{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T07:07:57Z","timestamp":1791443277466,"version":"4.3.3"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,4,3]],"date-time":"2020-04-03T00:00:00Z","timestamp":1585872000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,4,3]],"date-time":"2020-04-03T00:00:00Z","timestamp":1585872000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["R01-MH098899"],"award-info":[{"award-number":["R01-MH098899"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health","doi-asserted-by":"publisher","award":["R01-MH098899"],"award-info":[{"award-number":["R01-MH098899"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1533623"],"award-info":[{"award-number":["1533623"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1533623"],"award-info":[{"award-number":["1533623"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"U.S. Department of Health & Human Services | NIH | National Institute of Mental Health"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Commun"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>When learning about dynamic and uncertain environments, people should update their beliefs most strongly when new evidence is most informative, such as when the environment undergoes a surprising change or existing beliefs are highly uncertain. Here we show that modulations of surprise and uncertainty are encoded in a particular, temporally dynamic pattern of whole-brain functional connectivity, and this encoding is enhanced in individuals that adapt their learning dynamics more appropriately in response to these factors. The key feature of this whole-brain pattern of functional connectivity is stronger connectivity, or functional integration, between the fronto-parietal and other functional systems. Our results provide new insights regarding the association between dynamic adjustments in learning and dynamic, large-scale changes in functional connectivity across the brain.<\/jats:p>","DOI":"10.1038\/s41467-020-15442-2","type":"journal-article","created":{"date-parts":[[2020,4,3]],"date-time":"2020-04-03T06:06:32Z","timestamp":1585893992000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Functional brain network reconfiguration during learning in a dynamic environment"],"prefix":"10.1038","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2928-302X","authenticated-orcid":false,"given":"Chang-Hao","family":"Kao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankit N.","family":"Khambhati","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6183-4493","authenticated-orcid":false,"given":"Danielle S.","family":"Bassett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5397-535X","authenticated-orcid":false,"given":"Matthew R.","family":"Nassar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6259-0809","authenticated-orcid":false,"given":"Joseph T.","family":"McGuire","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6018-0483","authenticated-orcid":false,"given":"Joshua I.","family":"Gold","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph W.","family":"Kable","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,4,3]]},"reference":[{"key":"15442_CR1","doi-asserted-by":"publisher","first-page":"12366","DOI":"10.1523\/JNEUROSCI.0822-10.2010","volume":"30","author":"MR Nassar","year":"2010","unstructured":"Nassar, M. R., Wilson, R. C., Heasly, B. & Gold, J. I. An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment. J. Neurosci. 30, 12366\u201312378 (2010).","journal-title":"J. Neurosci."},{"key":"15442_CR2","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1016\/j.neuron.2014.10.013","volume":"84","author":"JT McGuire","year":"2014","unstructured":"McGuire, J. T., Nassar, M. R., Gold, J. I. & Kable, J. W. Functionally dissociable influences on learning rate in a dynamic environment. Neuron 84, 870\u2013881 (2014).","journal-title":"Neuron"},{"key":"15442_CR3","doi-asserted-by":"publisher","first-page":"1040","DOI":"10.1038\/nn.3130","volume":"15","author":"MR Nassar","year":"2012","unstructured":"Nassar, M. R. et al. Rational regulation of learning dynamics by pupil-linked arousal systems. Nat. Neurosci. 15, 1040\u20131046 (2012).","journal-title":"Nat. Neurosci."},{"key":"15442_CR4","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1038\/nn1954","volume":"10","author":"TEJ Behrens","year":"2007","unstructured":"Behrens, T. E. J., Woolrich, M. W., Walton, M. E. & Rushworth, M. F. S. Learning the value of information in an uncertain world. Nat. Neurosci. 10, 1214\u20131221 (2007).","journal-title":"Nat. Neurosci."},{"key":"15442_CR5","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-017-02169-w","volume":"8","author":"D Meder","year":"2017","unstructured":"Meder, D. et al. Simultaneous representation of a spectrum of dynamically changing value estimates during decision making. Nat. Commun. 8, 1942 (2017).","journal-title":"Nat. Commun."},{"key":"15442_CR6","doi-asserted-by":"publisher","first-page":"E3660","DOI":"10.1073\/pnas.1305373110","volume":"110","author":"JX O\u2019Reilly","year":"2013","unstructured":"O\u2019Reilly, J. X. et al. Dissociable effects of surprise and model update in parietal and anterior cingulate cortex. Proc. Natl Acad. Sci. USA 110, E3660\u2013E3669 (2013).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"15442_CR7","first-page":"1688","volume":"39","author":"MR Nassar","year":"2019","unstructured":"Nassar, M. R., McGuire, J. T., Ritz, H. & Kable, J. W. Dissociable forms of uncertainty-driven representational change across the human brain. J. Neurosci. 39, 1688\u20131698 (2019).","journal-title":"J. Neurosci."},{"key":"15442_CR8","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1089\/brain.2011.0008","volume":"1","author":"KJ Friston","year":"2011","unstructured":"Friston, K. J. Functional and effective connectivity: a review. Brain Connect. 1, 13\u201336 (2011).","journal-title":"Brain Connect."},{"key":"15442_CR9","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1038\/nn.4502","volume":"20","author":"DS Bassett","year":"2017","unstructured":"Bassett, D. S. & Sporns, O. Network neuroscience. Nat. Neurosci. 20, 353\u2013364 (2017).","journal-title":"Nat. Neurosci."},{"key":"15442_CR10","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/nrn2575","volume":"10","author":"E Bullmore","year":"2009","unstructured":"Bullmore, E. & Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10, 186 (2009).","journal-title":"Nat. Rev. Neurosci."},{"key":"15442_CR11","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1162\/jocn_a_00810","volume":"27","author":"JD Medaglia","year":"2015","unstructured":"Medaglia, J. D., Lynall, M.-E. & Bassett, D. S. Cognitive network neuroscience. J. Cogn. Neurosci. 27, 1471\u20131491 (2015).","journal-title":"J. Cogn. Neurosci."},{"key":"15442_CR12","doi-asserted-by":"publisher","first-page":"7641","DOI":"10.1073\/pnas.1018985108","volume":"108","author":"DS Bassett","year":"2011","unstructured":"Bassett, D. S. et al. Dynamic reconfiguration of human brain networks during learning. Proc. Natl Acad. Sci. 108, 7641\u20137646 (2011).","journal-title":"Proc. Natl Acad. Sci."},{"key":"15442_CR13","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1038\/nn.3993","volume":"18","author":"DS Bassett","year":"2015","unstructured":"Bassett, D. S., Yang, M., Wymbs, N. F. & Grafton, S. T. Learning-induced autonomy of sensorimotor systems. Nat. Neurosci. 18, 744\u2013751 (2015).","journal-title":"Nat. Neurosci."},{"key":"15442_CR14","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.neuroimage.2018.01.037","volume":"172","author":"MG Mattar","year":"2018","unstructured":"Mattar, M. G. et al. Predicting future learning from baseline network architecture. NeuroImage 172, 107\u2013117 (2018).","journal-title":"NeuroImage"},{"key":"15442_CR15","doi-asserted-by":"publisher","first-page":"2442","DOI":"10.1523\/JNEUROSCI.2084-17.2018","volume":"38","author":"RT Gerraty","year":"2018","unstructured":"Gerraty, R. T. et al. Dynamic flexibility in striatal-cortical circuits supports reinforcement learning. J. Neurosci. 38, 2442\u20132453 (2018).","journal-title":"J. Neurosci."},{"key":"15442_CR16","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1162\/netn_a_00021","volume":"2","author":"MG Mattar","year":"2018","unstructured":"Mattar, M. G., Thompson-Schill, S. L. & Bassett, D. S. The network architecture of value learning. Netw. Neurosci. 2, 128\u2013149 (2018).","journal-title":"Netw. Neurosci."},{"key":"15442_CR17","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/j.neuron.2014.05.005","volume":"83","author":"G Antzoulatos Evan","year":"2014","unstructured":"Antzoulatos Evan, G. & Miller Earl, K. Increases in functional connectivity between prefrontal cortex and striatum during category learning. Neuron 83, 216\u2013225 (2014).","journal-title":"Neuron"},{"key":"15442_CR18","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1523\/JNEUROSCI.4759-06.2007","volume":"27","author":"EH Baeg","year":"2007","unstructured":"Baeg, E. H. et al. Learning-induced enduring changes in functional connectivity among prefrontal cortical neurons. J. Neurosci. 27, 909\u2013918 (2007).","journal-title":"J. Neurosci."},{"key":"15442_CR19","doi-asserted-by":"publisher","first-page":"1538","DOI":"10.1126\/science.283.5407.1538","volume":"283","author":"C B\u00fcchel","year":"1999","unstructured":"B\u00fcchel, C., Coull, J. T. & Friston, K. J. The predictive value of changes in effective connectivity for human learning. Science 283, 1538\u20131541 (1999).","journal-title":"Science"},{"key":"15442_CR20","doi-asserted-by":"publisher","first-page":"3911","DOI":"10.1002\/hbm.23285","volume":"37","author":"Z Fatima","year":"2016","unstructured":"Fatima, Z., Kovacevic, N., Misic, B. & McIntosh, A. R. Dynamic functional connectivity shapes individual differences in associative learning. Hum. Brain Mapp. 37, 3911\u20133928 (2016).","journal-title":"Hum. Brain Mapp."},{"key":"15442_CR21","doi-asserted-by":"publisher","first-page":"17558","DOI":"10.1073\/pnas.0902455106","volume":"106","author":"CM Lewis","year":"2009","unstructured":"Lewis, C. M., Baldassarre, A., Committeri, G., Romani, G. L. & Corbetta, M. Learning sculpts the spontaneous activity of the resting human brain. Proc. Natl Acad. Sci. USA 106, 17558\u201317563 (2009).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"15442_CR22","doi-asserted-by":"publisher","first-page":"1227","DOI":"10.1093\/cercor\/bhl033","volume":"17","author":"FT Sun","year":"2006","unstructured":"Sun, F. T., Miller, L. M., Rao, A. A. & D'esposito, M. Functional connectivity of cortical networks involved in bimanual motor sequence learning. Cereb. Cortex 17, 1227\u20131234 (2006).","journal-title":"Cereb. Cortex"},{"key":"15442_CR23","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1038\/44565","volume":"401","author":"DD Lee","year":"1999","unstructured":"Lee, D. D. & Seung, H. S. Learning the parts of objects by non-negative matrix factorization. Nature 401, 788\u2013791 (1999).","journal-title":"Nature"},{"key":"15442_CR24","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1162\/NETN_a_00001","volume":"1","author":"LR Chai","year":"2017","unstructured":"Chai, L. R. et al. Evolution of brain network dynamics in neurodevelopment. Netw. Neurosci. 1, 14\u201330 (2017).","journal-title":"Netw. Neurosci."},{"key":"15442_CR25","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/j.neuroimage.2017.11.015","volume":"166","author":"AN Khambhati","year":"2018","unstructured":"Khambhati, A. N., Mattar, M. G., Wymbs, N. F., Grafton, S. T. & Bassett, D. S. Beyond modularity: Fine-scale mechanisms and rules for brain network reconfiguration. NeuroImage 166, 385\u2013399 (2018).","journal-title":"NeuroImage"},{"key":"15442_CR26","doi-asserted-by":"publisher","first-page":"e1006234","DOI":"10.1371\/journal.pcbi.1006234","volume":"14","author":"AN Khambhati","year":"2018","unstructured":"Khambhati, A. N., Medaglia, J. D., Karuza, E. A., Thompson-Schill, S. L. & Bassett, D. S. Subgraphs of functional brain networks identify dynamical constraints of cognitive control. PLOS Comput. Biol. 14, e1006234 (2018).","journal-title":"PLOS Comput. Biol."},{"key":"15442_CR27","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1016\/j.neuron.2011.09.006","volume":"72","author":"JD Power","year":"2011","unstructured":"Power, J. D. et al. Functional network organization of the human brain. Neuron 72, 665\u2013678 (2011).","journal-title":"Neuron"},{"key":"15442_CR28","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms11609","volume":"7","author":"MR Nassar","year":"2016","unstructured":"Nassar, M. R. et al. Age differences in learning emerge from an insufficient representation of uncertainty in older adults. Nat. Commun. 7, 11609 (2016).","journal-title":"Nat. Commun."},{"key":"15442_CR29","doi-asserted-by":"publisher","first-page":"e5","DOI":"10.1017\/pen.2018.4","volume":"1","author":"S Tompson","year":"2018","unstructured":"Tompson, S., Falk, E. B., Vettel, J. M. & Bassett, D. S. Network approaches to understand individual differences in brain connectivity: opportunities for personality neuroscience. Personal. Neurosci. 1, e5 (2018).","journal-title":"Personal. Neurosci."},{"key":"15442_CR30","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1177\/1073858414525995","volume":"20","author":"MW Cole","year":"2014","unstructured":"Cole, M. W., Repov\u0161, G. & Anticevic, A. The frontoparietal control system: a central role in mental health. Neuroscientist 20, 652\u2013664 (2014).","journal-title":"Neuroscientist"},{"key":"15442_CR31","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1016\/j.conb.2012.12.009","volume":"23","author":"JD Power","year":"2013","unstructured":"Power, J. D. & Petersen, S. E. Control-related systems in the human brain. Curr. Opin. Neurobiol. 23, 223\u2013228 (2013).","journal-title":"Curr. Opin. Neurobiol."},{"key":"15442_CR32","doi-asserted-by":"publisher","first-page":"1348","DOI":"10.1038\/nn.3470","volume":"16","author":"MW Cole","year":"2013","unstructured":"Cole, M. W. et al. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat. Neurosci. 16, 1348\u20131355 (2013).","journal-title":"Nat. Neurosci."},{"key":"15442_CR33","doi-asserted-by":"publisher","first-page":"E6798","DOI":"10.1073\/pnas.1510619112","volume":"112","author":"MA Bertolero","year":"2015","unstructured":"Bertolero, M. A., Yeo, B. T. T. & D\u2019Esposito, M. The modular and integrative functional architecture of the human brain. Proc. Natl Acad. Sci. USA 112, E6798\u2013E6807 (2015).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"15442_CR34","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1016\/j.neuroimage.2017.08.010","volume":"180","author":"JM Shine","year":"2017","unstructured":"Shine, J. M. & Poldrack, R. A. Principles of dynamic network reconfiguration across diverse brain states. NeuroImage 180, 396\u2013405 (2017).","journal-title":"NeuroImage"},{"key":"15442_CR35","doi-asserted-by":"publisher","first-page":"12083","DOI":"10.1523\/JNEUROSCI.2965-15.2016","volume":"36","author":"JR Cohen","year":"2016","unstructured":"Cohen, J. R. & D'Esposito, M. The segregation and integration of distinct brain networks and their relationship to cognition. J. Neurosci. 36, 12083\u201312094 (2016).","journal-title":"J. Neurosci."},{"key":"15442_CR36","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1016\/j.neuron.2016.09.018","volume":"92","author":"JM Shine","year":"2016","unstructured":"Shine, J. M. et al. The dynamics of functional brain networks: integrated network states during cognitive task performance. Neuron 92, 544\u2013554 (2016).","journal-title":"Neuron"},{"key":"15442_CR37","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","volume":"62","author":"M Jenkinson","year":"2012","unstructured":"Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. NeuroImage 62, 782\u2013790 (2012).","journal-title":"NeuroImage"},{"key":"15442_CR38","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","volume":"23","author":"SM Smith","year":"2004","unstructured":"Smith, S. M. et al. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23, S208\u2013S219 (2004).","journal-title":"NeuroImage"},{"key":"15442_CR39","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1006\/cbmr.1996.0014","volume":"29","author":"RW Cox","year":"1996","unstructured":"Cox, R. W. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29, 162\u2013173 (1996).","journal-title":"Comput. Biomed. Res."},{"key":"15442_CR40","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1016\/j.neuroimage.2011.08.056","volume":"62","author":"RW Cox","year":"2012","unstructured":"Cox, R. W. AFNI: what a long strange trip it\u2019s been. NeuroImage 62, 743\u2013747 (2012).","journal-title":"NeuroImage"},{"key":"15442_CR41","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/42.906424","volume":"20","author":"Y Zhang","year":"2001","unstructured":"Zhang, Y., Brady, M. & Smith, S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging 20, 45\u201357 (2001).","journal-title":"IEEE Trans. Med. Imaging"},{"key":"15442_CR42","doi-asserted-by":"publisher","first-page":"e68910","DOI":"10.1371\/journal.pone.0068910","volume":"8","author":"M Xia","year":"2013","unstructured":"Xia, M., Wang, J. & He, Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLOS ONE 8, e68910 (2013).","journal-title":"PLOS ONE"},{"key":"15442_CR43","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1002\/mrm.1910340409","volume":"34","author":"B Biswal","year":"1995","unstructured":"Biswal, B., Zerrin Yetkin, F., Haughton, V. M. & Hyde, J. S. Functional connectivity in the motor cortex of resting human brain using echo-planar mri. Magn. Reson. Med. 34, 537\u2013541 (1995).","journal-title":"Magn. Reson. Med."},{"key":"15442_CR44","doi-asserted-by":"publisher","first-page":"18265","DOI":"10.1073\/pnas.0705791104","volume":"104","author":"H Lu","year":"2007","unstructured":"Lu, H. et al. Synchronized delta oscillations correlate with the resting-state functional MRI signal. Proc. Natl Acad. Sci. USA 104, 18265\u201318269 (2007).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"15442_CR45","doi-asserted-by":"publisher","first-page":"1432","DOI":"10.1016\/j.neuroimage.2009.09.037","volume":"49","author":"X-N Zuo","year":"2010","unstructured":"Zuo, X.-N. et al. The oscillating brain: complex and reliable. NeuroImage 49, 1432\u20131445 (2010).","journal-title":"NeuroImage"},{"key":"15442_CR46","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1002\/mrm.1910350312","volume":"35","author":"KJ Friston","year":"1996","unstructured":"Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S. J. & Turner, R. Movement-related effects in fMRI time-series. Magn. Reson. Med. 35, 346\u2013355 (1996).","journal-title":"Magn. Reson. Med."},{"key":"15442_CR47","doi-asserted-by":"publisher","first-page":"9673","DOI":"10.1073\/pnas.0504136102","volume":"102","author":"MD Fox","year":"2005","unstructured":"Fox, M. D. et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl Acad. Sci. USA 102, 9673\u20139678 (2005).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"15442_CR48","doi-asserted-by":"publisher","first-page":"3261","DOI":"10.1137\/110821172","volume":"33","author":"J Kim","year":"2011","unstructured":"Kim, J. & Park, H. Fast nonnegative matrix factorization: an active-set-like method and comparisons. SIAM J. Sci. Comput. 33, 3261\u20133281 (2011).","journal-title":"SIAM J. Sci. Comput."},{"key":"15442_CR49","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1007\/s10898-013-0035-4","volume":"58","author":"J Kim","year":"2014","unstructured":"Kim, J., He, Y. & Park, H. Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework. J. Glob. Optim. 58, 285\u2013319 (2014).","journal-title":"J. Glob. Optim."},{"key":"15442_CR50","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J. & Bengio, Y. Random search for hyper-parameter optimization. J. Mach. Learn. Res. 13, 281\u2013305 (2012).","journal-title":"J. Mach. Learn. Res."},{"key":"15442_CR51","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/A:1023949509487","volume":"52","author":"S Monti","year":"2003","unstructured":"Monti, S., Tamayo, P., Mesirov, J. & Golub, T. Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Mach. Learn. 52, 91\u2013118 (2003).","journal-title":"Mach. Learn."}],"container-title":["Nature Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41467-020-15442-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-020-15442-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41467-020-15442-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T15:15:03Z","timestamp":1670253303000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41467-020-15442-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,3]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["15442"],"URL":"https:\/\/doi.org\/10.1038\/s41467-020-15442-2","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/800284","asserted-by":"object"}]},"ISSN":["2041-1723"],"issn-type":[{"value":"2041-1723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,3]]},"assertion":[{"value":"27 July 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 March 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 April 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1682"}}