{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T03:39:47Z","timestamp":1769744387920,"version":"3.49.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2018,5,7]],"date-time":"2018-05-07T00:00:00Z","timestamp":1525651200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Digit Imaging"],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1007\/s10278-018-0093-8","type":"journal-article","created":{"date-parts":[[2018,5,7]],"date-time":"2018-05-07T14:05:32Z","timestamp":1525701932000},"page":"895-903","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":122,"title":["Combination of rs-fMRI and sMRI Data to Discriminate Autism Spectrum Disorders in Young Children Using Deep Belief Network"],"prefix":"10.1007","volume":"31","author":[{"given":"Maryam","family":"Akhavan Aghdam","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2441-9477","authenticated-orcid":false,"given":"Arash","family":"Sharifi","sequence":"additional","affiliation":[]},{"given":"Mir Mohsen","family":"Pedram","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,5,7]]},"reference":[{"issue":"2","key":"93_CR1","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1097\/WCO.0b013e3282f49579","volume":"21","author":"I Rapin","year":"2008","unstructured":"Rapin I, Tuchman RF: What is new in autism? Curr Opin Neurol. Apr 1 21(2):143\u2013149, 2008","journal-title":"Curr Opin Neurol"},{"key":"93_CR2","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.3174\/ajnr.A2800","volume":"33","author":"S Mueller","year":"2012","unstructured":"Mueller S, Keeser D, Reiser MF, Teipel S, Meindl T: Functional and Structural MR Imaging in Neuropsychiatric Disorders, Part 2: Application in Schizophrenia and Autism. AJNR Am J Neuroradiol 33:2033\u20132037, 2012","journal-title":"AJNR Am J Neuroradiol"},{"key":"93_CR3","unstructured":"Office of Special Education Programs, United States Department Of Education, Twenty-Seventh Annual Report to Congress on the Implementation of the Individuals with Dis- abilities Education Act, 2005."},{"issue":"9701","key":"93_CR4","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1016\/S0140-6736(09)61376-3","volume":"374","author":"SE Levy","year":"2009","unstructured":"Levy SE, Mandell DS, Schultz RT: Autism. The Lancet 374(9701):1627\u20131638, 2009","journal-title":"The Lancet"},{"key":"93_CR5","doi-asserted-by":"crossref","unstructured":"Coleman M, Gillberg C: The Autisms. Oxford; Oxford University Press, 2012","DOI":"10.1093\/med\/9780199732128.001.0001"},{"key":"93_CR6","volume-title":"Rethinking Autism: Variation and Complexity","author":"L Waterhouse","year":"2013","unstructured":"Waterhouse L: Rethinking Autism: Variation and Complexity. London: Academic Press, 2013"},{"key":"93_CR7","doi-asserted-by":"publisher","first-page":"33","DOI":"10.2147\/CLEP.S41714","volume":"5","author":"E Fernell","year":"2013","unstructured":"Fernell E, Eriksson MA, Gillberg C: Early diagnosis of autism and impact on prognosis: a narrative review. Clin. Epidemiol. 5:33\u201343, 2013","journal-title":"Clin. Epidemiol."},{"key":"93_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2014\/327271","volume":"2014","author":"Malinda L. Pennington","year":"2014","unstructured":"Pennington ML, Cullinan D, Southern LB, Defining Autism: Variability in State Education Agency Definitions of and Evaluations for Autism Spectrum Disorders, 2014. Available at: \n                    https:\/\/doi.org\/10.1155\/2014\/327271\n                    \n                  ,","journal-title":"Autism Research and Treatment"},{"key":"93_CR9","doi-asserted-by":"crossref","unstructured":"Saniano M, Pellegrino L, Casadio M, Summa S, Garbanio E, Rossi V, Dall\u2019Agata D, Sanguineti V, Natural interface and virtual environments for the acquisition of street crossing and path following skills in adults with Autism Spectrum Disorders: a feasibility study. J Neuroeng Rehabil, 2015.","DOI":"10.1186\/s12984-015-0010-z"},{"issue":"4","key":"93_CR10","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1002\/aur.204","volume":"4","author":"BE Yerys","year":"2011","unstructured":"Yerys BE, Pennington BF: How do we establish a biological marker for a behaviorally defined disorder? Autism as a test case. Autism Res. 4(4):239\u2013241, 2011","journal-title":"Autism Res."},{"key":"93_CR11","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.nicl.2014.12.013","volume":"7","author":"M Plitt","year":"2015","unstructured":"Plitt M, Barnes KA, Martin A: Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards. Neuroimage Clin. 7:359\u2013366, 2015","journal-title":"Neuroimage Clin."},{"key":"93_CR12","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.3174\/ajnr.A2800","volume":"33","author":"S Mueller","year":"2012","unstructured":"Mueller S, Keeser D, Reiser MF, Teipel S, Meindl T: Functional and Structural MR Imaging in Neuropsychiatric Disorders, Part 1: Imaging Techniques and Their Application in Mild Cognitive Impairment and Alzheimer Disease. AJNR Am J Neuroradiol 33:2033\u20132037, 2012","journal-title":"AJNR Am J Neuroradiol"},{"issue":"12","key":"93_CR13","doi-asserted-by":"publisher","first-page":"3742","DOI":"10.1093\/brain\/awr263","volume":"134","author":"JS Anderson","year":"2011","unstructured":"Anderson JS, Nielsen JA, Froehlich AL, DuBray MB, Druzgal TJ, Cariello AN, Cooperrider JR, Zielinski BA, Ravichandran C, Fletcher PT, Alexander AL: Functional connectivity magnetic resonance imaging classification of autism. Brain. 134(12):3742\u20133754, 2011","journal-title":"Brain."},{"issue":"8","key":"93_CR14","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1001\/jamapsychiatry.2013.104","volume":"70","author":"LQ Uddin","year":"2013","unstructured":"Uddin LQ, Supekar K, Lynch CJ, Khouzam A, Phillips J, Feinstein C, Ryali S, Menon V: Salience network-based classification and prediction of symptom severity in children with autism. JAMA Psychiatry 70(8):869\u2013879, 2013","journal-title":"JAMA Psychiatry"},{"key":"93_CR15","doi-asserted-by":"publisher","first-page":"599","DOI":"10.3389\/fnhum.2013.00599","volume":"7","author":"JA Nielsen","year":"2013","unstructured":"Nielsen JA, Zielinski BA et al.: Multisite functional connectivity MRI classification of autism: ABIDE results. Front Hum Neurosci 7 (September:599, 2013","journal-title":"Front Hum Neurosci"},{"key":"93_CR16","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1016\/j.nicl.2015.04.002","volume":"8","author":"CP Chen","year":"2015","unstructured":"Chen CP, Keown CL, Jahedi A, Nair A, Pflieger ME, Bailey BA, M\u00fcller RA: Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism. Neuroimage Clin. 8:238\u2013245, 2015","journal-title":"Neuroimage Clin."},{"issue":"12","key":"93_CR17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0166934","volume":"11","author":"S Ghiassian","year":"2016","unstructured":"Ghiassian S, Greiner R, Jin P, Brown MRG: Using Functional or Structural Magnetic Resonance Images and Personal Characteristic Data to Identify ADHD and Autism. PLoS ONE. 11(12):e0166934, 2016","journal-title":"PLoS ONE."},{"issue":"4","key":"93_CR18","doi-asserted-by":"publisher","first-page":"929","DOI":"10.1007\/s00429-012-0439-9","volume":"218","author":"E Greimel","year":"2013","unstructured":"Greimel E, Nehrkorn B, Schulte-R\u00fcther M, Fink GR, Nickl-Jockschat T, Herpertz-Dahlmann B, Konrad K, Eickhoff SB: Changes in grey matter development in autism spectrum disorder. Brain Struct Funct. 218(4):929\u2013942, 2013","journal-title":"Brain Struct Funct."},{"issue":"7","key":"93_CR19","doi-asserted-by":"publisher","first-page":"e00483","DOI":"10.1002\/brb3.483","volume":"6","author":"M Wilkinson","year":"2016","unstructured":"Wilkinson M, Wang R, van der Kouwe A, Takahashi E: White and gray matter fiber pathways in autism spectrum disorder revealed by ex vivo diffusion MR tractography. Brain Behav 6(7):e00483, 2016","journal-title":"Brain Behav"},{"issue":"1","key":"93_CR20","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/j.nicl.2012.09.001","volume":"1","author":"R Bakhtiari","year":"2012","unstructured":"Bakhtiari R, Z\u00fcrcher NR, Rogier O, Russo B, Hippolyte L, Granziera C, Araabi BN, Nili Ahmadabadi M, Hadjikhani N: Differences in white matter reflect atypical developmental trajectory in autism: A Tract-based Spatial Statistics study. Neuroimage Clin. 1(1):48\u201356, 2012","journal-title":"Neuroimage Clin."},{"issue":"2","key":"93_CR21","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1177\/155005940803900206","volume":"39","author":"RW McCarley","year":"2008","unstructured":"McCarley RW, Nakamura M, Shenton ME, Salisbury DF: Combining ERP and structural MRI information in first episode schizophrenia and bipolar disorder. Clin EEG Neurosci 39(2):57\u201360, 2008","journal-title":"Clin EEG Neurosci"},{"issue":"3","key":"93_CR22","doi-asserted-by":"publisher","first-page":"2626","DOI":"10.1016\/j.neuroimage.2009.08.056","volume":"49","author":"AM Michael","year":"2010","unstructured":"Michael AM, Baum SA, White T, Demirci O, Andreasen NC, Segall JM, Jung RE, Pearlson G, Clark VP, Gollub RL, Schulz SC, Roffman JL, Lim KO, Ho BC, Bockholt HJ, Calhoun VD: Does function follow form? Methods to fuse structural and functional brain images show decreased linkage in schizophrenia. Neuroimage. 49(3):2626\u20132637, 2010","journal-title":"Neuroimage."},{"issue":"3","key":"93_CR23","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1016\/j.neuroimage.2011.05.055","volume":"57","author":"J Sui","year":"2011","unstructured":"Sui J, Pearlson G, Caprihan A, Adali T, Kiehl KA, Liu J, Yamamoto J, Calhoun VD: Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+joint ICA model. Neuroimage. 57(3):839\u2013855, 2011","journal-title":"Neuroimage."},{"key":"93_CR24","doi-asserted-by":"crossref","unstructured":"Sui J, He H, Yu Q, Chen J, Rogers J, Pearlson G, Mayer A, Bustillo J, Canive J, Calhoun VD, Combination of resting state fMRI, DTI, and sMRI data to discriminate schizophrenia by N-way MCCA + jICA. Fron Hum Neurosci, 7,2013.","DOI":"10.3389\/fnhum.2013.00235"},{"issue":"8","key":"93_CR25","doi-asserted-by":"publisher","first-page":"2192","DOI":"10.1162\/neco.2010.08-09-1081","volume":"22","author":"N Roux Le","year":"2010","unstructured":"Le Roux N, Bengio Y: Deep belief networks are compact universal approximators. Neural Comput. 22(8):2192\u20132207, 2010","journal-title":"Neural Comput."},{"key":"93_CR26","doi-asserted-by":"crossref","unstructured":"Plis SM, Hjelm D, Salakhutdinov R, Allen EA, Bockholt HJ, Long JD, Johnson HJ, Paulsen J, Turner JA, Calhoun VD: Deep learning for neuroimaging: a validation study. Front Neurosci, 8, 2014.","DOI":"10.3389\/fnins.2014.00229"},{"key":"93_CR27","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1016\/j.neuroimage.2014.06.077","volume":"101","author":"Heung-Il Suk","year":"2014","unstructured":"Suk HI, Lee SW, Shen D: Hierarchical feature representation and multimodal fusion with deep learning for AD\/MCI diagnosis. Neuroimage. 101:569\u2013582, 2014 Available at: \n                    https:\/\/doi.org\/10.1016\/j.neuroimage.2014.06.077","journal-title":"NeuroImage"},{"issue":"2","key":"93_CR28","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1007\/s00429-013-0687-3","volume":"220","author":"HI Suk","year":"2015","unstructured":"Suk HI, Lee SW, Shen D: Latent feature representation with stacked auto-encoder for AD\/MCI diagnosis. Brain Struct Func 220(2):841\u2013859, 2015","journal-title":"Brain Struct Func"},{"key":"93_CR29","unstructured":"Sarraf S, Tofighi G, Classification of Alzheimer\u2019s Disease Using fMRI Data and Deep Learning Convolutional Neural Networks 2016. Available at: \n                    https:\/\/arxiv.org\/pdf\/1603.08631.pdf"},{"key":"93_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2016\/3049632","volume":"2016","author":"Shan Pang","year":"2016","unstructured":"Pang S, Yang X: Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification. Comput Intell Neurosci. 2016:1\u201310, 2016. Available at: \n                    https:\/\/doi.org\/10.1155\/2016\/3049632","journal-title":"Computational Intelligence and Neuroscience"},{"key":"93_CR31","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1007\/s10278-017-9983-4","volume":"30","author":"Z Akkus","year":"2017","unstructured":"Akkus Z, Galimzianova A, Hoogi A, Rubin DL, Erickson BJ: Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions. J Digit Imaging 30:449\u2013459, 2017","journal-title":"J Digit Imaging"},{"key":"93_CR32","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1038\/381607a0","volume":"381","author":"BA Olshausen","year":"1996","unstructured":"Olshausen BA: Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381:607\u2013609, 1996","journal-title":"Nature"},{"issue":"5786","key":"93_CR33","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR: Reducing the dimensionality of data with neural networks. Science 313(5786):504\u2013507, 2006","journal-title":"Science"},{"issue":"7","key":"93_CR34","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Osindero S, Teh YW: A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527\u20131554, 2006","journal-title":"Neural Comput"},{"key":"93_CR35","doi-asserted-by":"crossref","unstructured":"Kuang D, Guo X, An X, Zhao Y, He L: Discrimination of ADHD based on fMRI data with Deep Belief Network. In: International Conference on Intelligent Computing, Aug 3.Springer, Cham, 2014, pp 225\u2013232","DOI":"10.1007\/978-3-319-09330-7_27"},{"key":"93_CR36","doi-asserted-by":"publisher","unstructured":"Di Martino A, Yan CG, Li Q, Denio E, Castellanos FX et al.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol. Psychiatry 19(6):659\u2013667, 2014 Available at: \n                    https:\/\/doi.org\/10.1038\/mp.2013.7823774715","DOI":"10.1038\/mp.2013.7823774715"},{"key":"93_CR37","unstructured":"Autism Brain Imaging Data Exchange, http:\/\/fcon_1000.projects.nitrc.org\/indi\/abide\/, accessed at 1\/10\/2017"},{"key":"93_CR38","unstructured":"Available at: \n                    http:\/\/www.fil.ion.ucl.ac.uk\/spm\/software\/spm8\/"},{"key":"93_CR39","unstructured":"Jenkinson M, Smith SM: Pre-Processing of BOLD FMRI Data. Oxford University Centre for Functional MRI of the Brain (FMRIB), 2006."},{"issue":"4","key":"93_CR40","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.nic.2007.09.002","volume":"17","author":"F. DuBois Bowman","year":"2007","unstructured":"Bowman FD, Guo Y, Derado G: Statistical Approaches to Functional Neuroimaging Data. Neuroimaging Clin 17(4, 2007):441\u2013viii. \n                    https:\/\/doi.org\/10.1016\/j.nic.2007.09.002","journal-title":"Neuroimaging Clinics of North America"},{"issue":"1","key":"93_CR41","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","volume":"15","author":"N Tzourio-Mazoyer","year":"2002","unstructured":"Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M: Automated Anatomical Labeling of activations in SPM using a Macroscopic Anatomical Parcellation of the MNI MRI single-subject brain. NeuroImage. 15(1):273\u2013289, 2002","journal-title":"NeuroImage."},{"key":"93_CR42","unstructured":"Available at: \n                    http:\/\/deeplearning.net\/tutorial\/code\/\n                    \n                   (LISA lab, University of Montreal, 2015)."},{"issue":"2","key":"93_CR43","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1148\/rg.2017160130","volume":"37","author":"BJ Erickson","year":"2017","unstructured":"Erickson BJ, Korfiatis P, Akkus Z, Kline TL: Machine Learning for Medical Imaging. RadioGraphics. Feb 17 37(2):505\u2013515, 2017","journal-title":"RadioGraphics"},{"key":"93_CR44","unstructured":"Available at: \n                    https:\/\/docs.scipy.org\/doc\/scipy-0.15.1\/reference\/generated\/scipy.stats.ttest_ind.html"},{"key":"93_CR45","doi-asserted-by":"crossref","unstructured":"Katuwal GJ, Cahill ND, Baum SA, Michael AM: The predictive power of structural MRI in Autism diagnosis. In 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); 2015, p 4270\u20134273","DOI":"10.1109\/EMBC.2015.7319338"},{"issue":"3\u20135","key":"93_CR46","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/S0736-5748(02)00053-9","volume":"20","author":"H Cody","year":"2002","unstructured":"Cody H, Pelphrey K, Piven J: Structural and functional magnetic resonance imaging of autism. Int J Dev Neurosci 20(3\u20135):421\u2013438, 2002","journal-title":"Int J Dev Neurosci"},{"key":"93_CR47","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.ijdevneu.2015.02.007","volume":"46","author":"MR Bennett","year":"2015","unstructured":"Bennett MR, Lagopoulos J: Neurodevelopmental sequelae associated with gray and white matter changes and their cellular basis: A comparison between Autism Spectrum Disorder, ADHD and dyslexia. Int J Dev Neurosci 46:132\u2013143, 2015","journal-title":"Int J Dev Neurosci"},{"issue":"2","key":"93_CR48","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1097\/WCO.0b013e32833782d4","volume":"23","author":"NJ Minshew","year":"2010","unstructured":"Minshew NJ, Keller TA: The nature of brain dysfunction in autism: functional brain imaging studies. Curr Opin Neurol 23(2):124\u2013130, 2010","journal-title":"Curr Opin Neurol"},{"key":"93_CR49","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun Y, Bengio Y, Hinton G: Deep learning. Nature 521:436\u2013444, 2015","journal-title":"Nature"},{"key":"93_CR50","doi-asserted-by":"publisher","first-page":"38897","DOI":"10.1038\/srep38897","volume":"6","author":"WH Pinaya","year":"2016","unstructured":"Pinaya WH, Gadelha A, Doyle OM, Noto C, Zugman A, Cordeiro Q, Jackowski AP, Bressan RA, Sato JR: Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia. Sci Rep Dec 12 6:38897, 2016","journal-title":"Sci Rep"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10278-018-0093-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-018-0093-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-018-0093-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,7]],"date-time":"2019-05-07T12:30:52Z","timestamp":1557232252000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10278-018-0093-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,7]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,12]]}},"alternative-id":["93"],"URL":"https:\/\/doi.org\/10.1007\/s10278-018-0093-8","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,5,7]]},"assertion":[{"value":"7 May 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}