{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T03:43:50Z","timestamp":1790221430304,"version":"4.1.0"},"reference-count":47,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62271177"],"award-info":[{"award-number":["62271177"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004731","name":"Zhejiang Province Natural Science Foundation","doi-asserted-by":"publisher","award":["LZ24F010007"],"award-info":[{"award-number":["LZ24F010007"]}],"id":[{"id":"10.13039\/501100004731","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014041","name":"Alzheimer's Disease Neuroimaging Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014041","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003467","name":"Hangzhou Dianzi University","doi-asserted-by":"publisher","award":["IRB-2020001"],"award-info":[{"award-number":["IRB-2020001"]}],"id":[{"id":"10.13039\/501100003467","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017542","name":"Beijing Hospital","doi-asserted-by":"publisher","award":["2022BJYYEC-375-01"],"award-info":[{"award-number":["2022BJYYEC-375-01"]}],"id":[{"id":"10.13039\/501100017542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ibroneuroscience.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neuroscience"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1016\/j.neuroscience.2025.08.059","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T00:32:42Z","timestamp":1756945962000},"page":"313-322","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":3,"special_numbering":"C","title":["Cognitive prediction using regional connectivities and network biomarkers in Alzheimer\u2019s disease"],"prefix":"10.1016","volume":"585","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7662-9126","authenticated-orcid":false,"given":"Jinhua","family":"Sheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jialei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruilin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.neuroscience.2025.08.059_b0005","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1002\/hbm.22213","article-title":"Amyloid and its association with default network integrity in Alzheimer\u2019s disease","volume":"35","author":"Adriaanse","year":"2014","journal-title":"Hum. Brain Mapp."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0010","doi-asserted-by":"crossref","first-page":"1249","DOI":"10.1007\/s11042-014-2123-y","article-title":"Classification of Alzheimer\u2019s disease subjects from MRI using hippocampal visual features","volume":"74","author":"Ben Ahmed","year":"2015","journal-title":"Multimed. Tools Appl."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0015","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1503\/jpn.180016","article-title":"An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures","volume":"44","author":"Bhagwat","year":"2019","journal-title":"J. Psychiatry Neurosci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0020","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1038\/nrn2575","article-title":"Complex brain networks: graph theoretical analysis of structural and functional systems","volume":"10","author":"Bullmore","year":"2009","journal-title":"Nat. Rev. Neurosci."},{"issue":"1","key":"10.1016\/j.neuroscience.2025.08.059_b0025","article-title":"Lithium-ion batteries remaining useful life prediction based on BLS-RVM","volume":"234","author":"Chen","year":"2021","journal-title":"Energy"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0030","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.neuroimage.2017.07.059","article-title":"Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker","volume":"163","author":"Cole","year":"2017","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0035","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1016\/j.neuroimage.2018.06.001","article-title":"The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features","volume":"178","author":"Cui","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0040","unstructured":"Dubois, J., Galdi, P., Paul, L.K., Adolphs, R. A distributed brain network predicts general intelligence from resting-state human neuroimaging data."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0045","doi-asserted-by":"crossref","DOI":"10.1126\/scitranslmed.aag2882","article-title":"Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age","volume":"9","author":"Emerson","year":"2017","journal-title":"Sci. Transl. Med."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0050","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1093\/cercor\/bhac189","article-title":"Determining four confounding factors in individual cognitive traits prediction with functional connectivity: an exploratory study","volume":"33","author":"Feng","year":"2023","journal-title":"Cereb. Cortex"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2019.116038","article-title":"Combining multiple connectomes improves predictive modeling of phenotypic measures","volume":"201","author":"Gao","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0060","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.intell.2017.06.004","article-title":"Brain volume and intelligence: the moderating role of intelligence measurement quality","volume":"64","author":"Gignac","year":"2017","journal-title":"Intelligence"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0065","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/nature18933","article-title":"A multi-modal parcellation of human cerebral cortex","volume":"536","author":"Glasser","year":"2016","journal-title":"Nature"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0070","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1016\/j.neuroimage.2010.03.043","article-title":"A common neural scale for the subjective pleasantness of different primary rewards","volume":"51","author":"Grabenhorst","year":"2010","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0075","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.neuroimage.2013.10.067","article-title":"On the interpretation of weight vectors of linear models in multivariate neuroimaging","volume":"87","author":"Haufe","year":"2014","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0080","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.neuroimage.2018.10.006","article-title":"Mapping the human brain\u2019s cortical-subcortical functional network organization","volume":"185","author":"Ji","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0085","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1109\/MSP.2022.3155951","article-title":"Interpreting Brain Biomarkers: challenges and solutions in interpreting machine learning-based predictive neuroimaging","volume":"39","author":"Jiang","year":"2022","journal-title":"IEEE Signal Process Mag."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0090","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1017\/S0140525X07001185","article-title":"The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence","volume":"30","author":"Jung","year":"2007","journal-title":"Behav. Brain Sci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0095","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1007\/s12264-020-00560-0","article-title":"Visuospatial memory alteration in Alzheimer\u2019s disease","volume":"36","author":"Lin","year":"2020","journal-title":"Neurosci. Bull."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0100","doi-asserted-by":"crossref","first-page":"94","DOI":"10.3389\/fnagi.2018.00094","article-title":"Resting-state functional connectivity predicts cognitive impairment related to Alzheimer\u2019s disease","volume":"10","author":"Lin","year":"2018","journal-title":"Front. Aging Neurosci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0105","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1038\/nature06976","article-title":"What we can do and what we cannot do with fMRI","volume":"453","author":"Logothetis","year":"2008","journal-title":"Nature"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0110","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.nicl.2016.12.011","article-title":"Rey\u2019s auditory verbal learning test scores can be predicted from whole brain MRI in Alzheimer\u2019s disease","volume":"13","author":"Moradi","year":"2017","journal-title":"NeuroImage: Clinical"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0115","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1016\/j.neuron.2011.09.006","article-title":"Functional network organization of the human brain","volume":"72","author":"Power","year":"2011","journal-title":"Neuron"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0120","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.neuroimage.2009.12.025","article-title":"Impairment and compensation coexist in amnestic MCI default mode network","volume":"50","author":"Qi","year":"2010","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0125","doi-asserted-by":"crossref","DOI":"10.1136\/gpsych-2022-100751","article-title":"The China Alzheimer report 2022","volume":"35","author":"Ren","year":"2022","journal-title":"Gen. Psych."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0130","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1002\/hbm.26089","article-title":"The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation","volume":"44","author":"Rolls","year":"2023","journal-title":"Hum. Brain Mapp."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0135","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1176\/ajp.141.11.1356","article-title":"A new rating scale for Alzheimer\u2019s disease","volume":"141","author":"Rosen Wilma","year":"1984","journal-title":"AJP"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0140","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/nn.4179","article-title":"A neuromarker of sustained attention from whole-brain functional connectivity","volume":"19","author":"Rosenberg","year":"2016","journal-title":"Nat. Neurosci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0145","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.1604378113","article-title":"Morphometricity as a measure of the neuroanatomical signature of a trait","volume":"113","author":"Sabuncu","year":"2016","journal-title":"PNAS"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0150","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1038\/nprot.2016.178","article-title":"Using connectome-based predictive modeling to predict individual behavior from brain connectivity","volume":"12","author":"Shen","year":"2017","journal-title":"Nat. Protoc."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0155","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.bbr.2019.03.004","article-title":"A novel joint HCPMMP method for automatically classifying Alzheimer\u2019s and different stage MCI patients","volume":"365","author":"Sheng","year":"2019","journal-title":"Behav. Brain Res."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0160","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1038\/s41598-022-06444-9","article-title":"Predictive classification of Alzheimer\u2019s disease using brain imaging and genetic data","volume":"12","author":"Sheng","year":"2022","journal-title":"Sci. Rep."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0165","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1186\/s13195-020-00716-0","article-title":"Prognosis prediction model for conversion from mild cognitive impairment to Alzheimer\u2019s disease created by integrative analysis of multi-omics data","volume":"12","author":"Shigemizu","year":"2020","journal-title":"Alz. Res. Therapy"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0170","doi-asserted-by":"crossref","DOI":"10.1111\/adb.12969","article-title":"Resting\u2010state connectome\u2010based support\u2010vector\u2010machine predictive modeling of internet gaming disorder","volume":"26","author":"Song","year":"2021","journal-title":"Addict. Biol."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0175","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1016\/j.neuroimage.2010.03.051","article-title":"Predicting clinical scores from magnetic resonance scans in Alzheimer\u2019s disease","volume":"51","author":"Stonnington","year":"2010","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0180","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1152\/jn.00338.2011","article-title":"The organization of the human cerebral cortex estimated by intrinsic functional connectivity","volume":"106","author":"Thomas Yeo","year":"2011","journal-title":"J. Neurophysiol."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0185","first-page":"211","article-title":"Sparse Bayesian learning and the relevance vector machine","volume":"1","author":"Tipping","year":"2001","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0190","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0013701","article-title":"Comparing brain networks of different size and connectivity density using graph theory","volume":"5","author":"Van Wijk","year":"2010","journal-title":"PLoS One"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0195","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1038\/nn.4478","article-title":"Building better biomarkers: brain models in translational neuroimaging","volume":"20","author":"Woo","year":"2017","journal-title":"Nat. Neurosci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0200","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1177\/1745691617693393","article-title":"Choosing prediction over explanation in psychology: lessons from machine learning","volume":"12","author":"Yarkoni","year":"2017","journal-title":"Perspect. Psychol. Sci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0205","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1109\/TNSRE.2018.2828143","article-title":"Modulation of spectral power and functional connectivity in human brain by acupuncture stimulation","volume":"26","author":"Yu","year":"2018","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0210","doi-asserted-by":"crossref","DOI":"10.1109\/TFUZZ.2019.2903753","article-title":"Supervised network-based fuzzy learning of EEG signals for Alzheimer\u2019s disease identification","volume":"28","author":"Yu","year":"2020","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0215","doi-asserted-by":"crossref","first-page":"2450","DOI":"10.1109\/TNSRE.2024.3421648","article-title":"Evaluation of acupuncture efficacy in modulating brain activity with periodic-aperiodic EEG measurements","volume":"32","author":"Yu","year":"2024","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"6","key":"10.1016\/j.neuroscience.2025.08.059_b0220","doi-asserted-by":"crossref","first-page":"4147","DOI":"10.1109\/JBHI.2025.3530922","article-title":"Neural manifold decoder for acupuncture stimulation","volume":"29","author":"Yu","year":"2025","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0225","doi-asserted-by":"crossref","DOI":"10.3389\/fnagi.2021.708687","article-title":"Convergent functional changes of default mode network in mild cognitive impairment using activation likelihood estimation","volume":"13","author":"Yuan","year":"2021","journal-title":"Front. Aging Neurosci."},{"key":"10.1016\/j.neuroscience.2025.08.059_b0230","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1016\/j.neuroimage.2011.08.049","article-title":"Altered spontaneous activity in Alzheimer\u2019s disease and mild cognitive impairment revealed by regional homogeneity","volume":"59","author":"Zhang","year":"2012","journal-title":"Neuroimage"},{"key":"10.1016\/j.neuroscience.2025.08.059_b0235","doi-asserted-by":"crossref","DOI":"10.1016\/j.jneumeth.2021.109376","article-title":"Diagnosis of Alzheimer\u2019s disease based on regional attention with sMRI gray matter slices","volume":"365","author":"Zhang","year":"2022","journal-title":"J. Neurosci. Methods"}],"container-title":["Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306452225009078?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306452225009078?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T22:29:58Z","timestamp":1772836198000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306452225009078"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":47,"alternative-id":["S0306452225009078"],"URL":"https:\/\/doi.org\/10.1016\/j.neuroscience.2025.08.059","relation":{},"ISSN":["0306-4522"],"issn-type":[{"value":"0306-4522","type":"print"}],"subject":[],"published":{"date-parts":[[2025,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Cognitive prediction using regional connectivities and network biomarkers in Alzheimer\u2019s disease","name":"articletitle","label":"Article Title"},{"value":"Neuroscience","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neuroscience.2025.08.059","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}