{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T19:19:07Z","timestamp":1769023147169,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2016,4,6]],"date-time":"2016-04-06T00:00:00Z","timestamp":1459900800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2016,4,6]],"date-time":"2016-04-06T00:00:00Z","timestamp":1459900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100004871","name":"Research Foundation for the State University of New York","doi-asserted-by":"publisher","award":["66508"],"award-info":[{"award-number":["66508"]}],"id":[{"id":"10.13039\/100004871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000084","name":"Directorate for Engineering","doi-asserted-by":"publisher","award":["CMMI1538059"],"award-info":[{"award-number":["CMMI1538059"]}],"id":[{"id":"10.13039\/100000084","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Inf."],"published-print":{"date-parts":[[2016,9]]},"DOI":"10.1007\/s40708-016-0048-0","type":"journal-article","created":{"date-parts":[[2016,4,6]],"date-time":"2016-04-06T05:55:56Z","timestamp":1459922156000},"page":"193-203","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Exploring stability-based voxel selection methods in MVPA using cognitive neuroimaging data: a comprehensive study"],"prefix":"10.1007","volume":"3","author":[{"given":"Miaolin","family":"Fan","sequence":"first","affiliation":[]},{"given":"Chun-An","family":"Chou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,4,6]]},"reference":[{"issue":"7","key":"48_CR1","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1038\/nrn1931","volume":"7","author":"JD Haynes","year":"2006","unstructured":"Haynes JD, Rees G (2006) Decoding mental states from brain activity in humans. Nat Rev Neurosci 7(7):523\u2013534","journal-title":"Nat Rev Neurosci"},{"issue":"2","key":"48_CR2","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1016\/j.neuroimage.2010.11.004","volume":"56","author":"S Lemm","year":"2011","unstructured":"Lemm S, Blankertz B, Dickhaus T, M\u00fcller KR (2011) Introduction to machine learning for brain imaging. Neuroimage 56(2):387\u2013399","journal-title":"Neuroimage"},{"issue":"1","key":"48_CR3","doi-asserted-by":"publisher","first-page":"S199","DOI":"10.1016\/j.neuroimage.2008.11.007","volume":"45","author":"F Pereira","year":"2009","unstructured":"Pereira F, Mitchell T, Botvinick M (2009) Machine learning classifiers and fmri: a tutorial overview. Neuroimage 45(1):S199\u2013S209","journal-title":"Neuroimage"},{"issue":"5539","key":"48_CR4","doi-asserted-by":"publisher","first-page":"2425","DOI":"10.1126\/science.1063736","volume":"293","author":"JV Haxby","year":"2001","unstructured":"Haxby JV, Gobbini MI, Furey ML, Ishai A, Schouten JL, Pietrini P (2001) Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293(5539):2425\u20132430","journal-title":"Science"},{"issue":"9","key":"48_CR5","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1016\/j.tics.2006.07.005","volume":"10","author":"KA Norman","year":"2006","unstructured":"Norman KA, Polyn SM, Detre GJ, Haxby JV (2006) Beyond mind-reading: multi-voxel pattern analysis of fmri data. Trends Cognit Sci 10(9):424\u2013430","journal-title":"Trends Cognit Sci"},{"issue":"1","key":"48_CR6","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/s10115-006-0040-8","volume":"12","author":"A Kalousis","year":"2007","unstructured":"Kalousis A, Prados J, Hilario M (2007) Stability of feature selection algorithms: a study on high-dimensional spaces. Knowl Inform Syst 12(1):95\u2013116","journal-title":"Knowl Inform Syst"},{"key":"48_CR7","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1007\/978-3-540-74272-2_115","volume-title":"Computer analysis of images and patterns","author":"P K\u0159i\u017eek","year":"2007","unstructured":"K\u0159i\u017eek P, Kittler J, Hlavac V (2007) Improving stability of feature selection methods. Computer analysis of images and patterns. Springer, Berlin, pp 929\u2013936"},{"issue":"4","key":"48_CR8","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1111\/j.1467-9868.2010.00740.x","volume":"72","author":"N Meinshausen","year":"2010","unstructured":"Meinshausen N, B\u00fchlmann P (2010) Stability selection. J Royal Stat Soc Ser B 72(4):417\u2013473","journal-title":"J Royal Stat Soc Ser B"},{"issue":"1","key":"48_CR9","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1111\/j.1467-9868.2011.01034.x","volume":"75","author":"RD Shah","year":"2013","unstructured":"Shah RD, Samworth RJ (2013) Variable selection with error control: another look at stability selection. J Royal Stat Soc Ser B 75(1):55\u201380","journal-title":"J Royal Stat Soc Ser B"},{"key":"48_CR10","unstructured":"Kuncheva LI (2007) A stability index for feature selection. In: Artificial intelligence and applications, pp 421\u2013427"},{"key":"48_CR11","unstructured":"Lim C, Yu B (2015) Estimation stability with cross validation (escv). J Comput Gr Stat (just-accepted)"},{"key":"48_CR12","doi-asserted-by":"crossref","unstructured":"Bach FR Bolasso: model consistent lasso estimation through the bootstrap. In: Proceedings of the 25th international conference on machine learning, pp 33\u201340. ACM (2008)","DOI":"10.1145\/1390156.1390161"},{"key":"48_CR13","doi-asserted-by":"crossref","unstructured":"Liang X, Connelly A, Calamante F (2015) A novel joint sparse partial correlation method for estimating group functional networks. Human Brain Mapp","DOI":"10.1002\/hbm.23092"},{"key":"48_CR14","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1007\/978-3-642-42057-3_70","volume-title":"Intelligence science and big data engineering","author":"Y Wang","year":"2013","unstructured":"Wang Y, Wu G, Long Z, Sheng J, Zhang J, Chen H (2013) Feature selection via sparse regression for classification of functional brain networks. Intelligence science and big data engineering. Springer, Berlin, pp 554\u2013560"},{"issue":"3","key":"48_CR15","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1016\/j.neuroimage.2010.02.082","volume":"51","author":"P Bellec","year":"2010","unstructured":"Bellec P, Rosa-Neto P, Lyttelton OC, Benali H, Evans AC (2010) Multi-level bootstrap analysis of stable clusters in resting-state fmri. Neuroimage 51(3):1126\u20131139","journal-title":"Neuroimage"},{"issue":"4","key":"48_CR16","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1109\/TAMD.2015.2427341","volume":"7","author":"Y Wang","year":"2015","unstructured":"Wang Y, Zhang S, Zheng J, Chen H, Chen H (2015) Randomized structural sparsity-based support identification with applications to locating activated or discriminative brain areas: a multicenter reproducibility study. Auton Mental Dev IEEE Trans 7(4):287\u2013300","journal-title":"Auton Mental Dev IEEE Trans"},{"key":"48_CR17","doi-asserted-by":"crossref","unstructured":"Dresler T, Fallgatter AJ (2014) Scors\u2014a method based on stability for feature selection and apping in neuroimaging. IEEE Trans Med Imag 33(1)","DOI":"10.1109\/TMI.2013.2281398"},{"issue":"143","key":"48_CR18","first-page":"10","volume":"7","author":"I Cribben","year":"2013","unstructured":"Cribben I, Wager TD, Lindquist MA (2013) Detecting functional connectivity change points for single-subject fmri data. Front Comput Neurosci 7(143):10\u20133389","journal-title":"Front Comput Neurosci"},{"issue":"4","key":"48_CR19","doi-asserted-by":"publisher","first-page":"3852","DOI":"10.1016\/j.neuroimage.2011.11.054","volume":"59","author":"S Ryali","year":"2012","unstructured":"Ryali S, Chen T, Supekar K, Menon V (2012) Estimation of functional connectivity in fmri data using stability selection-based sparse partial correlation with elastic net penalty. Neuroimage 59(4):3852\u20133861","journal-title":"Neuroimage"},{"key":"48_CR20","doi-asserted-by":"crossref","unstructured":"Hoyos-Idrobo A, Schwartz Y, Varoquaux G, Thirion B (2015) Improving sparse recovery on structured images with bagged clustering. In: Pattern Recognition in NeuroImaging (PRNI), 2015 international workshop on, pp 73\u201376. IEEE","DOI":"10.1109\/PRNI.2015.30"},{"key":"48_CR21","unstructured":"Varoquaux G, Gramfort A, Thirion B (2012) Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering. arXiv preprint \n                    arXiv:1206.6447"},{"key":"48_CR22","unstructured":"Rao N, Cox C, Nowak R, Rogers TT (2013) Sparse overlapping sets lasso for multitask learning and its application to fmri analysis. In: Advances in neural information processing systems pp 2202\u20132210"},{"issue":"3","key":"48_CR23","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1109\/JBHI.2014.2353031","volume":"19","author":"S Gopakumar","year":"2015","unstructured":"Gopakumar S, Tran T, Nguyen TD, Phung D, Venkatesh S (2015) Stabilizing high-dimensional prediction models using feature graphs. Biomed Health Inform IEEE J 19(3):1044\u20131052","journal-title":"Biomed Health Inform IEEE J"},{"key":"48_CR24","unstructured":"Tom Mitchell, W.W.: Starplus fmri data. \n                    http:\/\/www.cs.cmu.edu\/afs\/cs.cmu.edu\/project\/theo-81\/www\/\n                    \n                  ."},{"key":"48_CR25","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511895029","volume-title":"Handbook of functional MRI data analysis","author":"RA Poldrack","year":"2011","unstructured":"Poldrack RA, Mumford JA, Nichols TE (2011) Handbook of functional MRI data analysis. Cambridge University Press, Cambridge"},{"key":"48_CR26","unstructured":"MATLAB (2014) version 8.4 (R2014a). The MathWorks Inc., Natick, Massachusetts"},{"key":"48_CR27","unstructured":"Kampa K.: fmri preprocessing toolbox. \n                    https:\/\/sites.google.com\/site\/kittipat\/mvpa-for-brain-fmri\/fmri-data-preprocessing\/beta-extraction-version-1-8"},{"issue":"2","key":"48_CR28","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s12021-013-9204-3","volume":"12","author":"B Mwangi","year":"2014","unstructured":"Mwangi B, Tian TS, Soares JC (2014) A review of feature reduction techniques in neuroimaging. Neuroinformatics 12(2):229\u2013244","journal-title":"Neuroinformatics"},{"issue":"19","key":"48_CR29","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larra\u00f1aga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23(19):2507\u20132517","journal-title":"Bioinformatics"},{"key":"48_CR30","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1016\/j.snb.2015.02.025","volume":"212","author":"K Yan","year":"2015","unstructured":"Yan K, Zhang D (2015) Feature selection and analysis on correlated gas sensor data with recursive feature elimination. Sens Actuators B 212:353\u2013363","journal-title":"Sens Actuators B"},{"key":"48_CR31","doi-asserted-by":"crossref","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological) pp. 267\u2013288 (1996)","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"issue":"2","key":"48_CR32","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","volume":"67","author":"H Zou","year":"2005","unstructured":"Zou H, Hastie T (2005) Regularization and variable selection via the elastic net. J Royal Stat Soc Ser B 67(2):301\u2013320","journal-title":"J Royal Stat Soc Ser B"},{"key":"48_CR33","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1093\/sysbio\/45.3.380","volume":"45","author":"R Real","year":"1996","unstructured":"Real R, Vargas JM (1996) The probabilistic basis of Jaccard's index of similarity. Syst Biol 45:380\u2013385","journal-title":"Syst Biol"},{"issue":"4","key":"48_CR34","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1109\/TMI.2014.2298856","volume":"33","author":"CA Chou","year":"2014","unstructured":"Chou CA, Kampa K, Mehta SH, Tungaraza RF, Chaovalitwongse WA, Grabowski TJ (2014) Voxel selection framework in multi-voxel pattern analysis of fmri data for prediction of neural response to visual stimuli. Med Imag IEEE Trans 33(4):925\u2013934","journal-title":"Med Imag IEEE Trans"},{"issue":"2\u20133","key":"48_CR35","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1007\/s10898-013-0134-2","volume":"59","author":"K Kampa","year":"2014","unstructured":"Kampa K, Mehta S, Chou CA, Chaovalitwongse WA, Grabowski TJ (2014) Sparse optimization in feature selection: application in neuroimaging. J Glob Optim 59(2\u20133):439\u2013457","journal-title":"J Glob Optim"}],"container-title":["Brain Informatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40708-016-0048-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s40708-016-0048-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40708-016-0048-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s40708-016-0048-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,16]],"date-time":"2020-05-16T18:27:48Z","timestamp":1589653668000},"score":1,"resource":{"primary":{"URL":"https:\/\/braininformatics.springeropen.com\/articles\/10.1007\/s40708-016-0048-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,6]]},"references-count":35,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,9]]}},"alternative-id":["48"],"URL":"https:\/\/doi.org\/10.1007\/s40708-016-0048-0","relation":{},"ISSN":["2198-4018","2198-4026"],"issn-type":[{"value":"2198-4018","type":"print"},{"value":"2198-4026","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,4,6]]},"assertion":[{"value":"16 November 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}