{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T07:28:03Z","timestamp":1792567683894,"version":"4.5.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2017,12,14]],"date-time":"2017-12-14T00:00:00Z","timestamp":1513209600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2017,12,14]],"date-time":"2017-12-14T00:00:00Z","timestamp":1513209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["973302, 179805, 157125, 1002560"],"award-info":[{"award-number":["973302, 179805, 157125, 1002560"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1063907"],"award-info":[{"award-number":["1063907"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010582","name":"National Computational Infrastructure","doi-asserted-by":"publisher","award":["J66"],"award-info":[{"award-number":["J66"]}],"id":[{"id":"10.13039\/100010582","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["120100227"],"award-info":[{"award-number":["120100227"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Imaging and Behavior"],"published-print":{"date-parts":[[2019,2]]},"DOI":"10.1007\/s11682-017-9789-5","type":"journal-article","created":{"date-parts":[[2017,12,14]],"date-time":"2017-12-14T04:41:15Z","timestamp":1513226475000},"page":"65-74","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Validated Alzheimer\u2019s Disease Risk Index (ANU-ADRI) is associated with smaller volumes in the default mode network in the early 60s"],"prefix":"10.1007","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6481-0748","authenticated-orcid":false,"given":"Nicolas","family":"Cherbuin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marnie E.","family":"Shaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erin","family":"Walsh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Perminder","family":"Sachdev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaarin J.","family":"Anstey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,12,14]]},"reference":[{"key":"9789_CR1","doi-asserted-by":"crossref","unstructured":"Andrews, S. J., Eramudugolla, R., Velez, J., Cherbuin, N., Easteal, S., & Anstey, K. J. (2017). Validating the role of the Australian National University Alzheimer\u2019s disease risk index (ANU-ADRI) and a genetic risk score in progression to cognitive impairment in a population-based cohort of older adults followed for 12 years. Alzheimer\u2019s Research & Therapy, 9(1), 16.","DOI":"10.1186\/s13195-017-0240-3"},{"key":"9789_CR2","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1016\/j.neuron.2010.02.005","volume":"65","author":"JR Andrews-Hanna","year":"2010","unstructured":"Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010). Functional-anatomic fractionation of the brain\u2019s default network. Neuron, 65, 550\u2013562.","journal-title":"Neuron"},{"key":"9789_CR3","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1007\/s11121-012-0313-2","volume":"14","author":"KJ Anstey","year":"2013","unstructured":"Anstey, K. J., Cherbuin, N., & Herath, P. M. (2013). Development of a new method for assessing global risk of Alzheimer\u2019s disease for use in population health approaches to prevention. Prevention Science, 14, 411\u2013421.","journal-title":"Prevention Science"},{"key":"9789_CR4","doi-asserted-by":"publisher","first-page":"e86141","DOI":"10.1371\/journal.pone.0086141","volume":"9","author":"KJ Anstey","year":"2014","unstructured":"Anstey, K. J., Cherbuin, N., Herath, P. M., et al. (2014). A self-report risk index to predict occurrence of dementia in three independent cohorts of older adults: the ANU-ADRI. PloS One, 9, e86141.","journal-title":"PloS One"},{"key":"9789_CR5","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1093\/ije\/dyr025","volume":"41","author":"KJ Anstey","year":"2012","unstructured":"Anstey, K. J., Christensen, H., Butterworth, P., et al. (2012). Cohort profile: the PATH through life project. International Journal of Epidemiology, 41, 951\u2013960.","journal-title":"International Journal of Epidemiology"},{"key":"9789_CR6","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1186\/s12916-014-0206-2","volume":"12","author":"J Attems","year":"2014","unstructured":"Attems, J., & Jellinger, K. A. (2014). The overlap between vascular disease and Alzheimer\u2019s disease\u2014lessons from pathology. BMC Medicine, 12, 206.","journal-title":"BMC Medicine"},{"key":"9789_CR7","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1037\/0022-3514.51.6.1173","volume":"51","author":"RM Baron","year":"1986","unstructured":"Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173\u20131182.","journal-title":"Journal of Personality and Social Psychology"},{"key":"9789_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1196\/annals.1440.011","volume":"1124","author":"RL Buckner","year":"2008","unstructured":"Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain\u2019s default network: anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1\u201338.","journal-title":"Annals of the New York Academy of Sciences"},{"key":"9789_CR9","doi-asserted-by":"publisher","first-page":"e763","DOI":"10.1097\/MD.0000000000000763","volume":"94","author":"YT Chang","year":"2015","unstructured":"Chang, Y. T., Huang, C. W., Chang, Y. H., et al. (2015). Amyloid burden in the hippocampus and default mode network: relationships with gray matter volume and cognitive performance in mild stage Alzheimer disease. Medicine, 94, e763.","journal-title":"Medicine"},{"key":"9789_CR10","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1006\/nimg.1998.0395","volume":"9","author":"AM Dale","year":"1999","unstructured":"Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. NeuroImage, 9, 179\u2013194.","journal-title":"NeuroImage"},{"key":"9789_CR11","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.neuroimage.2006.01.021","volume":"31","author":"RS Desikan","year":"2006","unstructured":"Desikan, R. S., Segonne, F., Fischl, B., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31, 968\u2013980.","journal-title":"NeuroImage"},{"key":"9789_CR12","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","volume":"62","author":"B Fischl","year":"2012","unstructured":"Fischl, B. (2012). FreeSurfer. Neuroimage, 62, 774\u2013781.","journal-title":"Neuroimage"},{"key":"9789_CR13","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.pneurobio.2014.02.004","volume":"117","author":"AM Fjell","year":"2014","unstructured":"Fjell, A. M., McEvoy, L., Holland, D., Dale, A. M., & Walhovd, K. B. (2014). What is normal in normal aging? Effects of aging, amyloid and Alzheimer\u2019s disease on the cerebral cortex and the hippocampus. Progress in Neurobiology, 117, 20\u201340.","journal-title":"Progress in Neurobiology"},{"key":"9789_CR14","doi-asserted-by":"publisher","first-page":"897","DOI":"10.1136\/bmj.297.6653.897","volume":"297","author":"D Goldberg","year":"1988","unstructured":"Goldberg, D., Bridges, K., Duncan-Jones, P., & Grayson, D. (1988). Detecting anxiety and depression in general medical settings. BMJ, 297, 897\u2013899.","journal-title":"BMJ"},{"key":"9789_CR15","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1002\/hbm.23018","volume":"37","author":"MJ Grothe","year":"2016","unstructured":"Grothe, M. J., & Teipel, S. J. (2016). Spatial patterns of atrophy, hypometabolism, and amyloid deposition in Alzheimer\u2019s disease correspond to dissociable functional brain networks. Human Brain Mapping, 37, 35\u201353.","journal-title":"Human Brain Mapping"},{"key":"9789_CR16","doi-asserted-by":"publisher","first-page":"144","DOI":"10.3389\/fnmol.2017.00144","volume":"10","author":"X-f He","year":"2017","unstructured":"He, X-f, Liu, D-x, Zhang, Q., et al. (2017). Voluntary exercise promotes glymphatic clearance of amyloid beta and reduces the activation of astrocytes and microglia in aged mice. Frontiers in Molecular Neuroscience, 10, 144.","journal-title":"Frontiers in Molecular Neuroscience"},{"key":"9789_CR17","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1038\/nrn2808","volume":"11","author":"VE Johnson","year":"2010","unstructured":"Johnson, V. E., Stewart, W., & Smith, D. H. (2010). Traumatic brain injury and amyloid-beta pathology: a link to Alzheimer\u2019s disease? Nature Reviews Neuroscience, 11, 361\u2013370.","journal-title":"Nature Reviews Neuroscience"},{"key":"9789_CR18","first-page":"4678","volume":"25","author":"K Koch","year":"2015","unstructured":"Koch, K., Myers, N. E., Gottler, J., et al. (2015). Disrupted intrinsic networks link amyloid-beta pathology and impaired cognition in prodromal Alzheimer\u2019s disease. Cerebral Cortex (New York, NY: 1991), 25, 4678\u20134688.","journal-title":"Cerebral Cortex (New York, NY: 1991)"},{"key":"9789_CR19","doi-asserted-by":"publisher","first-page":"14496","DOI":"10.1523\/JNEUROSCI.4004-09.2009","volume":"29","author":"AR Laird","year":"2009","unstructured":"Laird, A. R., Eickhoff, S. B., Li, K., Robin, D. A., Glahn, D. C., & Fox, P. T. (2009). Investigating the functional heterogeneity of the default mode network using coordinate-based meta-analytic modeling. The Journal of Neuroscience : the Official Journal of the Society for Neuroscience, 29, 14496\u201314505.","journal-title":"The Journal of Neuroscience : the Official Journal of the Society for Neuroscience"},{"key":"9789_CR20","doi-asserted-by":"publisher","first-page":"1074","DOI":"10.1542\/peds.2014-2391","volume":"135","author":"R Luciano","year":"2015","unstructured":"Luciano, R., Barraco, G. M., Muraca, M., et al. (2015). Biomarkers of Alzheimer disease, insulin resistance, and obesity in childhood. Pediatrics, 135, 1074\u20131081.","journal-title":"Pediatrics"},{"key":"9789_CR21","first-page":"2399","volume":"21","author":"EC Mormino","year":"2011","unstructured":"Mormino, E. C., Smiljic, A., Hayenga, A. O., et al. Relationships between beta-amyloid and functional connectivity in different components of the default mode network in aging. Cerebral Cortex (New York, NY: 1991) 2011;21:pp.\u00a02399\u20132407.","journal-title":"Cerebral Cortex (New York, NY: 1991)"},{"key":"9789_CR22","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1001\/archneur.56.3.303","volume":"56","author":"RC Petersen","year":"1999","unstructured":"Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999). Mild cognitive impairment: clinical characterization and outcome. Archives of Neurology, 56, 303\u2013308.","journal-title":"Archives of Neurology"},{"key":"9789_CR23","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1212\/WNL.0b013e31820af94e","volume":"76","author":"JR Petrella","year":"2011","unstructured":"Petrella, J. R., Sheldon, F. C., Prince, S. E., Calhoun, V. D., & Doraiswamy, P. M. (2011). Default mode network connectivity in stable vs progressive mild cognitive impairment. Neurology, 76, 511\u2013517.","journal-title":"Neurology"},{"key":"9789_CR24","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.biopsych.2009.08.024","volume":"67","author":"YI Sheline","year":"2010","unstructured":"Sheline, Y. I., Raichle, M. E., Snyder, A. Z., et al. (2010). Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biological Psychiatry, 67, 584\u2013587.","journal-title":"Biological Psychiatry"},{"key":"9789_CR25","doi-asserted-by":"publisher","first-page":"692","DOI":"10.1111\/cns.12260","volume":"20","author":"G Simic","year":"2014","unstructured":"Simic, G., Babic, M., Borovecki, F., & Hof, P. R. (2014). Early failure of the default mode network and the pathogenesis of Alzheimer\u2019s disease. CNS Neuroscience & Therapeutics, 20, 692\u2013698.","journal-title":"CNS Neuroscience & Therapeutics"},{"key":"9789_CR26","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/42.668698","volume":"17","author":"JG Sled","year":"1998","unstructured":"Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging, 17, 87\u201397.","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"9789_CR27","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1152\/jn.00338.2011","volume":"106","author":"BT Thomas Yeo","year":"2011","unstructured":"Thomas Yeo, B. T., Krienen, F. M., Sepulcre, J., et al. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125\u20131165.","journal-title":"Journal of Neurophysiology"},{"key":"9789_CR28","doi-asserted-by":"publisher","first-page":"825.e825-836","DOI":"10.1016\/j.neurobiolaging.2011.05.018","volume":"33","author":"M Tondelli","year":"2012","unstructured":"Tondelli, M., Wilcock, G. K., Nichelli, P., De Jager, C. A., Jenkinson, M., & Zamboni, G. (2012). Structural MRI changes detectable up to ten years before clinical Alzheimer\u2019s disease. Neurobiology of Aging, 33, 825.e825-836.","journal-title":"Neurobiology of Aging"},{"key":"9789_CR29","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1111\/j.1365-2796.2004.01380.x","volume":"256","author":"B Winblad","year":"2004","unstructured":"Winblad, B., Palmer, K., Kivipelto, M., et al. (2004). Mild cognitive impairment\u2013beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240\u2013246.","journal-title":"Journal of Internal Medicine"},{"key":"9789_CR30","doi-asserted-by":"crossref","unstructured":"Xu, W., Tan, L., Wang, H.-F., et al. (2015). Meta-analysis of modifiable risk factors for Alzheimer\u2019s disease. Journal of Neurology, Neurosurgery & Psychiatry, 86, 1284\u20131285.","DOI":"10.1136\/jnnp-2015-310548"}],"container-title":["Brain Imaging and Behavior"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-017-9789-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11682-017-9789-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-017-9789-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,17]],"date-time":"2020-05-17T18:16:31Z","timestamp":1589739391000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11682-017-9789-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,14]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,2]]}},"alternative-id":["9789"],"URL":"https:\/\/doi.org\/10.1007\/s11682-017-9789-5","relation":{},"ISSN":["1931-7557","1931-7565"],"issn-type":[{"value":"1931-7557","type":"print"},{"value":"1931-7565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,14]]},"assertion":[{"value":"14 December 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Assoc. Prof. Cherbuin reports no disclosures. Dr Shaw reports no disclosures. Dr Walsh reports no disclosures. Prof. Sachdev reports no disclosures. Prof. Anstey reports no disclosures.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosures"}},{"value":"All authors declare that they have no conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"All procedures performed in studies involving human participants were in accordance with the ethical standards of (and approved by) the Australian National University Ethics committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}