{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:58:06Z","timestamp":1773248286652,"version":"3.50.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T00:00:00Z","timestamp":1642982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"The research work is financially supported by the National High Technology 863 Programs of China","award":["2015AA124103"],"award-info":[{"award-number":["2015AA124103"]}]},{"name":"National Key R&D Program","award":["2016YFB05502001"],"award-info":[{"award-number":["2016YFB05502001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Topogr"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s10548-021-00884-8","type":"journal-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T11:03:16Z","timestamp":1643022196000},"page":"507-524","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Examining the Effects of Normal Ageing on Cortical Connectivity of Older Adults"],"prefix":"10.1007","volume":"35","author":[{"given":"Muhammad Aamir","family":"Panhwar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Mohsin","family":"Pathan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nasrullah","family":"Pirzada","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad Aashed Khan","family":"Abbasi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deng","family":"ZhongLiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ghazala","family":"Panhwar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,24]]},"reference":[{"key":"884_CR1","doi-asserted-by":"crossref","first-page":"105942","DOI":"10.1016\/j.optlastec.2019.105942","volume":"124","author":"AA Abd EL-Latif","year":"2020","unstructured":"Abd EL-Latif AA, Abd-El-Atty B, Abou-Nassar EM, Venegas-Andraca SE (2020) Controlled alternate quantum walks based privacy preserving healthcare images in Internet of Things. Opt Laser Technol 124:105942","journal-title":"Opt Laser Technol"},{"issue":"1","key":"884_CR2","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1523\/JNEUROSCI.3874-05.2006","volume":"26","author":"S Achard","year":"2006","unstructured":"Achard S, Salvador R, Whitcher B, Suckling J (2006) Ed Bullmore A Resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci 26(1):63\u201372. https:\/\/doi.org\/10.1523\/JNEUROSCI.3874-05.2006","journal-title":"J Neurosci"},{"key":"884_CR3","doi-asserted-by":"crossref","first-page":"184","DOI":"10.3389\/fnagi.2018.00184","volume":"10","author":"O Al Zoubi","year":"2018","unstructured":"Al Zoubi O, Ki Wong C, Kuplicki RT, Yeh HW, Mayeli A, Refai H et al (2018) Predicting age from brain EEG signals\u2014a machine learning approach. Front Aging Neurosci 10:184","journal-title":"Front Aging Neurosci"},{"issue":"6","key":"884_CR4","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1136\/gutjnl-2017-315940","volume":"68","author":"LJ Alferink","year":"2018","unstructured":"Alferink LJ, Kiefte-de Jong JC, Erler NS, Veldt BJ, Schoufour JD, de Knegt RJ et al (2018) Association of dietary macronutrient composition and non-alcoholic fatty liver disease in an ageing population: the Rotterdam Study. Gut 68(6):1088\u20131098","journal-title":"Gut"},{"issue":"1","key":"884_CR5","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1038\/nrn.2017.149","volume":"19","author":"A Avena-Koenigsberger","year":"2018","unstructured":"Avena-Koenigsberger A, Misic B, Sporns O (2018) Communication dynamics in complex brain networks. Nat Rev Neurosci 19(1):17","journal-title":"Nat Rev Neurosci"},{"issue":"2","key":"884_CR6","first-page":"510","volume":"12","author":"Y Camchong","year":"2019","unstructured":"Camchong Y, Roy A, Gilmore C, Thao M, Kazynski M, Fiecas M, Lim K (2019) Using brain stimulation to modify a brain network and support abstinence during alcohol use disorder recovery. Brain Stimul Basic Transl Clin Res Neuromodulation 12(2):510","journal-title":"Brain Stimul Basic Transl Clin Res Neuromodulation"},{"issue":"2","key":"884_CR7","first-page":"1","volume":"24","author":"JH Cole","year":"2018","unstructured":"Cole JH, Marioni RE, Harris SE, Deary IJ (2018a) Brain age and other bodily \u2018ages\u2019: implications for neuropsychiatry. Mol Psychiatry 24(2):1","journal-title":"Mol Psychiatry"},{"issue":"5","key":"884_CR8","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.1038\/mp.2017.62","volume":"23","author":"JH Cole","year":"2018","unstructured":"Cole JH, Ritchie SJ, Bastin ME, Hern\u00e1ndez MV, Maniega SM, Royle N, Wray NR (2018b) Brain age predicts mortality. Mol Psychiatry 23(5):1385","journal-title":"Mol Psychiatry"},{"key":"884_CR9","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.bcp.2018.10.030","volume":"158","author":"S Daniele","year":"2018","unstructured":"Daniele S, Giacomelli C, Martini C (2018) Brain ageing and neurodegenerative disease: the role of cellular waste management. Biochem Pharmacol 158:207\u2013216","journal-title":"Biochem Pharmacol"},{"issue":"50","key":"884_CR10","doi-asserted-by":"crossref","first-page":"5454","DOI":"10.1080\/00036846.2018.1486996","volume":"50","author":"B Gannon","year":"2018","unstructured":"Gannon B, Banks J, Nazroo J, Munford L (2018) An econometric analysis of cognitive impairment and healthcare utilization in the ageing population. Appl Econ 50(50):5454\u20135463","journal-title":"Appl Econ"},{"issue":"6","key":"884_CR11","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1111\/ejn.13527","volume":"47","author":"A Giuliano","year":"2018","unstructured":"Giuliano A, Saviozzi I, Brambilla P, Muratori F, Retico A, Calderoni S (2018) The effect of age, sex and clinical features on the volume of Corpus Callosum in pre-schoolers with Autism Spectrum Disorder: a case\u2013control study. Eur J Neurosci 47(6):568\u2013578","journal-title":"Eur J Neurosci"},{"issue":"6","key":"884_CR12","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1016\/j.clinph.2018.02.133","volume":"129","author":"F Gobert","year":"2018","unstructured":"Gobert F, Dailler F, Fischer C, Andr\u00e9-Obadia N, Luaut\u00e9 J (2018) Proving cortical death after vascular coma: evoked potentials, EEG and Neuroimaging. Clin Neurophysiol 129(6):1105\u20131116","journal-title":"Clin Neurophysiol"},{"issue":"01","key":"884_CR13","doi-asserted-by":"crossref","first-page":"1750032","DOI":"10.1142\/S0129065717500320","volume":"28","author":"J Gomez-Pilar","year":"2018","unstructured":"Gomez-Pilar J, Poza J, Bachiller A, G\u00f3mez C, N\u00fa\u00f1ez P, Lubeiro A, Hornero R (2018) Quantification of graph complexity based on the edge weight distribution balance: application to brain networks. Int J Neural Syst 28(01):1750032","journal-title":"Int J Neural Syst"},{"issue":"1","key":"884_CR14","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1111\/disa.12233","volume":"42","author":"MW Horner","year":"2018","unstructured":"Horner MW, Ozguven EE, Marcelin JM, Kocatepe A (2018) Special needs hurricane shelters and the ageing population: development of a methodology and a case study application. Disasters 42(1):169\u2013186","journal-title":"Disasters"},{"key":"884_CR15","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.jhealeco.2017.11.001","volume":"57","author":"D Howdon","year":"2018","unstructured":"Howdon D, Rice N (2018) Health care expenditures, age, proximity to death and morbidity: implications for an ageing population. J Health Econ 57:60\u201374","journal-title":"J Health Econ"},{"key":"884_CR16","doi-asserted-by":"publisher","first-page":"12386","DOI":"10.1109\/access.2019.2893063","volume":"7","author":"H Huang","year":"2019","unstructured":"Huang H, Meng F, Zhou S, Jiang F, Manogaran G (2019) Brain image segmentation based on FCM clustering algorithm and rough set. IEEE Access 7:12386\u201312396. https:\/\/doi.org\/10.1109\/access.2019.2893063","journal-title":"IEEE Access"},{"key":"884_CR17","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.2011.1959","author":"R Kanai","year":"2011","unstructured":"Kanai R, Bahrami B, Roylance R, Rees G (2011) Online social network size is reflected in human brain structure. Proc R Soc. https:\/\/doi.org\/10.1098\/rspb.2011.1959","journal-title":"Proc R Soc"},{"key":"884_CR18","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.yebeh.2017.09.027","volume":"78","author":"S Kemp","year":"2018","unstructured":"Kemp S, Prendergast G, Karapanagiotidis T, Baker G, Kelly TP, Patankar T, Keller SS (2018) Concordance between the Wada test and neuroimaging lateralization: influence of imaging modality (fMRI and MEG) and patient experience. Epilepsy Behav 78:155\u2013160","journal-title":"Epilepsy Behav"},{"key":"884_CR19","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neuropsychologia.2018.01.001","volume":"118","author":"YN Kenett","year":"2018","unstructured":"Kenett YN, Medaglia JD, Beaty RE, Chen Q, Betzel RF, Thompson-Schill SL, Qiu J (2018) Driving the brain towards creativity and intelligence: a network control theory analysis. Neuropsychologia 118:79\u201390","journal-title":"Neuropsychologia"},{"issue":"1","key":"884_CR20","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1186\/s41747-018-0055-4","volume":"2","author":"N Klasson","year":"2018","unstructured":"Klasson N, Olsson E, Eckerstr\u00f6m C, Malmgren H, Wallin A (2018) Estimated intracranial volume from FreeSurfer is biased by total brain volume. Eur Radiol Exp 2(1):24","journal-title":"Eur Radiol Exp"},{"key":"884_CR21","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.jpsychires.2018.02.012","volume":"99","author":"M Kolenic","year":"2018","unstructured":"Kolenic M, Franke K, Hlinka J, Matejka M, Capkova J, Pausova Z, Hajek T (2018) Obesity, dyslipidemia and brain age in first-episode psychosis. J Psychiatr Res 99:151\u2013158","journal-title":"J Psychiatr Res"},{"issue":"11","key":"884_CR22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0141840","volume":"10","author":"XZ Kong","year":"2015","unstructured":"Kong XZ, Liu Z, Huang L, Wang X, Yang Z, Zhou G, Liu J (2015) Mapping individual brain networks using statistical similarity in regional morphology from MRI. PLoS ONE 10(11):e0141840. https:\/\/doi.org\/10.1371\/journal.pone.0141840","journal-title":"PLoS ONE"},{"issue":"22","key":"884_CR23","first-page":"E5154","volume":"115","author":"XZ Kong","year":"2018","unstructured":"Kong XZ, Mathias SR, Guadalupe T, Glahn DC, Franke B, Crivello F, ENIGMA Laterality Working Group 2018 (2018) Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium. Proc Natl Acad Sci USA 115(22):E5154\u2013E5163","journal-title":"Proc Natl Acad Sci USA"},{"issue":"5","key":"884_CR24","doi-asserted-by":"crossref","first-page":"306","DOI":"10.4236\/jbbs.2018.85019","volume":"8","author":"JJ Lee-Park","year":"2018","unstructured":"Lee-Park JJ, Deshpande H, Lisinski J, LaConte S, Ramey S, DeLuca S (2018) Neuroimaging strategies addressing challenges in using fMRI for the children with cerebral palsy. J Behav Brain Sci 8(5):306\u2013318","journal-title":"J Behav Brain Sci"},{"issue":"2","key":"884_CR25","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1109\/TCBB.2016.2635144","volume":"15","author":"J Liu","year":"2018","unstructured":"Liu J, Li M, Lan W, Wu FX, Pan Y, Wang J (2018) Classification of Alzheimer\u2019s disease using whole brain hierarchical network. IEEE\/ACM Trans Comput Biol Bioinform 15(2):624\u2013632","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"884_CR26","doi-asserted-by":"crossref","first-page":"14736","DOI":"10.1109\/ACCESS.2019.2893275","volume":"7","author":"D Liu","year":"2019","unstructured":"Liu D, Yu X, Feng Q, Chen W, Manogaran G (2019) Brain image segmentation based on multi-weight probability map. IEEE Access 7:14736\u201314746","journal-title":"IEEE Access"},{"key":"884_CR27","doi-asserted-by":"crossref","first-page":"e35237","DOI":"10.7554\/eLife.35237","volume":"7","author":"RB Mars","year":"2018","unstructured":"Mars RB, Sotiropoulos SN, Passingham RE, Sallet J, Verhagen L, Khrapitchev AA et al (2018) Whole brain comparative anatomy using connectivity blueprints. Elife 7:e35237","journal-title":"Elife"},{"key":"884_CR28","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.nicl.2018.02.006","volume":"18","author":"LK McEvoy","year":"2018","unstructured":"McEvoy LK, Fennema-Notestine C, Elman JA, Eyler LT, Franz CE, Hagler DJ Jr et al (2018) Alcohol intake and brain white matter in middle aged men: microscopic and macroscopic differences. NeuroImage Clin 18:390\u2013398","journal-title":"NeuroImage Clin"},{"issue":"1","key":"884_CR29","doi-asserted-by":"crossref","first-page":"49","DOI":"10.17116\/sudmed201861149-51","volume":"61","author":"YE Morozov","year":"2018","unstructured":"Morozov YE, Velenko PS (2018) The characteristic of protein biosynthesis in brain neurons with chronic alcohol intoxication. Sudebno Meditsinskaiaekspertiza 61(1):49\u201351","journal-title":"Sudebno Meditsinskaiaekspertiza"},{"key":"884_CR30","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.neubiorev.2017.11.012","volume":"84","author":"VI M\u00fcller","year":"2018","unstructured":"M\u00fcller VI, Cieslik EC, Laird AR, Fox PT, Radua J, Mataix-Cols D et al (2018) Ten simple rules for neuroimaging meta-analysis. Neurosci Biobehav Rev 84:151\u2013161","journal-title":"Neurosci Biobehav Rev"},{"issue":"2","key":"884_CR31","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.tics.2017.11.003","volume":"22","author":"RA Poldrack","year":"2018","unstructured":"Poldrack RA, Monahan J, Imrey PB, Reyna V, Raichle ME, Faigman D, Buckholtz JW (2018) Predicting violent behavior: what can neuroscience add? Trends Cogn Sci 22(2):111\u2013123","journal-title":"Trends Cogn Sci"},{"key":"884_CR32","doi-asserted-by":"crossref","unstructured":"Rajkumar S, Bardhan P, Akkireddy SK, Munshi C (2014) CT and MRI image fusion based on Wavelet Transform and Neuro-Fuzzy concepts with quantitative analysis. In: 2014 International conference on electronics and communication systems (ICECS), 2014, pp 1\u20136","DOI":"10.1109\/ECS.2014.6892544"},{"key":"884_CR33","first-page":"355","volume":"10","author":"A Sanjay","year":"2017","unstructured":"Sanjay A, Soundrapandiyan R, Karuppiah M, Ganapathy R (2017) CT and MRI image fusion based on discrete wavelet transform and type-2 fuzzy logic. Int J Intell Eng Syst 10:355\u2013362","journal-title":"Int J Intell Eng Syst"},{"issue":"4","key":"884_CR34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00429-019-01848-2","volume":"224","author":"I Shamir","year":"2019","unstructured":"Shamir I, Tomer O, Baratz Z, Tsarfaty G, Faraggi M, Horowitz A, Assaf Y (2019) A framework for cortical laminar composition analysis using low-resolution T1 MRI images. Brain Struct Funct 224(4):1\u201311","journal-title":"Brain Struct Funct"},{"issue":"10","key":"884_CR35","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1038\/s41593-018-0234-x","volume":"21","author":"MD Sweeney","year":"2018","unstructured":"Sweeney MD, Kisler K, Montagne A, Toga AW, Zlokovic BV (2018) The role of brain vasculature in neurodegenerative disorders. Nat Neurosci 21(10):1318","journal-title":"Nat Neurosci"},{"issue":"10","key":"884_CR36","doi-asserted-by":"crossref","first-page":"2981","DOI":"10.1093\/brain\/awy223","volume":"141","author":"C Tangwiriyasakul","year":"2018","unstructured":"Tangwiriyasakul C, Perani S, Centeno M, Yaakub SN, Abela E, Carmichael DW, Richardson MP (2018) Dynamic brain network states in human generalized spike-wave discharges. Brain 141(10):2981\u20132994","journal-title":"Brain"},{"issue":"5","key":"884_CR37","doi-asserted-by":"crossref","first-page":"1030","DOI":"10.1016\/j.radcr.2018.04.010","volume":"13","author":"CJJ Yeo","year":"2018","unstructured":"Yeo CJJ, Hutton GJ, Fung SH (2018) Advanced neuroimaging in Balo\u2019s concentric sclerosis: MRI, MRS, DTI, and ASL perfusion imaging over 1 year. Radiol Case Rep 13(5):1030\u20131035","journal-title":"Radiol Case Rep"},{"key":"884_CR38","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1016\/j.neuroimage.2018.06.047","volume":"185","author":"T Zhao","year":"2018","unstructured":"Zhao T, Mishra V, Jeon T, Ouyang M, Peng Q, Chalak L, Huang H (2018) Structural network maturation of the preterm human brain. Neuroimage 185:699\u2013710","journal-title":"Neuroimage"}],"container-title":["Brain Topography"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10548-021-00884-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10548-021-00884-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10548-021-00884-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T15:31:55Z","timestamp":1659108715000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10548-021-00884-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,24]]},"references-count":38,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["884"],"URL":"https:\/\/doi.org\/10.1007\/s10548-021-00884-8","relation":{},"ISSN":["0896-0267","1573-6792"],"issn-type":[{"value":"0896-0267","type":"print"},{"value":"1573-6792","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,24]]},"assertion":[{"value":"29 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}