{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T20:38:14Z","timestamp":1773434294098,"version":"3.50.1"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"French Embassy in Spain \/ Institut fran\u00e7ais de Espa\u00f1a fellowship"},{"DOI":"10.13039\/501100010785","name":"Canada First Research Excellence Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010785","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["ANR-22-PESN-0012"],"award-info":[{"award-number":["ANR-22-PESN-0012"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["HORIZON-INFRA-2022-SERV-B-01"],"award-info":[{"award-number":["HORIZON-INFRA-2022-SERV-B-01"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Struct Funct"],"DOI":"10.1007\/s00429-025-03068-3","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T06:22:32Z","timestamp":1768026152000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Subject fingerprinting and task classification rely on distinct functional connectivity features"],"prefix":"10.1007","volume":"231","author":[{"given":"Himanshu","family":"Aggarwal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana Fernanda","family":"Ponce","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Swetha","family":"Shankar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yasmin","family":"Mzayek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agn\u00e9s","family":"P\u00e9rez-Millan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ana Lu\u00edsa","family":"Pinho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexis","family":"Thual","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bertrand","family":"Thirion","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"key":"3068_CR1","doi-asserted-by":"publisher","unstructured":"Abraham A, Pedregosa F, Eickenberg M, Gervais P, Mueller A, Kossaifi J, Gramfort A, Thirion B, Varoquaux G (2014) Machine learning for neuroimaging with scikit-learn. Front Neuroinform. https:\/\/doi.org\/10.3389\/fninf.2014.00014","DOI":"10.3389\/fninf.2014.00014"},{"issue":"1","key":"3068_CR2","doi-asserted-by":"publisher","first-page":"8254","DOI":"10.1038\/s41598-018-25089-1","volume":"8","author":"E Amico","year":"2018","unstructured":"Amico E, Go\u00f1i J (2018) The quest for identifiability in human functional connectomes. Sci Rep 8(1):8254. https:\/\/doi.org\/10.1038\/s41598-018-25089-1","journal-title":"Sci Rep"},{"issue":"2","key":"3068_CR3","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1016\/S1053-8119(03)00336-7","volume":"20","author":"JLR Andersson","year":"2003","unstructured":"Andersson JLR, Skare S, Ashburner J (2003) How to correct susceptibility distortions in spin-echo echo-planar images: Application to diffusion tensor imaging. Neuroimage 20(2):870\u2013888. https:\/\/doi.org\/10.1016\/S1053-8119(03)00336-7","journal-title":"Neuroimage"},{"key":"3068_CR4","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1016\/j.neuroimage.2015.10.019","volume":"125","author":"JLR Andersson","year":"2016","unstructured":"Andersson JLR, Sotiropoulos SN (2016) An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125:1063\u20131078. https:\/\/doi.org\/10.1016\/j.neuroimage.2015.10.019","journal-title":"Neuroimage"},{"issue":"1","key":"3068_CR5","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","volume":"12","author":"BB Avants","year":"2008","unstructured":"Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12(1):26\u201341. https:\/\/doi.org\/10.1016\/j.media.2007.06.004","journal-title":"Med Image Anal"},{"issue":"365","key":"3068_CR6","first-page":"1","volume":"2","author":"BB Avants","year":"2009","unstructured":"Avants BB, Tustison N, Johnson H (2009) Advanced Normalization Tools (ANTS) 2(365):1\u201335","journal-title":"Adv Normalization Tools (ANTS)"},{"issue":"1","key":"3068_CR7","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.neuroimage.2007.04.042","volume":"37","author":"Y Behzadi","year":"2007","unstructured":"Behzadi Y, Restom K, Liau J, Liu TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37(1):90\u2013101. https:\/\/doi.org\/10.1016\/j.neuroimage.2007.04.042","journal-title":"Neuroimage"},{"issue":"1","key":"3068_CR8","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","volume":"57","author":"Y Benjamini","year":"1995","unstructured":"Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc: Ser B (Methodol) 57(1):289\u2013300. https:\/\/doi.org\/10.1111\/j.2517-6161.1995.tb02031.x","journal-title":"J Roy Stat Soc: Ser B (Methodol)"},{"issue":"3","key":"3068_CR9","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1177\/10738584221130974","volume":"30","author":"M Bernstein-Eliav","year":"2024","unstructured":"Bernstein-Eliav M, Tavor I (2024) The prediction of brain activity from connectivity: advances and applications. Neuroscientist 30(3):367\u2013377. https:\/\/doi.org\/10.1177\/10738584221130974","journal-title":"Neuroscientist"},{"key":"3068_CR10","doi-asserted-by":"publisher","unstructured":"Bijsterbosch JD, Beckmann CF, Woolrich MW, Smith SM, Harrison SJ (2019). The relationship between spatial configuration and functional connectivity of brain regions revisited. eLife. https:\/\/doi.org\/10.7554\/eLife.44890","DOI":"10.7554\/eLife.44890"},{"issue":"1","key":"3068_CR11","doi-asserted-by":"publisher","first-page":"2217","DOI":"10.1038\/s41467-022-29766-8","volume":"13","author":"J Chen","year":"2022","unstructured":"Chen J, Tam A, Kebets V, Orban C, Ooi LQR, Asplund CL, Marek S, Dosenbach NUF, Eickhoff SB, Bzdok D, Holmes AJ, Yeo BTT (2022) Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study. Nat Commun 13(1):2217. https:\/\/doi.org\/10.1038\/s41467-022-29766-8","journal-title":"Nat Commun"},{"key":"3068_CR12","doi-asserted-by":"publisher","first-page":"giac014","DOI":"10.1093\/gigascience\/giac014","volume":"11","author":"D Chyzhyk","year":"2022","unstructured":"Chyzhyk D, Varoquaux G, Milham M, Thirion B (2022) How to remove or control confounds in predictive models, with applications to brain biomarkers. GigaScience 11:giac014. https:\/\/doi.org\/10.1093\/gigascience\/giac014","journal-title":"GigaScience"},{"key":"3068_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.neuroimage.2018.12.054","volume":"189","author":"MW Cole","year":"2019","unstructured":"Cole MW, Ito T, Schultz D, Mill R, Chen R, Cocuzza C (2019) Task activations produce spurious but systematic inflation of task functional connectivity estimates. Neuroimage 189:1\u201318. https:\/\/doi.org\/10.1016\/j.neuroimage.2018.12.054","journal-title":"Neuroimage"},{"key":"3068_CR14","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1016\/j.neuroimage.2019.06.039","volume":"200","author":"L Cordero-Grande","year":"2019","unstructured":"Cordero-Grande L, Christiaens D, Hutter J, Price AN, Hajnal JV (2019) Complex diffusion-weighted image estimation via matrix recovery under general noise models. Neuroimage 200:391\u2013404. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.06.039","journal-title":"Neuroimage"},{"key":"3068_CR15","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.neuroimage.2019.02.062","volume":"192","author":"K Dadi","year":"2019","unstructured":"Dadi K, Rahim M, Abraham A, Chyzhyk D, Milham M, Thirion B, Varoquaux G, Initiative ADN (2019) Benchmarking functional connectome-based predictive models for resting-state fMRI. Neuroimage 192:115\u2013134. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.02.062","journal-title":"Neuroimage"},{"key":"3068_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117126","volume":"221","author":"K Dadi","year":"2020","unstructured":"Dadi K, Varoquaux G, Machlouzarides-Shalit A, Gorgolewski KJ, Wassermann D, Thirion B, Mensch A (2020) Fine-grain atlases of functional modes for fMRI analysis. Neuroimage 221:117126. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.117126","journal-title":"Neuroimage"},{"key":"3068_CR17","doi-asserted-by":"publisher","first-page":"335","DOI":"10.1016\/j.neuroimage.2018.09.042","volume":"184","author":"M Demirta\u015f","year":"2019","unstructured":"Demirta\u015f M, Ponce-Alvarez A, Gilson M, Hagmann P, Mantini D, Betti V, Romani GL, Friston K, Corbetta M, Deco G (2019) Distinct modes of functional connectivity induced by movie-watching. Neuroimage 184:335\u2013348. https:\/\/doi.org\/10.1016\/j.neuroimage.2018.09.042","journal-title":"Neuroimage"},{"key":"3068_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101799","volume":"66","author":"S Deslauriers-Gauthier","year":"2020","unstructured":"Deslauriers-Gauthier S, Zucchelli M, Frigo M, Deriche R (2020) A unified framework for multimodal structure-function mapping based on eigenmodes. Med Image Anal 66:101799. https:\/\/doi.org\/10.1016\/j.media.2020.101799","journal-title":"Med Image Anal"},{"key":"3068_CR19","unstructured":"Dhollander T, Mito R, Raffelt D, Connelly A (2019). Improved white matter response function estimation for 3-tissue constrained spherical deconvolution"},{"key":"3068_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117706","volume":"229","author":"E Dohmatob","year":"2021","unstructured":"Dohmatob E, Richard H, Pinho AL, Thirion B (2021) Brain topography beyond parcellations: local gradients of functional maps. Neuroimage 229:117706. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.117706","journal-title":"Neuroimage"},{"issue":"12","key":"3068_CR21","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1016\/j.tics.2021.09.005","volume":"25","author":"ES Finn","year":"2021","unstructured":"Finn ES (2021) Is it time to put rest to rest? Trends Cogn Sci 25(12):1021\u20131032. https:\/\/doi.org\/10.1016\/j.tics.2021.09.005","journal-title":"Trends Cogn Sci"},{"key":"3068_CR22","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.neuroimage.2017.03.064","volume":"160","author":"ES Finn","year":"2017","unstructured":"Finn ES, Scheinost D, Finn DM, Shen X, Papademetris X, Constable RT (2017) Can brain state be manipulated to emphasize individual differences in functional connectivity? Neuroimage 160:140\u2013151. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.03.064","journal-title":"Neuroimage"},{"issue":"11","key":"3068_CR23","doi-asserted-by":"publisher","first-page":"1664","DOI":"10.1038\/nn.4135","volume":"18","author":"ES Finn","year":"2015","unstructured":"Finn ES, Shen X, Scheinost D, Rosenberg MD, Huang J, Chun MM, Papademetris X, Constable RT (2015) Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity. Nat Neurosci 18(11):1664\u20131671. https:\/\/doi.org\/10.1038\/nn.4135","journal-title":"Nat Neurosci"},{"issue":"3","key":"3068_CR24","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1093\/biostatistics\/kxm045","volume":"9","author":"J Friedman","year":"2008","unstructured":"Friedman J, Hastie T, Tibshirani R (2008) Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9(3):432\u2013441. https:\/\/doi.org\/10.1093\/biostatistics\/kxm045","journal-title":"Biostatistics"},{"issue":"2 , Part A","key":"3068_CR25","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1006\/nimg.1995.1019","volume":"2","author":"KJ Friston","year":"1995","unstructured":"Friston KJ, Frith CD, Frackowiak RSJ, Turner R (1995) v. Neuroimage 2(2, Part A):166\u2013172. https:\/\/doi.org\/10.1006\/nimg.1995.1019","journal-title":"Neuroimage"},{"issue":"7615","key":"3068_CR26","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1038\/nature18933","volume":"536","author":"MF Glasser","year":"2016","unstructured":"Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, Ugurbil K, Andersson J, Beckmann CF, Jenkinson M, Smith SM, Van Essen DC (2016) A multi-modal parcellation of human cerebral cortex. Nature 536(7615):171\u2013178. https:\/\/doi.org\/10.1038\/nature18933","journal-title":"Nature"},{"issue":"16","key":"3068_CR27","doi-asserted-by":"publisher","first-page":"5294","DOI":"10.1002\/hbm.26423","volume":"44","author":"A Hannum","year":"2023","unstructured":"Hannum A, Lopez MA, Blanco SA, Betzel RF (2023) High-accuracy machine learning techniques for functional connectome fingerprinting and cognitive state decoding. Hum Brain Mapp 44(16):5294\u20135308. https:\/\/doi.org\/10.1002\/hbm.26423","journal-title":"Hum Brain Mapp"},{"key":"3068_CR28","doi-asserted-by":"publisher","unstructured":"Harris CR, Millman KJ, van der Walt SJ, Gommers R, Virtanen P, Cournapeau D, Wieser E, Taylor J, Berg S, Smith NJ, Kern R, Picus M, Hoyer S, van Kerkwijk MH, Brett M, Haldane A, del R\u00edo JF, Wiebe M, Peterson, P. et al. (2020) Array programming with NumPy. Nature 585(7825):357\u2013362. https:\/\/doi.org\/10.1038\/s41586-020-2649-2","DOI":"10.1038\/s41586-020-2649-2"},{"issue":"2","key":"3068_CR29","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1016\/j.neuron.2011.08.026","volume":"72","author":"JV Haxby","year":"2011","unstructured":"Haxby JV, Guntupalli JS, Connolly AC, Halchenko YO, Conroy BR, Gobbini MI, Hanke M, Ramadge PJ (2011) A common, high-dimensional model of the representational space in human ventral temporal cortex. Neuron 72(2):404\u2013416. https:\/\/doi.org\/10.1016\/j.neuron.2011.08.026","journal-title":"Neuron"},{"issue":"15","key":"3068_CR30","doi-asserted-by":"publisher","first-page":"6169","DOI":"10.1073\/pnas.1219562110","volume":"110","author":"AM Hermundstad","year":"2013","unstructured":"Hermundstad AM, Bassett DS, Brown KS, Aminoff EM, Clewett D, Freeman S, Frithsen A, Johnson A, Tipper CM, Miller MB, Grafton ST, Carlson JM (2013) Structural foundations of resting-state and task-based functional connectivity in the human brain. Proc Natl Acad Sci 110(15):6169\u20136174. https:\/\/doi.org\/10.1073\/pnas.1219562110","journal-title":"Proc Natl Acad Sci"},{"issue":"6","key":"3068_CR31","doi-asserted-by":"publisher","first-page":"2035","DOI":"10.1073\/pnas.0811168106","volume":"106","author":"CJ Honey","year":"2009","unstructured":"Honey CJ, Sporns O, Cammoun L, Gigandet X, Thiran JP, Meuli R, Hagmann P (2009) Predicting human resting-state functional connectivity from structural connectivity. Proc Natl Acad Sci 106(6):2035\u20132040. https:\/\/doi.org\/10.1073\/pnas.0811168106","journal-title":"Proc Natl Acad Sci"},{"issue":"3","key":"3068_CR32","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1016\/j.neuroimage.2010.01.071","volume":"52","author":"CJ Honey","year":"2010","unstructured":"Honey CJ, Thivierge J-P, Sporns O (2010) Can structure predict function in the human brain? Neuroimage 52(3):766\u2013776. https:\/\/doi.org\/10.1016\/j.neuroimage.2010.01.071","journal-title":"Neuroimage"},{"issue":"3","key":"3068_CR33","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/MCSE.2007.55","volume":"9","author":"JD Hunter","year":"2007","unstructured":"Hunter JD (2007) Matplotlib: a 2D graphics environment. Comput Sci Eng 9(3):90\u201395. https:\/\/doi.org\/10.1109\/MCSE.2007.55","journal-title":"Comput Sci Eng"},{"issue":"15","key":"3068_CR34","doi-asserted-by":"publisher","first-page":"4187","DOI":"10.1002\/hbm.25118","volume":"41","author":"M Jalbrzikowski","year":"2020","unstructured":"Jalbrzikowski M, Liu F, Foran W, Klei L, Calabro FJ, Roeder K, Devlin B, Luna B (2020) Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5-years apart. Hum Brain Mapp 41(15):4187\u20134199. https:\/\/doi.org\/10.1002\/hbm.25118","journal-title":"Hum Brain Mapp"},{"issue":"10","key":"3068_CR35","doi-asserted-by":"publisher","first-page":"4477","DOI":"10.1093\/cercor\/bhab101","volume":"31","author":"R Kong","year":"2021","unstructured":"Kong R, Yang Q, Gordon E, Xue A, Yan X, Orban C, Zuo X-N, Spreng N, Ge T, Holmes A, Eickhoff S, Yeo BTT (2021) Individual-specific areal-level parcellations improve functional connectivity prediction of behavior. Cereb Cortex 31(10):4477\u20134500. https:\/\/doi.org\/10.1093\/cercor\/bhab101","journal-title":"Cereb Cortex"},{"issue":"2","key":"3068_CR36","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/S0047-259X(03)00096-4","volume":"88","author":"O Ledoit","year":"2004","unstructured":"Ledoit O, Wolf M (2004) A well-conditioned estimator for large-dimensional covariance matrices. J Multivar Anal 88(2):365\u2013411. https:\/\/doi.org\/10.1016\/S0047-259X(03)00096-4","journal-title":"J Multivar Anal"},{"issue":"1","key":"3068_CR37","doi-asserted-by":"publisher","first-page":"530","DOI":"10.1038\/s41597-022-01625-7","volume":"9","author":"J Li","year":"2022","unstructured":"Li J, Bhattasali S, Zhang S, Franzluebbers B, Luh W-M, Spreng RN, Brennan JR, Yang Y, Pallier C, Hale J (2022) Le Petit Prince multilingual naturalistic fMRI corpus. Sci Data 9(1):530. https:\/\/doi.org\/10.1038\/s41597-022-01625-7","journal-title":"Sci Data"},{"issue":"4","key":"3068_CR38","doi-asserted-by":"publisher","first-page":"1235","DOI":"10.1162\/netn_a00166","volume":"4","author":"R Li\u00e9geois","year":"2020","unstructured":"Li\u00e9geois R, Santos A, Matta V, Van De Ville D, Sayed AH (2020) Revisiting correlation-based functional connectivity and its relationship with structural connectivity. Netw Neurosci 4(4):1235\u20131251. https:\/\/doi.org\/10.1162\/netn_a00166","journal-title":"Netw Neurosci"},{"key":"3068_CR39","doi-asserted-by":"publisher","unstructured":"Maier-Hein KH, Neher PF, Houde J-C, C\u00f4t\u00e9 M-A, Garyfallidis E, Zhong J, Chamberland M, Yeh F-C, Lin Y-C, Ji Q, Reddick WE, Glass JO, Chen DQ, Feng Y, Gao C, Wu Y, Ma J, He R, Li, Q.,... Descoteaux, M. (2017) The challenge of mapping the human connectome based on diffusion tractography. Nat Commun 8(1):1349. https:\/\/doi.org\/10.1038\/s41467-017-01285-x","DOI":"10.1038\/s41467-017-01285-x"},{"key":"3068_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.117695","volume":"229","author":"LS Mansour","year":"2021","unstructured":"Mansour LS, Tian Y, Yeo BT, Cropley V, Zalesky A (2021) High-resolution connectomic fingerprints: mapping neural identity and behavior. Neuroimage 229:117695. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.117695","journal-title":"Neuroimage"},{"issue":"3","key":"3068_CR41","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1038\/nmeth.1868","volume":"9","author":"D Mantini","year":"2012","unstructured":"Mantini D, Hasson U, Betti V, Perrucci MG, Romani GL, Corbetta M, Orban GA, Vanduffel W (2012) Interspecies activity correlations reveal functional correspondence between monkey and human brain areas. Nat Methods 9(3):277\u2013282. https:\/\/doi.org\/10.1038\/nmeth.1868","journal-title":"Nat Methods"},{"key":"3068_CR42","doi-asserted-by":"publisher","unstructured":"Nielsen J, Zielinski B, Fletcher P, Alexander A, Lange N, Bigler E, Lainhart J, Anderson J (2013) Multisite functional connectivity MRI classification of autism: ABIDE results. Front Hum Neurosci 7. https:\/\/doi.org\/10.3389\/fnhum.2013.00599","DOI":"10.3389\/fnhum.2013.00599"},{"issue":"1","key":"3068_CR43","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/0028-3932(71)90067-4","volume":"9","author":"RC Oldfield","year":"1971","unstructured":"Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9(1):97\u2013113. https:\/\/doi.org\/10.1016\/0028-3932(71)90067-4","journal-title":"Neuropsychologia"},{"key":"3068_CR44","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D (2011) Scikit-learn: machine learning in Python. J Mach Learn Res 12:2825\u20132830","journal-title":"J Mach Learn Res"},{"key":"3068_CR45","unstructured":"Penny WD, Friston KJ, Ashburner JT, Kiebel SJ, Nichols TE (2011) Statistical parametric mapping: the analysis of functional brain images. Elsevier"},{"key":"3068_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.116604","volume":"211","author":"U Pervaiz","year":"2020","unstructured":"Pervaiz U, Vidaurre D, Woolrich MW, Smith SM (2020) Optimising network modelling methods for fMRI. Neuroimage 211:116604. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.116604","journal-title":"Neuroimage"},{"key":"3068_CR47","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1016\/j.neuroimage.2019.04.056","volume":"197","author":"P Pinel","year":"2019","unstructured":"Pinel P, Forgeot d\u2019Arc B, Dehaene S, Bourgeron T, Thirion B, Le Bihan D, Poupon C (2019) The functional database of the ARCHI project: potential and perspectives. Neuroimage 197:527\u2013543. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.04.056","journal-title":"Neuroimage"},{"key":"3068_CR48","doi-asserted-by":"publisher","unstructured":"Pinho AL, Amadon A, Fabre M, Dohmatob E, Denghien I, Torre JJ, Ginisty C, Becuwe-Desmidt S, Roger S, Laurier L, Joly-Testault V, M\u00e9diouni-Cloarec G, Doubl\u00e9 C, Martins B, Pinel P, Eger E, Varoquaux G, Pallier C, Dehaene, S. et al. (2021) Subject-specific segregation of functional territories based on deep phenotyping. Hum Brain Mapp 42(4):841\u2013870. https:\/\/doi.org\/10.1002\/hbm.25189","DOI":"10.1002\/hbm.25189"},{"key":"3068_CR49","doi-asserted-by":"publisher","unstructured":"Pinho AL, Amadon A, Gauthier B, Clairis N, Knops A, Genon S, Dohmatob E, Torre JJ, Ginisty C, Becuwe-Desmidt S, Roger S, Lecomte Y, Berland V, Laurier L, Joly-Testault V, M\u00e9diouni-Cloarec G, Doubl\u00e9 C, Martins B, Salmon E, Thirion, B. (2020) Individual Brain Charting dataset extension, second release of high-resolution fMRI data for cognitive mapping. Sci Data 7(1):353. https:\/\/doi.org\/10.1038\/s41597-020-00670-4","DOI":"10.1038\/s41597-020-00670-4"},{"key":"3068_CR50","doi-asserted-by":"publisher","unstructured":"Pinho AL, Amadon A, Ruest T, Fabre M, Dohmatob E, Denghien I, Ginisty C, Becuwe-Desmidt S, Roger S, Laurier L, Joly-Testault V, M\u00e9diouni-Cloarec G, Doubl\u00e9 C, Martins B, Pinel P, Eger E, Varoquaux G, Pallier C, Dehaene S, Thirion, B. (2018) Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping. Sci Data 5(1):180105. https:\/\/doi.org\/10.1038\/sdata.2018.105","DOI":"10.1038\/sdata.2018.105"},{"key":"3068_CR51","doi-asserted-by":"publisher","unstructured":"Pinho AL, Richard H, Ponce AF, Eickenberg M, Amadon A, Dohmatob E, Denghien I, Torre JJ, Shankar S, Aggarwal H, Thual A, Chapalain T, Ginisty C, Becuwe-Desmidt S, Roger S, Lecomte Y, Berland V, Laurier L, Joly-Testault, V.,... Thirion, B. (2024) Individual Brain Charting dataset extension, third release for movie watching and retinotopy data. Sci Data 11(1):590. https:\/\/doi.org\/10.1038\/s41597-024-03390-1","DOI":"10.1038\/s41597-024-03390-1"},{"issue":"2","key":"3068_CR52","doi-asserted-by":"publisher","first-page":"616","DOI":"10.1016\/j.neuroimage.2010.05.081","volume":"56","author":"J Richiardi","year":"2011","unstructured":"Richiardi J, Eryilmaz H, Schwartz S, Vuilleumier P, Van De Ville D (2011) Decoding brain states from fMRI connectivity graphs. Neuroimage 56(2):616\u2013626. https:\/\/doi.org\/10.1016\/j.neuroimage.2010.05.081","journal-title":"Neuroimage"},{"issue":"9","key":"3068_CR53","doi-asserted-by":"publisher","first-page":"3095","DOI":"10.1093\/cercor\/bhx179","volume":"28","author":"A Schaefer","year":"2018","unstructured":"Schaefer A, Kong R, Gordon EM, Laumann TO, Zuo X-N, Holmes AJ, Eickhoff SB, Yeo BTT (2018) Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cereb Cortex 28(9):3095\u20133114. https:\/\/doi.org\/10.1093\/cercor\/bhx179","journal-title":"Cereb Cortex"},{"key":"3068_CR54","doi-asserted-by":"publisher","unstructured":"Shafto MA, Tyler LK, Dixon M, Taylor JR, Rowe JB, Cusack R, Calder AJ, Marslen-Wilson WD, Duncan J, Dalgleish T, Henson RN, Brayne C, Matthews FE, Cam-CAN. (2014) The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study protocol: a cross-sectional, lifespan, multidisciplinary examination of healthy cognitive ageing. BMC Neurol 14(1):204. https:\/\/doi.org\/10.1186\/s12883-014-0204-1","DOI":"10.1186\/s12883-014-0204-1"},{"issue":"3","key":"3068_CR55","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1038\/nprot.2016.178","volume":"12","author":"X Shen","year":"2017","unstructured":"Shen X, Finn ES, Scheinost D, Rosenberg MD, Chun MM, Papademetris X, Constable RT (2017) Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nat Protocol 12(3):506\u2013518. https:\/\/doi.org\/10.1038\/nprot.2016.178","journal-title":"Nat Protocol"},{"issue":"1","key":"3068_CR56","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1093\/cercor\/bhr099","volume":"22","author":"WR Shirer","year":"2012","unstructured":"Shirer WR, Ryali S, Rykhlevskaia E, Menon V, Greicius MD (2012) Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb Cortex 22(1):158\u2013165. https:\/\/doi.org\/10.1093\/cercor\/bhr099","journal-title":"Cereb Cortex"},{"key":"3068_CR57","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/j.neuroimage.2015.06.092","volume":"119","author":"RE Smith","year":"2015","unstructured":"Smith RE, Tournier J-D, Calamante F, Connelly A (2015) SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography. Neuroimage 119:338\u2013351. https:\/\/doi.org\/10.1016\/j.neuroimage.2015.06.092","journal-title":"Neuroimage"},{"key":"3068_CR58","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","volume":"23","author":"SM Smith","year":"2004","unstructured":"Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:S208\u2013S219. https:\/\/doi.org\/10.1016\/j.neuroimage.2004.07.051","journal-title":"Neuroimage"},{"issue":"2","key":"3068_CR59","doi-asserted-by":"publisher","first-page":"875","DOI":"10.1016\/j.neuroimage.2010.08.063","volume":"54","author":"SM Smith","year":"2011","unstructured":"Smith SM, Miller KL, Salimi-Khorshidi G, Webster M, Beckmann CF, Nichols TE, Ramsey JD, Woolrich MW (2011) Network modelling methods for FMRI. Neuroimage 54(2):875\u2013891. https:\/\/doi.org\/10.1016\/j.neuroimage.2010.08.063","journal-title":"Neuroimage"},{"key":"3068_CR60","doi-asserted-by":"publisher","unstructured":"St-Onge F, Javanray M, Pichet Binette A, Strikwerda-Brown C, Remz J, Spreng RN, Shafiei G, Misic B, Vachon-Presseau \u00c9, Villeneuve S (2023) Functional connectome fingerprinting across the lifespan. Netw Neurosci 1\u201322. https:\/\/doi.org\/10.1162\/netn_a_00320","DOI":"10.1162\/netn_a_00320"},{"issue":"2","key":"3068_CR61","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1177\/0271678X18809547","volume":"39","author":"M Straathof","year":"2019","unstructured":"Straathof M, Sinke MR, Dijkhuizen RM, Otte WM (2019) A systematic review on the quantitative relationship between structural and functional network connectivity strength in mammalian brains. J Cerebral Blood Flow Metabol 39(2):189\u2013209. https:\/\/doi.org\/10.1177\/0271678X18809547","journal-title":"J Cerebral Blood Flow Metabol"},{"key":"3068_CR62","doi-asserted-by":"publisher","DOI":"10.1007\/s00429-023-02723-x","volume-title":"Should one go for individual- or group-level brain parcellations?","author":"B Thirion","year":"2023","unstructured":"Thirion B, Aggarwal H, Ponce AF, Pinho AL, Thual A (2023) Should one go for individual- or group-level brain parcellations? Brain Structure and Function, A deep-phenotyping benchmark. https:\/\/doi.org\/10.1007\/s00429-023-02723-x"},{"issue":"46","key":"3068_CR63","doi-asserted-by":"publisher","first-page":"16574","DOI":"10.1073\/pnas.1405672111","volume":"111","author":"C Thomas","year":"2014","unstructured":"Thomas C, Ye FQ, Irfanoglu MO, Modi P, Saleem KS, Leopold DA, Pierpaoli C (2014) Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited. Proc Natl Acad Sci 111(46):16574\u201316579. https:\/\/doi.org\/10.1073\/pnas.1405672111","journal-title":"Proc Natl Acad Sci"},{"issue":"3","key":"3068_CR64","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1152\/jn.00338.2011","volume":"106","author":"BT Thomas Yeo","year":"2011","unstructured":"Thomas Yeo BT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M, Roffman JL, Smoller JW, Z\u00f6llei L, Polimeni JR, Fischl B, Liu H, Buckner RL (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 106(3):1125\u20131165. https:\/\/doi.org\/10.1152\/jn.00338.2011","journal-title":"J Neurophysiol"},{"key":"3068_CR65","unstructured":"Tournier J-D, Calamante F, Connelly A (2010) Improved probabilistic streamlines tractography by 2nd order integration over fibre orientation distributions"},{"key":"3068_CR66","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116137","volume":"202","author":"J-D Tournier","year":"2019","unstructured":"Tournier J-D, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, Christiaens D, Jeurissen B, Yeh C-H, Connelly A (2019) MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202:116137. https:\/\/doi.org\/10.1016\/j.neuroimage.2019.116137","journal-title":"Neuroimage"},{"key":"3068_CR67","doi-asserted-by":"publisher","unstructured":"Van Essen DC, Ugurbil K, Auerbach E, Barch D, Behrens TEJ, Bucholz R, Chang A, Chen L, Corbetta M, Curtiss SW, Della Penna S, Feinberg D, Glasser MF, Harel N, Heath AC, Larson-Prior L, Marcus D, Michalareas G, Moeller, S. (2012) The human connectome project: a data acquisition perspective. Neuroimage 62(4):2222\u20132231. https:\/\/doi.org\/10.1016\/j.neuroimage.2012.02.018","DOI":"10.1016\/j.neuroimage.2012.02.018"},{"key":"3068_CR68","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1016\/j.neuroimage.2017.06.027","volume":"157","author":"T Vanderwal","year":"2017","unstructured":"Vanderwal T, Eilbott J, Finn ES, Craddock RC, Turnbull A, Castellanos FX (2017) Individual differences in functional connectivity during naturalistic viewing conditions. Neuroimage 157:521\u2013530. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.06.027","journal-title":"Neuroimage"},{"key":"3068_CR69","unstructured":"Varoquaux G, Gramfort A, Poline J-b, Thirion B (2010). Brain covariance selection: better individual functional connectivity models using population prior. Adv Neural Inf Processing Syst 23"},{"key":"3068_CR70","doi-asserted-by":"publisher","first-page":"394","DOI":"10.1016\/j.neuroimage.2016.08.016","volume":"142","author":"J Veraart","year":"2016","unstructured":"Veraart J, Novikov DS, Christiaens D, Ades-aron B, Sijbers J, Fieremans E (2016) Denoising of diffusion MRI using random matrix theory. Neuroimage 142:394\u2013406. https:\/\/doi.org\/10.1016\/j.neuroimage.2016.08.016","journal-title":"Neuroimage"},{"issue":"3","key":"3068_CR71","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","volume":"17","author":"P Virtanen","year":"2020","unstructured":"Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, Burovski E, Peterson P, Weckesser W, Bright J, van der Walt SJ, Brett M, Wilson J, Millman KJ, Mayorov N, Nelson ARJ, Jones E, Kern R, Larson E, van Mulbregt P (2020) SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods 17(3):261\u2013272. https:\/\/doi.org\/10.1038\/s41592-019-0686-2","journal-title":"Nat Methods"},{"key":"3068_CR72","doi-asserted-by":"publisher","unstructured":"Wang HE, B\u00e9nar CG, Quilichini PP, Friston KJ, Jirsa VK, Bernard C (2014) A systematic framework for functional connectivity measures. Front Neurosci. https:\/\/doi.org\/10.3389\/fnins.2014.00405","DOI":"10.3389\/fnins.2014.00405"},{"issue":"60","key":"3068_CR73","doi-asserted-by":"publisher","first-page":"3021","DOI":"10.21105\/joss.03021","volume":"6","author":"ML Waskom","year":"2021","unstructured":"Waskom ML (2021) Seaborn: statistical data visualization. J Open Source Softw 6(60):3021. https:\/\/doi.org\/10.21105\/joss.03021","journal-title":"J Open Source Softw"},{"key":"3068_CR74","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1016\/j.neuroimage.2017.05.050","volume":"180","author":"H Xie","year":"2018","unstructured":"Xie H, Calhoun VD, Gonzalez-Castillo J, Damaraju E, Miller R, Bandettini PA, Mitra S (2018) Whole-brain connectivity dynamics reflect both task-specific and individual-specific modulation: a multitask study. Neuroimage 180:495\u2013504. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.05.050","journal-title":"Neuroimage"},{"issue":"1","key":"3068_CR75","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1162\/netn_a_00055","volume":"3","author":"J Zimmermann","year":"2018","unstructured":"Zimmermann J, Griffiths J, Schirner M, Ritter P, McIntosh AR (2018) Subject specificity of the correlation between large-scale structural and functional connectivity. Netw Neurosci 3(1):90\u2013106. https:\/\/doi.org\/10.1162\/netn_a_00055","journal-title":"Netw Neurosci"}],"container-title":["Brain Structure and Function"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00429-025-03068-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00429-025-03068-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00429-025-03068-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T07:51:39Z","timestamp":1770450699000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00429-025-03068-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,10]]},"references-count":75,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["3068"],"URL":"https:\/\/doi.org\/10.1007\/s00429-025-03068-3","relation":{},"ISSN":["1863-2661"],"issn-type":[{"value":"1863-2661","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,10]]},"assertion":[{"value":"20 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"12"}}