as paired helical filaments. A major theory of AD causation holds that soluble forms of Aβ initiate the disease, leading to alterations in synaptic structure and function, followed by Aβ aggregation into plaques (Hardy, 2009Hardy J. The amyloid hypothesis for Alzheimer’s disease: a critical reappraisal.J. Neurochem. 2009; 110: 1129-1134Crossref PubMed Scopus (225) Google Scholar). This is consistent with evidence that reveals limited associations between plaque Aβ and dementia severity but stronger associations between cognition and NFTs and synaptic number and size (DeKosky and Scheff, 1990DeKosky S.T. Scheff S.W. Synapse loss in frontal cortex biopsies in Alzheimer’s disease: correlation with cognitive severity.Ann. Neurol. 1990; 27: 457-464Crossref PubMed Google Scholar; Nelson et al., 2012Nelson P.T. Alafuzoff I. Bigio E.H. Bouras C. Braak H. Cairns N.J. Castellani R.J. Crain B.J. Davies P. Del Tredici K. et al.Correlation of Alzheimer disease neuropathologic changes with cognitive status: a review of the literature.J. Neuropathol. Exp. Neurol. 2012; 71: 362-381Crossref PubMed Scopus (58) Google Scholar). In its full form, this amyloid cascade hypothesis holds that early soluble Aβ unleashes a chain of events causing alterations in synapses and tau, and a host of downstream structural and functional neural changes that are closely related to cognitive decline. Several issues complicate the differentiation of AD from normal aging. First, the relationship between fundamental features of AD pathology and cognition are tenuous. Recent neuropathological criteria recognize that AD pathological change can exist in the absence of symptoms (Hyman et al., 2012Hyman B.T. Phelps C.H. Beach T.G. Bigio E.H. Cairns N.J. Carrillo M.C. Dickson D.W. Duyckaerts C. Frosch M.P. Masliah E. et al.National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease.Alzheimers Dement. 2012; 8: 1-13Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar), raising the likelihood that some individuals may be resistant to the pathology. This is a particularly confusing situation in the very old, where the relationship between AD pathological change and cognition is particularly weak (Savva et al., 2009Savva G.M. Wharton S.B. Ince P.G. Forster G. Matthews F.E. Brayne C. Medical Research Council Cognitive Function and Ageing StudyAge, neuropathology, and dementia.N. Engl. J. Med. 2009; 360: 2302-2309Crossref PubMed Scopus (250) Google Scholar; Balasubramanian et al., 2012Balasubramanian A.B. Kawas C.H. Peltz C.B. Brookmeyer R. Corrada M.M. Alzheimer disease pathology and longitudinal cognitive performance in the oldest-old with no dementia.Neurology. 2012; 79: 915-921Crossref PubMed Scopus (5) Google Scholar). Second, the pathology associated with AD occurs in partial forms. NFTs, without Aβ plaques, are seen in many cognitively normal people, usually in medial temporal lobe structures, and they increase exponentially with advancing age (Price and Morris, 1999Price J.L. Morris J.C. Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease.Ann. Neurol. 1999; 45: 358-368Crossref PubMed Scopus (779) Google Scholar). These NFTs particularly affect entorhinal cortical neurons that project to dentate gyrus as the perforant pathway, functionally disconnecting the hippocampus (Hyman et al., 1984Hyman B.T. Van Hoesen G.W. Damasio A.R. Barnes C.L. Alzheimer’s disease: cell-specific pathology isolates the hippocampal formation.Science. 1984; 225: 1168-1170Crossref PubMed Google Scholar). Aβ plaques also occur in “diffuse,” as opposed to cored or neuritic forms, and these too are commonly seen in cognitively intact older people (Knopman et al., 2003Knopman D.S. Parisi J.E. Salviati A. Floriach-Robert M. Boeve B.F. Ivnik R.J. Smith G.E. Dickson D.W. Johnson K.A. Petersen L.E. et al.Neuropathology of cognitively normal elderly.J. Neuropathol. Exp. Neurol. 2003; 62: 1087-1095Crossref PubMed Google Scholar). Whether these pathologies reflect early AD or processes related to aging itself remains debated. Stroke, or cerebral infarction, is also associated with both advancing age and cognitive decline (Seshadri et al., 2006Seshadri S. Beiser A. Kelly-Hayes M. Kase C.S. Au R. Kannel W.B. Wolf P.A. The lifetime risk of stroke: estimates from the Framingham Study.Stroke. 2006; 37: 345-350Crossref PubMed Scopus (180) Google Scholar). The most fulminant effect of stroke on cognition appears as “multi-infarct dementia” (Hachinski et al., 1974Hachinski V.C. Lassen N.A. Marshall J. Multi-infarct dementia. A cause of mental deterioration in the elderly.Lancet. 1974; 2: 207-210Abstract PubMed Google Scholar), but the prevalence of this disorder is argued. At least as important are many other forms of cerebrovascular disease seen in aging, including asymptomatic disease detected on imaging (O’Brien et al., 2003O’Brien J.T. Erkinjuntti T. Reisberg B. Roman G. Sawada T. Pantoni L. Bowler J.V. Ballard C. DeCarli C. Gorelick P.B. et al.Vascular cognitive impairment.Lancet Neurol. 2003; 2: 89-98Abstract Full Text Full Text PDF PubMed Scopus (505) Google Scholar). Other manifestations of CVD include alterations in subcortical white matter involving demyelination, rarefaction, and high signal intensity on MRIs, thinning of cerebral cortex and cerebral atrophy, and subclinical, silent infarction related to small vessel occlusion (DeCarli et al., 1999DeCarli C. Miller B.L. Swan G.E. Reed T. Wolf P.A. Garner J. Jack L. Carmelli D. Predictors of brain morphology for the men of the NHLBI twin study.Stroke. 1999; 30: 529-536Crossref PubMed Google Scholar; Vermeer et al., 2003Vermeer S.E. Prins N.D. den Heijer T. Hofman A. Koudstaal P.J. Breteler M.M. Silent brain infarcts and the risk of dementia and cognitive decline.N. Engl. J. Med. 2003; 348: 1215-1222Crossref PubMed Scopus (951) Google Scholar) (Figure 1). All of these forms of CVD have been linked with cognitive dysfunction, are subtle or clinically undetectable in onset and progression, and may play a role in age-related decline. Parkinson’s disease is a disorder of the motor system with cardinal manifestations of slowing of motion (bradykinesia), tremor, rigidity, and gait and postural instability. The characteristic neuropathology involves loss of dopaminergic neurons in the pars compacta of the substantia nigra (SN). These neurons, which project to the striatum as the nigrostriatal pathway, also contain Lewy bodies, an abnormally aggregated form of the protein α-synuclein (Figure 1). PD has a strong age-associated prevalence and is accompanied by cognitive dysfunction. Both dementia (Aarsland et al., 1996Aarsland D. Tandberg E. Larsen J.P. Cummings J.L. Frequency of dementia in Parkinson disease.Arch. Neurol. 1996; 53: 538-542Crossref PubMed Google Scholar) and mild cognitive impairment (Litvan et al., 2012Litvan I. Goldman J.G. Tröster A.I. Schmand B.A. Weintraub D. Petersen R.C. Mollenhauer B. Adler C.H. Marder K. Williams-Gray C.H. et al.Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines.Mov. Disord. 2012; 27: 349-356Crossref PubMed Scopus (83) Google Scholar) are common in PD patients. This type of major cognitive dysfunction is associated with widespread limbic and neocortical Lewy body pathology as well as concomittant AD pathology (Compta et al., 2011Compta Y. Parkkinen L. O’Sullivan S.S. Vandrovcova J. Holton J.L. Collins C. Lashley T. Kallis C. Williams D.R. de Silva R. et al.Lewy- and Alzheimer-type pathologies in Parkinson’s disease dementia: which is more important?.Brain. 2011; 134: 1493-1505Crossref PubMed Scopus (67) Google Scholar). However, PD is also associated with a range of more subtle cognitive manifestations that may reflect dopamine deficiency. Substantial AD pathology is consistently reported in postmortem studies of older individuals who were cognitively normal prior to death. About 20%–40% of cognitively normal individuals in their eighth to ninth decades have at least intermediate levels of Aβ and NFT-tau pathology on autopsy examination (Bennett et al., 2006Bennett D.A. Schneider J.A. Arvanitakis Z. Kelly J.F. Aggarwal N.T. Shah R.C. Wilson R.S. Neuropathology of older persons without cognitive impairment from two community-based studies.Neurology. 2006; 66: 1837-1844Crossref PubMed Scopus (369) Google Scholar; Kok et al., 2009Kok E. Haikonen S. Luoto T. Huhtala H. Goebeler S. Haapasalo H. Karhunen P.J. Apolipoprotein E-dependent accumulation of Alzheimer disease-related lesions begins in middle age.Ann. Neurol. 2009; 65: 650-657Crossref PubMed Scopus (72) Google Scholar); many of these people meet pathological criteria for AD. This evidence has been used to assail the amyloid cascade hypothesis, but adherents hold that such individuals were in a stage of preclinical AD that would have progressed to dementia had they lived longer. These people may remain normal because of neural compensation or reserve, which has been conceptualized in two ways: a static or passive form of reserve, often referred to as “brain reserve,” and a more dynamic form of reserve, described as “cognitive reserve” or compensation (Stern, 2002Stern Y. What is cognitive reserve? Theory and research application of the reserve concept.J. Int. Neuropsychol. Soc. 2002; 8: 448-460Crossref PubMed Scopus (773) Google Scholar). Brain reserve implies that individuals differ in baseline neural resources at the onset of age-related pathology, perhaps because of developmental factors or the balance of lifelong positive and negative exposures. The dynamic concept of reserve implies a more active compensatory process that could represent functional reorganization that recruits additional neural resources to maintain task performance. Individuals with AD pathology who maintain normal cognition are the focus of intense investigation because they may represent the earliest phase of AD, and thus the types of individuals most amenable to therapy. Such people clearly reside on the border of normal cognitive aging and neurodegeneration. A major technological advance for studying such individuals is the development of radiolabeled tracers that bind to Aβ that can be imaged with positron emission tomography (PET) (Figure 2). A number of such PET amyloid imaging agents are currently available; the ligand [11C]PiB (or Pittsburgh compound B) has been the most widely used (Klunk et al., 2004Klunk W.E. Engler H. Nordberg A. Wang Y. Blomqvist G. Holt D.P. Bergström M. Savitcheva I. Huang G.F. Estrada S. et al.Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B.Ann. Neurol. 2004; 55: 306-319Crossref PubMed Scopus (1644) Google Scholar), with longer-lived [18F]-labeled imaging agents recently available (Clark et al., 2011Clark C.M. Schneider J.A. Bedell B.J. Beach T.G. Bilker W.B. Mintun M.A. Pontecorvo M.J. Hefti F. Carpenter A.P. Flitter M.L. et al.AV45-A07 Study GroupUse of florbetapir-PET for imaging beta-amyloid pathology.JAMA. 2011; 305: 275-283Crossref PubMed Scopus (196) Google Scholar). PET amyloid imaging detects only the fibrillar aggregated forms of Aβ, which is probably a later phenomenon and less pathogenic than the soluble forms. In studies of cognitively intact elderly, proportions of subjects with PET evidence of fibrillar Aβ deposition are congruent with the 20%–30% rates seen with autopsy examination (Morris et al., 2010Morris J.C. Roe C.M. Xiong C. Fagan A.M. Goate A.M. Holtzman D.M. Mintun M.A. APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging.Ann. Neurol. 2010; 67: 122-131Crossref PubMed Scopus (201) Google Scholar). These values also agree with measurements of Aβ obtained in cerebrospinal fluid (CSF) (Jagust et al., 2009Jagust W.J. Landau S.M. Shaw L.M. Trojanowski J.Q. Koeppe R.A. Reiman E.M. Foster N.L. Petersen R.C. Weiner M.W. Price J.C. Mathis C.A. Alzheimer’s Disease Neuroimaging InitiativeRelationships between biomarkers in aging and dementia.Neurology. 2009; 73: 1193-1199Crossref PubMed Scopus (133) Google Scholar), where lower levels of CSF Aβ probably reflect increased deposition in insoluble forms in the amyloid plaque. Although both CSF and PET imaging show similar proportions of older people with evidence of brain Aβ, the majority of older people do not have evidence of brain Aβ deposition. Nevertheless, this technology makes it possible to evaluate living people for the effects of Aβ on neural systems. The ability to detect brain Aβ deposition in older healthy adults has resulted in intensive efforts to define cognitive performance in such people, with somewhat conflicting results. While many studies have failed to find any evidence of lower cognitive performance (Aizenstein et al., 2008Aizenstein H.J. Nebes R.D. Saxton J.A. Price J.C. Mathis C.A. Tsopelas N.D. Ziolko S.K. James J.A. Snitz B.E. Houck P.R. et al.Frequent amyloid deposition without significant cognitive impairment among the elderly.Arch. Neurol. 2008; 65: 1509-1517Crossref PubMed Scopus (328) Google Scholar), a number have reported subtle decrements in a host of cognitive abilities in those with either imaging or pathological evidence of Aβ. Most often this is seen in episodic memory (Bennett et al., 2006Bennett D.A. Schneider J.A. Arvanitakis Z. Kelly J.F. Aggarwal N.T. Shah R.C. Wilson R.S. Neuropathology of older persons without cognitive impairment from two community-based studies.Neurology. 2006; 66: 1837-1844Crossref PubMed Scopus (369) Google Scholar; Pike et al., 2011Pike K.E. Ellis K.A. Villemagne V.L. Good N. Chételat G. Ames D. Szoeke C. Laws S.M. Verdile G. Martins R.N. et al.Cognition and beta-amyloid in preclinical Alzheimer’s disease: data from the AIBL study.Neuropsychologia. 2011; 49: 2384-2390Crossref PubMed Scopus (39) Google Scholar; Perrotin et al., 2012Perrotin A. Mormino E.C. Madison C.M. Hayenga A.O. Jagust W.J. Subjective cognition and amyloid deposition imaging: a Pittsburgh Compound B positron emission tomography study in normal elderly individuals.Arch. Neurol. 2012; 69: 223-229Crossref PubMed Scopus (10) Google Scholar), although other cognitive domains may be affected (Rodrigue et al., 2012Rodrigue K.M. Kennedy K.M. Devous Sr., M.D. Rieck J.R. Hebrank A.C. Diaz-Arrastia R. Mathews D. Park D.C. β-Amyloid burden in healthy aging: regional distribution and cognitive consequences.Neurology. 2012; 78: 387-395Crossref PubMed Scopus (46) Google Scholar). Longitudinal memory decline also appears to be greater in those with evidence of Aβ (Storandt et al., 2009Storandt M. Mintun M.A. Head D. Morris J.C. 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.Arch. Neurol. 2009; 66: 1476-1481Crossref PubMed Scopus (109) Google Scholar; Resnick et al., 2010Resnick S.M. Sojkova J. Zhou Y. An Y. Ye W. Holt D.P. Dannals R.F. Mathis C.A. Klunk W.E. Ferrucci L. et al.Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB.Neurology. 2010; 74: 807-815Crossref PubMed Scopus (83) Google Scholar). In studies that report such cross-sectional or longitudinal decline, deficits are quite small. Preservation of cognitive ability could be due to reserve, or it could reflect the fact that the full cascade of negative events has not yet occurred. These downstream pathological alterations appear to follow Aβ in a sequence of events with prototypical ordering (Jack et al., 2010Jack Jr., C.R. Knopman D.S. Jagust W.J. Shaw L.M. Aisen P.S. Weiner M.W. Petersen R.C. Trojanowski J.Q. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade.Lancet Neurol. 2010; 9: 119-128Abstract Full Text Full Text PDF PubMed Scopus (774) Google Scholar). Brain atrophy, for example, is associated with Aβ deposition in normals (Jack et al., 2009Jack Jr., C.R. Lowe V.J. Weigand S.D. Wiste H.J. Senjem M.L. Knopman D.S. Shiung M.M. Gunter J.L. Boeve B.F. Kemp B.J. et al.Alzheimer’s Disease Neuroimaging InitiativeSerial PIB and MRI in normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease.Brain. 2009; 132: 1355-1365Crossref PubMed Scopus (391) Google Scholar) and hippocampal atrophy may mediate effects of Aβ on cognition (Mormino et al., 2009Mormino E.C. Kluth J.T. Madison C.M. Rabinovici G.D. Baker S.L. Miller B.L. Koeppe R.A. Mathis C.A. Weiner M.W. Jagust W.J. Alzheimer’s Disease Neuroimaging InitiativeEpisodic memory loss is related to hippocampal-mediated beta-amyloid deposition in elderly subjects.Brain. 2009; 132: 1310-1323Crossref PubMed Scopus (240) Google Scholar) so that individuals with Aβ who have not yet developed these downstream changes could be spared symptoms. Thus, older people with evidence of Aβ may remain normal because they have not expressed the full phenotype of AD—they have amyloid pathology without clear evidence of neurodegeneration and will look like all other older individuals on every measure except Aβ. However, mounting evidence suggests that very subtle alterations in brain function may also be present in such individuals. Aβ deposition is associated with disruption of large-scale neural networks. These have been studied in the resting state using the technique of functional connectivity MRI (fcMRI), which makes use of the observation that spontaneous fluctuations in the MRI signal occur synchronously within neural systems (Biswal et al., 1995Biswal B. Yetkin F.Z. Haughton V.M. Hyde J.S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.Magn. Reson. Med. 1995; 34: 537-541Crossref PubMed Scopus (1987) Google Scholar). These networks reflect sensory and motor systems as well as ensembles of brain regions brought online during tasks requiring memory, attention, or executive function (Damoiseaux et al., 2006Damoiseaux J.S. Rombouts S.A. Barkhof F. Scheltens P. Stam C.J. Smith S.M. Beckmann C.F. Consistent resting-state networks across healthy subjects.Proc. Natl. Acad. Sci. USA. 2006; 103: 13848-13853Crossref PubMed Scopus (1003) Google Scholar). These may be “task-positive” networks activated by externally directed cognitive tasks or “task-negative” networks that are deactivated during externally driven cognition. The primary task-negative network, the default mode network (DMN) (Raichle et al., 2001Raichle M.E. MacLeod A.M. Snyder A.Z. Powers W.J. Gusnard" @default.
• W2017022537 created "2016-06-24" @default.
• W2017022537 creator A5061269385 @default.
• W2017022537 date "2013-01-01" @default.
• W2017022537 modified "2023-10-06" @default.
• W2017022537 title "Vulnerable Neural Systems and the Borderland of Brain Aging and Neurodegeneration" @default.
• W2017022537 cites W1492360652 @default.
• W2017022537 cites W1591978608 @default.
• W2017022537 cites W1596429639 @default.
• W2017022537 cites W1762188861 @default.
• W2017022537 cites W1855610705 @default.
• W2017022537 cites W1921980981 @default.
• W2017022537 cites W1929729372 @default.
• W2017022537 cites W1964206422 @default.
• W2017022537 cites W1966907278 @default.
• W2017022537 cites W1968051953 @default.
• W2017022537 cites W1968578449 @default.
• W2017022537 cites W1969001168 @default.
• W2017022537 cites W1969237172 @default.
• W2017022537 cites W1971603645 @default.
• W2017022537 cites W1971811680 @default.
• W2017022537 cites W1972661606 @default.
• W2017022537 cites W1974594322 @default.
• W2017022537 cites W1978465828 @default.
• W2017022537 cites W1978611788 @default.
• W2017022537 cites W1979706194 @default.
• W2017022537 cites W1980111435 @default.
• W2017022537 cites W1980225806 @default.
• W2017022537 cites W1980842500 @default.
• W2017022537 cites W1980858895 @default.
• W2017022537 cites W1984748043 @default.
• W2017022537 cites W1987110004 @default.
• W2017022537 cites W1988370080 @default.
• W2017022537 cites W1989019473 @default.
• W2017022537 cites W1989592528 @default.
• W2017022537 cites W1990019125 @default.
• W2017022537 cites W1994994698 @default.
• W2017022537 cites W1996415028 @default.
• W2017022537 cites W1996589171 @default.
• W2017022537 cites W1996642546 @default.
• W2017022537 cites W1997301424 @default.
• W2017022537 cites W1998088268 @default.
• W2017022537 cites W1998395846 @default.
• W2017022537 cites W1999367055 @default.
• W2017022537 cites W1999489033 @default.
• W2017022537 cites W2002776021 @default.
• W2017022537 cites W2002923643 @default.
• W2017022537 cites W2003428745 @default.
• W2017022537 cites W2008609885 @default.
• W2017022537 cites W2008683968 @default.
• W2017022537 cites W2009494091 @default.
• W2017022537 cites W2011286803 @default.
• W2017022537 cites W2012437345 @default.
• W2017022537 cites W2014897304 @default.
• W2017022537 cites W2015837978 @default.
• W2017022537 cites W2018007042 @default.
• W2017022537 cites W2021005581 @default.
• W2017022537 cites W2021405530 @default.
• W2017022537 cites W2024053893 @default.
• W2017022537 cites W2028050242 @default.
• W2017022537 cites W2029151785 @default.
• W2017022537 cites W2029164422 @default.
• W2017022537 cites W2029167038 @default.
• W2017022537 cites W2029603577 @default.
• W2017022537 cites W2031293980 @default.
• W2017022537 cites W2032420429 @default.
• W2017022537 cites W2036642860 @default.
• W2017022537 cites W2037403969 @default.
• W2017022537 cites W2042974739 @default.
• W2017022537 cites W2043955468 @default.
• W2017022537 cites W2045311514 @default.
• W2017022537 cites W2045893895 @default.
• W2017022537 cites W2050800850 @default.
• W2017022537 cites W2051910095 @default.
• W2017022537 cites W2053395355 @default.
• W2017022537 cites W2055964704 @default.
• W2017022537 cites W2057245667 @default.
• W2017022537 cites W2060629467 @default.
• W2017022537 cites W2063142549 @default.
• W2017022537 cites W2064446115 @default.
• W2017022537 cites W2067147530 @default.
• W2017022537 cites W2069476204 @default.
• W2017022537 cites W2070069429 @default.
• W2017022537 cites W2070268750 @default.
• W2017022537 cites W2070524933 @default.
• W2017022537 cites W2074274706 @default.
• W2017022537 cites W2075126496 @default.
• W2017022537 cites W2075348467 @default.
• W2017022537 cites W2075714285 @default.
• W2017022537 cites W2076513227 @default.
• W2017022537 cites W2077066095 @default.
• W2017022537 cites W2078790263 @default.
• W2017022537 cites W2079082269 @default.
• W2017022537 cites W2084177652 @default.
• W2017022537 cites W2086978209 @default.
• W2017022537 cites W2089649622 @default.
• W2017022537 cites W2089744719 @default.
• W2017022537 cites W2091646494 @default.

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