{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T04:13:15Z","timestamp":1759032795437},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,10,6]],"date-time":"2013-10-06T00:00:00Z","timestamp":1381017600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Multidim Syst Sign Process"],"published-print":{"date-parts":[[2015,1]]},"DOI":"10.1007\/s11045-013-0254-3","type":"journal-article","created":{"date-parts":[[2013,10,5]],"date-time":"2013-10-05T07:34:28Z","timestamp":1380958468000},"page":"225-241","source":"Crossref","is-referenced-by-count":1,"title":["Voxel selection and neural decoding of fMRI data based on robust sparse programming with multi-dimensional derivative constraints"],"prefix":"10.1007","volume":"26","author":[{"given":"Zhuliang","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bao","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenghui","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenxia","family":"Xue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanqing","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2013,10,6]]},"reference":[{"issue":"1","key":"254_CR1","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1137\/060676489","volume":"30","author":"BW Bader","year":"2007","unstructured":"Bader, B. W., & Kolda, T. G. (2007). Efficient MATLAB computations with sparse and factored tensors. SIAM Journal on Scientific Computing, 30(1), 205\u2013231.","journal-title":"SIAM Journal on Scientific Computing"},{"key":"254_CR2","doi-asserted-by":"crossref","unstructured":"Bandettini, P. A., Wong, E. C., Hinks, R. S., Tikofsky, R. S., & Hyde, J. S. (1992). Time course EPI of human brain function during task activation. Magnetic Resonance in Medicine, 25(2), 390\u2013397.","DOI":"10.1002\/mrm.1910250220"},{"issue":"4","key":"254_CR3","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1006\/nimg.2001.0873","volume":"14","author":"RM Birn","year":"2001","unstructured":"Birn, R. M., Saad, Z. S., & Bandettini, P. A. (2001). Spatial heterogeneity of the nonlinear dynamics in the fMRI BOLD response. NeuroImage, 14(4), 817\u2013826.","journal-title":"NeuroImage"},{"issue":"4","key":"254_CR4","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.1016\/j.neuroimage.2010.12.028","volume":"55","author":"F Bunea","year":"2011","unstructured":"Bunea, F., She, Y., Ombao, H., Gongvatana, A., Devlin, K., & Cohen, R. (2011). Penalized least squares regression methods and applications to neuroimaging. NeuroImage, 55(4), 1519\u20131527.","journal-title":"NeuroImage"},{"issue":"6","key":"254_CR5","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1002\/mrm.1910390602","volume":"39","author":"RB Buxton","year":"1998","unstructured":"Buxton, R. B., Wong, E. C., & Frank, L. R. (1998). Dynamics of blood flow and oxygenation changes during brain activation: The balloon model. Magnetic Resonance in Medicine, 39(6), 855\u2013864.","journal-title":"Magnetic Resonance in Medicine"},{"issue":"5","key":"254_CR6","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1162\/jocn.2003.15.5.704","volume":"15","author":"TA Carlson","year":"2003","unstructured":"Carlson, T. A., Schrater, P., & He, S. (2003). Patterns of activity in the categorical representations of objects. Journal of Cognitive Neuroscience, 15(5), 704\u2013717.","journal-title":"Journal of Cognitive Neuroscience"},{"issue":"1","key":"254_CR7","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.neuroimage.2008.08.020","volume":"44","author":"MK Carroll","year":"2009","unstructured":"Carroll, M. K., Cecchi, G. A., Rish, I., Garg, R., & Rao, A. R. (2009). Prediction and interpretation of distributed neural activity with sparse models. NeuroImage, 44(1), 112\u2013122.","journal-title":"NeuroImage"},{"issue":"7","key":"254_CR8","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/0166-2236(94)90055-8","volume":"17","author":"MS Cohen","year":"1994","unstructured":"Cohen, M. S., & Bookheimer, S. Y. (1994). Localization of brain function using magnetic resonance imaging. Trends in Neurosciences, 17(7), 268\u2013277.","journal-title":"Trends in Neurosciences"},{"issue":"2","key":"254_CR9","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/S1053-8119(03)00049-1","volume":"19","author":"DD Cox","year":"2003","unstructured":"Cox, D. D., & Savoy, R. L. (2003). Functional magnetic resonance imaging (fMRI) brain reading: Detecting and classifying distributed patterns of fMRI activity in human visual cortex. NeuroImage, 19(2), 261\u2013270.","journal-title":"NeuroImage"},{"issue":"4","key":"254_CR10","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1006\/nimg.2000.0630","volume":"12","author":"KJ Friston","year":"2000","unstructured":"Friston, K. J., Mechelli, A., Turner, R., & Price, C. J. (2000). Nonlinear responses in fMRI: The balloon model, volterra kernels, and other hemodynamics. NeuroImage, 12(4), 466\u2013477.","journal-title":"NeuroImage"},{"key":"254_CR11","unstructured":"Friston, K. J., Ashburner, J. T., Kiebel, S. J., Nichols, T. E., & Penny, W. D. (2007). Statistical parametric mapping: The analysis of funtional brain images. Amsterdam: Academic Press."},{"issue":"6","key":"254_CR12","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1109\/TNSRE.2008.926701","volume":"16","author":"L Grosenick","year":"2008","unstructured":"Grosenick, L., Greer, S., & Knutson, B. (2008). Interpretable classifiers for fMRI improve prediction of purchases. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(6), 539\u2013548.","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"issue":"4","key":"254_CR13","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s11045-010-0119-y","volume":"21","author":"X Guo","year":"2010","unstructured":"Guo, X., Wan, Q., Chang, C., & Lam, E. Y. (2010). Source localization using a sparse representation framework to achieve superresolution. Multidimensional Systems and Signal Processing, 21(4), 391\u2013402.","journal-title":"Multidimensional Systems and Signal Processing"},{"issue":"2\u20133","key":"254_CR14","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.neuroimage.2008.02.005","volume":"41","author":"LM Harrison","year":"2008","unstructured":"Harrison, L. M., Penny, W., Daunizeau, J., & Friston, K. J. (2008). Diffusion-based spatial priors for functional magnetic resonance images. NeuroImage, 41(2\u20133), 408.","journal-title":"NeuroImage"},{"issue":"3","key":"254_CR15","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s11045-011-0147-2","volume":"23","author":"L Jiang","year":"2012","unstructured":"Jiang, L., & Yin, H. (2012). Bregman iteration algorithm for sparse nonnegative matrix factorizations via alternating l1-norm minimization. Multidimensional Systems and Signal Processing, 23(3), 315\u2013328.","journal-title":"Multidimensional Systems and Signal Processing"},{"issue":"2","key":"254_CR16","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.neuroimage.2005.01.048","volume":"26","author":"S LaConte","year":"2005","unstructured":"LaConte, S., Strother, S., Cherkassky, V., Anderson, J., & Hu, X. (2005). Support vector machines for temporal classification of block design fMRI data. NeuroImage, 26(2), 317.","journal-title":"NeuroImage"},{"issue":"10","key":"254_CR17","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.1109\/TBME.2009.2025866","volume":"56","author":"Y Li","year":"2009","unstructured":"Li, Y., Namburi, P., Yu, Z., Guan, C., Feng, J., & Gu, Z. (2009). Voxel selection in fMRI data analysis based on sparse representation. IEEE Transactions on Biomedical Engineering, 56(10), 2439\u20132451.","journal-title":"IEEE Transactions on Biomedical Engineering"},{"issue":"6843","key":"254_CR18","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1038\/35084005","volume":"412","author":"NK Logothetis","year":"2001","unstructured":"Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412(6843), 150\u2013157.","journal-title":"Nature"},{"issue":"10","key":"254_CR19","doi-asserted-by":"crossref","first-page":"3963","DOI":"10.1523\/JNEUROSCI.23-10-03963.2003","volume":"23","author":"NK Logothetis","year":"2003","unstructured":"Logothetis, N. K. (2003). The underpinnings of the BOLD functional magnetic resonance imaging signal. The Journal of Neuroscience, 23(10), 3963\u20133971.","journal-title":"The Journal of Neuroscience"},{"issue":"1","key":"254_CR20","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1023\/B:MACH.0000035475.85309.1b","volume":"57","author":"TM Mitchell","year":"2004","unstructured":"Mitchell, T. M., Hutchinson, R., Niculescu, R. S., Pereira, F., Wang, X., Just, M., et al. (2004). Learning to decode cognitive states from brain images. Machine Learning, 57(1), 145\u2013175.","journal-title":"Machine Learning"},{"issue":"1","key":"254_CR21","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/TBME.2010.2104321","volume":"59","author":"VP Oikonomou","year":"2012","unstructured":"Oikonomou, V. P., Blekas, K., & Astrakas, L. (2012). A sparse and spatially constrained generative regression model for fMRI data analysis. IEEE Transactions on Biomedical Engineering, 59(1), 58\u201367.","journal-title":"IEEE Transactions on Biomedical Engineering"},{"issue":"4","key":"254_CR22","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1162\/0898929053467550","volume":"17","author":"AJ O\u2019toole","year":"2005","unstructured":"O\u2019toole, A. J., Jiang, F., Abdi, H., & Haxby, J. V. (2005). Partially distributed representations of objects and faces in ventral temporal cortex. Journal of Cognitive Neuroscience, 17(4), 580\u2013590.","journal-title":"Journal of Cognitive Neuroscience"},{"issue":"10","key":"254_CR23","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1111\/j.1467-9280.2005.01618.x","volume":"16","author":"DA Pizzagalli","year":"2005","unstructured":"Pizzagalli, D. A., Sherwood, R. J., Henriques, J. B., & Davidson, R. J. (2005). Frontal brain asymmetry and reward responsiveness a source-localization study. Psychological Science, 16(10), 805\u2013813.","journal-title":"Psychological Science"},{"issue":"10","key":"254_CR24","doi-asserted-by":"crossref","first-page":"812","DOI":"10.1038\/nrn1521","volume":"5","author":"C Rorden","year":"2004","unstructured":"Rorden, C., & Karnath, H. O. (2004). Using human brain lesions to infer function: A relic from a past era in the fMRI age? Nature Reviews Neuroscience, 5(10), 812\u2013819.","journal-title":"Nature Reviews Neuroscience"},{"issue":"6","key":"254_CR25","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1016\/S0896-6273(02)00877-2","volume":"35","author":"M Spiridon","year":"2002","unstructured":"Spiridon, M., & Kanwisher, N. (2002). How distributed is visual category information in human occipito-temporal cortex? An fMRI study. Neuron, 35(6), 1157\u20131166.","journal-title":"Neuron"},{"issue":"2","key":"254_CR26","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/j.neuroimage.2008.04.262","volume":"42","author":"KE Stephan","year":"2008","unstructured":"Stephan, K. E., Kasper, L., Harrison, L. M., Daunizeau, J., den Ouden, H. E. M., Breakspear, M., et al. (2008). Nonlinear dynamic causal models for fMRI. NeuroImage, 42(2), 649\u2013662.","journal-title":"NeuroImage"},{"issue":"4","key":"254_CR27","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1006\/nimg.2001.1034","volume":"15","author":"SC Strother","year":"2002","unstructured":"Strother, S. C., Anderson, J., Hansen, L. K., Kjems, U., Kustra, R., Sidtis, J., et al. (2002). The quantitative evaluation of functional neuroimaging experiments: The NPAIRS data analysis framework. NeuroImage, 15(4), 747\u2013771.","journal-title":"NeuroImage"},{"key":"254_CR28","doi-asserted-by":"crossref","unstructured":"Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society, Series B: Methodological, 58(1), 267\u2013288.","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"issue":"2","key":"254_CR29","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1006\/nimg.1997.0316","volume":"7","author":"AL Vazquez","year":"1998","unstructured":"Vazquez, A. L., & Noll, D. C. (1998). Nonlinear aspects of the BOLD response in functional MRI. NeuroImage, 7(2), 108\u2013118.","journal-title":"NeuroImage"},{"issue":"4","key":"254_CR30","doi-asserted-by":"crossref","first-page":"1414","DOI":"10.1016\/j.neuroimage.2008.05.050","volume":"42","author":"O Yamashita","year":"2008","unstructured":"Yamashita, O., Sato, M., Yoshioka, T., Tong, F., & Kamitani, Y. (2008). Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns. NeuroImage, 42(4), 1414\u20131429.","journal-title":"NeuroImage"},{"issue":"1","key":"254_CR31","first-page":"95","volume":"17","author":"FZ Yetkin","year":"1996","unstructured":"Yetkin, F. Z., McAuliffe, T. L., Cox, R., & Haughton, V. M. (1996). Test-retest precision of functional MR in sensory and motor task activation. American Journal of Neuroradiology, 17(1), 95\u201398.","journal-title":"American Journal of Neuroradiology"},{"key":"254_CR32","doi-asserted-by":"crossref","unstructured":"Yu, Z., Gu, Z., & Li, Y. (2011). A sparse voxel selection approach for fMRI data analysis with multi-dimensional derivative constraints. In Multidimensional (nD) systems (nDs), (2011). 7th international workshop on. IEEE, 2011, pp. 1\u20134.","DOI":"10.1109\/nDS.2011.6076846"}],"container-title":["Multidimensional Systems and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11045-013-0254-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11045-013-0254-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11045-013-0254-3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,29]],"date-time":"2019-07-29T05:51:54Z","timestamp":1564379514000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11045-013-0254-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,10,6]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2015,1]]}},"alternative-id":["254"],"URL":"https:\/\/doi.org\/10.1007\/s11045-013-0254-3","relation":{},"ISSN":["0923-6082","1573-0824"],"issn-type":[{"value":"0923-6082","type":"print"},{"value":"1573-0824","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,10,6]]}}}