{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T02:28:30Z","timestamp":1776479310936,"version":"3.51.2"},"reference-count":45,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2020,1,15]],"date-time":"2020-01-15T00:00:00Z","timestamp":1579046400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"DOI":"10.1371\/journal.pcbi.1007549","type":"journal-article","created":{"date-parts":[[2020,1,15]],"date-time":"2020-01-15T13:41:08Z","timestamp":1579095668000},"page":"e1007549","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":63,"title":["BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4911-2885","authenticated-orcid":true,"given":"Manoj","family":"Kumar","sequence":"first","affiliation":[]},{"given":"Cameron T.","family":"Ellis","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0730-5240","authenticated-orcid":true,"given":"Qihong","family":"Lu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5222-5277","authenticated-orcid":true,"given":"Hejia","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7323-2393","authenticated-orcid":true,"given":"Mihai","family":"Capot\u0103","sequence":"additional","affiliation":[]},{"given":"Theodore L.","family":"Willke","sequence":"additional","affiliation":[]},{"given":"Peter J.","family":"Ramadge","sequence":"additional","affiliation":[]},{"given":"Nicholas B.","family":"Turk-Browne","sequence":"additional","affiliation":[]},{"given":"Kenneth A.","family":"Norman","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2020,1,15]]},"reference":[{"key":"pcbi.1007549.ref001","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.tics.2006.07.005","article-title":"Beyond mind-reading: multi-voxel pattern analysis of fMRI data","volume":"10","author":"KA Norman","year":"2006","journal-title":"Trends in Cognitive Sciences"},{"key":"pcbi.1007549.ref002","doi-asserted-by":"crossref","first-page":"3107","DOI":"10.1016\/j.neuropsychologia.2012.07.007","article-title":"Decoding information in the human hippocampus: A user\u2019s guide","volume":"50","author":"MJ Chadwick","year":"2012","journal-title":"Neuropsychologia"},{"key":"pcbi.1007549.ref003","author":"N Kriegeskorte","year":"2012"},{"key":"pcbi.1007549.ref004","doi-asserted-by":"crossref","DOI":"10.3389\/fnhum.2015.00151","article-title":"Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations","volume":"9","author":"JT Kaplan","year":"2015","journal-title":"Front Hum Neurosci"},{"key":"pcbi.1007549.ref005","article-title":"Representational Similarity Analysis\u2013Connecting the Branches of Systems Neuroscience","volume":"2","author":"N Kriegeskorte","year":"2008","journal-title":"Front Syst Neurosci"},{"key":"pcbi.1007549.ref006","doi-asserted-by":"crossref","first-page":"e1003553","DOI":"10.1371\/journal.pcbi.1003553","article-title":"A Toolbox for Representational Similarity Analysis","volume":"10","author":"H Nili","year":"2014","journal-title":"PLoS Computational Biology"},{"key":"pcbi.1007549.ref007","first-page":"1","volume-title":"Full correlation matrix analysis of fMRI data on Intel\u00ae Xeon PhiTM coprocessors","author":"Y Wang","year":"2015"},{"key":"pcbi.1007549.ref008","doi-asserted-by":"crossref","first-page":"1634","DOI":"10.1126\/science.1089506","article-title":"Intersubject Synchronization of Cortical Activity During Natural Vision","volume":"303","author":"U Hasson","year":"2004","journal-title":"Science"},{"key":"pcbi.1007549.ref009","first-page":"667","article-title":"Measuring shared responses across subjects using intersubject correlation","volume":"14","author":"SA Nastase","year":"2019","journal-title":"Soc Cogn Affect Neurosci"},{"key":"pcbi.1007549.ref010","doi-asserted-by":"crossref","first-page":"12141","DOI":"10.1038\/ncomms12141","article-title":"Dynamic reconfiguration of the default mode network during narrative comprehension","volume":"7","author":"E Simony","year":"2016","journal-title":"Nature Communications"},{"key":"pcbi.1007549.ref011","first-page":"460","volume-title":"Advances in Neural Information Processing Systems 28","author":"P-H Chen","year":"2015"},{"key":"pcbi.1007549.ref012","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1016\/j.neuron.2017.06.041","article-title":"Discovering Event Structure in Continuous Narrative Perception and Memory","volume":"95","author":"C Baldassano","year":"2017","journal-title":"Neuron"},{"key":"pcbi.1007549.ref013","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1038\/nn.3940","article-title":"Closed-loop training of attention with real-time brain imaging","volume":"18","author":"MT deBettencourt","year":"2015","journal-title":"Nature Neuroscience"},{"key":"pcbi.1007549.ref014","doi-asserted-by":"crossref","unstructured":"Wang Y, Keller B, Capota M, Anderson MJ, Sundaram N, Cohen JD, et al. Real-time full correlation matrix analysis of fMRI data. 2016 IEEE International Conference on Big Data (Big Data). 2016. pp. 1242\u20131251. doi: 10.1109\/BigData.2016.7840728","DOI":"10.1109\/BigData.2016.7840728"},{"key":"pcbi.1007549.ref015","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1038\/nrn.2016.164","article-title":"Closed-loop brain training: the science of neurofeedback","volume":"18","author":"R Sitaram","year":"2017","journal-title":"Nature Reviews Neuroscience"},{"key":"pcbi.1007549.ref016","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.tics.2017.01.006","article-title":"Neuroadaptive Bayesian Optimization and Hypothesis Testing","volume":"21","author":"R Lorenz","year":"2017","journal-title":"Trends in Cognitive Sciences"},{"key":"pcbi.1007549.ref017","doi-asserted-by":"crossref","DOI":"10.3389\/fninf.2014.00088","article-title":"The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data","volume":"8","author":"MN Hebart","year":"2015","journal-title":"Front Neuroinform"},{"key":"pcbi.1007549.ref018","doi-asserted-by":"crossref","DOI":"10.3389\/fninf.2016.00027","article-title":"CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab\/GNU Octave","volume":"10","author":"NN Oosterhof","year":"2016","journal-title":"Front Neuroinform"},{"key":"pcbi.1007549.ref019","first-page":"8","author":"A Abraham","year":"2014","journal-title":"Machine learning for neuroimaging with scikit-learn"},{"key":"pcbi.1007549.ref020","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s12021-008-9041-y","article-title":"PyMVPA: a Python Toolbox for Multivariate Pattern Analysis of fMRI Data","volume":"7","author":"M Hanke","year":"2009","journal-title":"Neuroinform"},{"key":"pcbi.1007549.ref021","doi-asserted-by":"crossref","DOI":"10.3389\/neuro.11.003.2009","article-title":"PyMVPA: a unifying approach to the analysis of neuroscientific data","volume":"3","author":"M Hanke","year":"2009","journal-title":"Front Neuroinform"},{"key":"pcbi.1007549.ref022","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1006\/cbmr.1996.0014","article-title":"AFNI: Software for Analysis and Visualization of Functional Magnetic Resonance Neuroimages","volume":"29","author":"RW Cox","year":"1996","journal-title":"Computers and Biomedical Research"},{"key":"pcbi.1007549.ref023","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","article-title":"FSL","volume":"62","author":"M Jenkinson","year":"2012","journal-title":"NeuroImage"},{"key":"pcbi.1007549.ref024","doi-asserted-by":"crossref","DOI":"10.1016\/B978-012372560-8\/50002-4","volume-title":"Statistical Parametric Mapping: The Analysis of Functional Brain Images","author":"KJ Friston","year":"2007"},{"key":"pcbi.1007549.ref025","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1038\/s41592-018-0235-4","article-title":"fMRIPrep: a robust preprocessing pipeline for functional MRI","volume":"16","author":"O Esteban","year":"2019","journal-title":"Nature Methods"},{"key":"pcbi.1007549.ref026","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1038\/nn.2303","article-title":"Circular analysis in systems neuroscience: the dangers of double dipping","volume":"12","author":"N Kriegeskorte","year":"2009","journal-title":"Nature Neuroscience"},{"key":"pcbi.1007549.ref027","first-page":"87","article-title":"Jupyter Notebooks\u2014a publishing format for reproducible computational workflows","author":"T Kluyver","year":"2016","journal-title":"In Positioning and Power in Academic Publishing: Players, Agents and Agendas"},{"key":"pcbi.1007549.ref028","article-title":"nipy\/nibabel: 2.3.1","author":"M Brett","year":"2018","journal-title":"Zenodo"},{"key":"pcbi.1007549.ref029","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"F Pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"pcbi.1007549.ref030","first-page":"1151","article-title":"Enabling factor analysis on thousand-subject neuroimaging datasets","author":"MJ Anderson","year":"2016"},{"key":"pcbi.1007549.ref031","doi-asserted-by":"crossref","first-page":"3863","DOI":"10.1073\/pnas.0600244103","article-title":"Information-based functional brain mapping","volume":"103","author":"N Kriegeskorte","year":"2006","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"pcbi.1007549.ref032","first-page":"44","volume-title":"In Lecture Notes in Computer Science: Proceedings of Job Scheduling Strategies for Parallel Processing (JSSPP) 2003","author":"MA Jette","year":"2002"},{"key":"pcbi.1007549.ref033","article-title":"BrainIAK Tutorials: Condensed Datasets","author":"M Kumar","year":"2019","journal-title":"Zenodo"},{"key":"pcbi.1007549.ref034","article-title":"matplotlib\/matplotlib v2.2.2","author":"M Droettboom","year":"2018","journal-title":"Zenodo"},{"key":"pcbi.1007549.ref035","article-title":"mwaskom\/seaborn: v0.9.0 (July 2018)","author":"M Waskom","year":"2018","journal-title":"Zenodo"},{"key":"pcbi.1007549.ref036","unstructured":"Hagberg AA, Schult DA, Swart PJ. Exploring Network Structure, Dynamics, and Function using NetworkX. In: Varoquaux G, Vaught T, Millman J, editors. Proceedings of the 7th Python in Science Conference. Pasadena, CA USA; 2008. pp. 11\u201315."},{"key":"pcbi.1007549.ref037","doi-asserted-by":"crossref","first-page":"2022","DOI":"10.1523\/JNEUROSCI.3272-16.2017","article-title":"Neural Differentiation of Incorrectly Predicted Memories","volume":"37","author":"G Kim","year":"2017","journal-title":"J Neurosci"},{"key":"pcbi.1007549.ref038","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1016\/j.neuron.2008.10.043","article-title":"Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey","volume":"60","author":"N Kriegeskorte","year":"2008","journal-title":"Neuron"},{"key":"pcbi.1007549.ref039","doi-asserted-by":"crossref","first-page":"7202","DOI":"10.1523\/JNEUROSCI.0942-12.2012","article-title":"Scene Representations in Parahippocampal Cortex Depend on Temporal Context","volume":"32","author":"NB Turk-Browne","year":"2012","journal-title":"J Neurosci"},{"key":"pcbi.1007549.ref040","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1162\/jocn_a_00889","article-title":"Biased Competition during Long-term Memory Formation","volume":"28","author":"JB Hutchinson","year":"2016","journal-title":"J Cogn Neurosci"},{"key":"pcbi.1007549.ref041","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1016\/j.neuron.2011.08.026","article-title":"A common, high-dimensional model of the representational space in human ventral temporal cortex","volume":"72","author":"JV Haxby","year":"2011","journal-title":"Neuron"},{"key":"pcbi.1007549.ref042","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nn.4450","article-title":"Shared memories reveal shared structure in neural activity across individuals","volume":"20","author":"J Chen","year":"2017","journal-title":"Nature Neuroscience"},{"key":"pcbi.1007549.ref043","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/99.660313","article-title":"OpenMP: An Industry-Standard API for Shared-Memory Programming","volume":"5","author":"L Dagum","year":"1998","journal-title":"IEEE Comput Sci Eng"},{"key":"pcbi.1007549.ref044","volume-title":"MPI: A Message-Passing Interface Standard","author":"MP Forum","year":"1994"},{"key":"pcbi.1007549.ref045","doi-asserted-by":"crossref","DOI":"10.3389\/fninf.2013.00012","article-title":"Toward open sharing of task-based fMRI data: the OpenfMRI project","volume":"7","author":"RA Poldrack","year":"2013","journal-title":"Frontiers in Neuroinformatics"}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1007549","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,15]],"date-time":"2020-01-15T13:42:44Z","timestamp":1579095764000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1007549"}},"subtitle":[],"editor":[{"given":"Daniele","family":"Marinazzo","sequence":"first","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,1,15]]},"references-count":45,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,1,15]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1007549","relation":{"has-preprint":[{"id-type":"doi","id":"10.31219\/osf.io\/j4sbc","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,15]]}}}