{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T20:34:17Z","timestamp":1793392457700,"version":"4.5.0"},"reference-count":70,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T00:00:00Z","timestamp":1681171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>The capacity to stay still during scanning, which is necessary to avoid motion confounds while imaging, varies markedly between people.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Here we investigated the effect of head motion on functional connectivity using connectome-based predictive modeling (CPM) and publicly available brain functional magnetic resonance imaging (fMRI) data from 414 individuals with low frame-to-frame motion (\u0394<jats:italic>d<\/jats:italic>\u2009&amp;lt;\u20090.18\u2009mm). Leave-one-out was used for internal cross-validation of head motion prediction in 207 participants, and twofold cross-validation was used in an independent sample (<jats:italic>n<\/jats:italic>\u2009=\u2009207).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results and Discussion<\/jats:title><jats:p>Parametric testing, as well as CPM-based permutations for null hypothesis testing, revealed strong linear associations between observed and predicted values of head motion. Motion prediction accuracy was higher for task- than for rest-fMRI, and for absolute head motion (<jats:italic>d<\/jats:italic>) than for \u0394<jats:italic>d<\/jats:italic>. Denoising attenuated the predictability of head motion, but stricter framewise displacement threshold (FD\u2009=\u20090.2\u2009mm) for motion censoring did not alter the accuracy of the predictions obtained with lenient censoring (FD\u2009=\u20090.5\u2009mm). For rest-fMRI, prediction accuracy was lower for individuals with low motion (mean \u0394<jats:italic>d<\/jats:italic>\u2009&amp;lt;\u20090.02\u2009mm; <jats:italic>n<\/jats:italic>\u2009=\u2009200) than for those with moderate motion (\u0394<jats:italic>d<\/jats:italic>\u2009&amp;lt;\u20090.04\u2009mm; <jats:italic>n<\/jats:italic>\u2009=\u2009414). The cerebellum and default-mode network (DMN) regions that forecasted individual differences in <jats:italic>d<\/jats:italic> and \u0394<jats:italic>d<\/jats:italic> during six different tasks- and two rest-fMRI sessions were consistently prone to the deleterious effect of head motion. However, these findings generalized to a novel group of 1,422 individuals but not to simulated datasets without neurobiological contributions, suggesting that cerebellar and DMN connectivity could partially reflect functional signals pertaining to inhibitory motor control during fMRI.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fnins.2023.1096232","type":"journal-article","created":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T05:07:42Z","timestamp":1681189662000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Brain motion networks predict head motion during rest- and task-fMRI"],"prefix":"10.3389","volume":"17","author":[{"given":"Dardo","family":"Tomasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nora D.","family":"Volkow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1016\/j.neuron.2007.10.038","article-title":"Disruption of large-scale brain systems in advanced aging","volume":"56","author":"Andrews-Hanna","year":"2007","journal-title":"Neuron"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1016\/j.neuroimage.2013.05.033","article-title":"Function in the human connectome: task-fMRI and individual differences in behavior","volume":"80","author":"Barch","year":"2013","journal-title":"Neuroimage"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.neuroimage.2007.04.042","article-title":"A component based noise correction method (CompCor) for BOLD and perfusion based fMRI","volume":"37","author":"Behzadi","year":"2007","journal-title":"Neuroimage"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"118993","DOI":"10.1016\/j.neuroimage.2022.118993","article-title":"Individualized event structure drives individual differences in whole-brain functional connectivity","volume":"252","author":"Betzel","year":"2022","journal-title":"Neuroimage"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1016\/j.neuroimage.2010.09.048","article-title":"Mapping anterior temporal lobe language areas with fMRI: a multicenter normative study","volume":"54","author":"Binder","year":"2011","journal-title":"Neuroimage"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"1536","DOI":"10.1016\/j.neuroimage.2006.02.048","article-title":"Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI","volume":"31","author":"Birn","year":"2006","journal-title":"Neuroimage"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"2322","DOI":"10.1152\/jn.00339.2011","article-title":"The organization of the human cerebellum estimated by intrinsic functional connectivity","volume":"106","author":"Buckner","year":"2011","journal-title":"J. Neurophysiol."},{"key":"ref8","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1038\/nn.3423","article-title":"Opportunities and limitations of intrinsic functional connectivity MRI","volume":"16","author":"Buckner","year":"2013","journal-title":"Nat. Neurosci."},{"key":"ref9","doi-asserted-by":"publisher","first-page":"154","DOI":"10.2967\/jnumed.110.079343","article-title":"MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner","volume":"52","author":"Catana","year":"2011","journal-title":"J. Nucl. Med."},{"key":"ref10","first-page":"1566","article-title":"Effect of patient motion on tomographic myocardial perfusion imaging","volume":"33","author":"Cooper","year":"1992","journal-title":"J. Nucl. Med."},{"key":"ref11","doi-asserted-by":"publisher","first-page":"1856","DOI":"10.1093\/cercor\/bhm207","article-title":"Reduced resting-state brain activity in the \"default network\" in normal aging","volume":"18","author":"Damoiseaux","year":"2008","journal-title":"Cereb. Cortex"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"3072","DOI":"10.1152\/jn.2000.84.6.3072","article-title":"Tracking the hemodynamic responses to reward and punishment in the striatum","volume":"84","author":"Delgado","year":"2000","journal-title":"J. Neurophysiol."},{"key":"ref13","doi-asserted-by":"publisher","first-page":"1358","DOI":"10.1126\/science.1194144","article-title":"Prediction of individual brain maturity using fMRI","volume":"329","author":"Dosenbach","year":"2010","journal-title":"Science"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"4341","DOI":"10.1038\/s41598-019-40737-w","article-title":"A study of the relationship between the level of anxiety declared by MRI patients in the STAI questionnaire and their respiratory rate acquired by a fibre-optic sensor system","volume":"9","author":"Dziuda","year":"2019","journal-title":"Sci. Rep."},{"key":"ref15","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.dcn.2017.01.011","article-title":"Children's head motion during fMRI tasks is heritable and stable over time","volume":"25","author":"Engelhardt","year":"2017","journal-title":"Dev. Cogn. Neurosci."},{"key":"ref16","doi-asserted-by":"publisher","first-page":"4028","DOI":"10.1073\/pnas.0800376105","article-title":"The maturing architecture of the brain's default network","volume":"105","author":"Fair","year":"2008","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"ref17","doi-asserted-by":"publisher","first-page":"13507","DOI":"10.1073\/pnas.0705843104","article-title":"Development of distinct control networks through segregation and integration","volume":"104","author":"Fair","year":"2007","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"ref18","doi-asserted-by":"publisher","first-page":"116400","DOI":"10.1016\/j.neuroimage.2019.116400","article-title":"Correction of respiratory artifacts in MRI head motion estimates","volume":"208","author":"Fair","year":"2020","journal-title":"Neuroimage"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.neuroimage.2017.05.007","article-title":"Reprint of: minimizing noise in pediatric task-based functional MRI; adolescents with developmental disabilities and typical development","volume":"154","author":"Fassbender","year":"2017","journal-title":"Neuroimage"},{"key":"ref20","doi-asserted-by":"publisher","first-page":"1664","DOI":"10.1038\/nn.4135","article-title":"Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity","volume":"18","author":"Finn","year":"2015","journal-title":"Nat. Neurosci."},{"key":"ref21","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/S0896-6273(02)00569-X","article-title":"Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain","volume":"33","author":"Fischl","year":"2002","journal-title":"Neuron"},{"key":"ref22","doi-asserted-by":"publisher","first-page":"e0265112","DOI":"10.1371\/journal.pone.0265112","article-title":"Getting the nod: pediatric head motion in a transdiagnostic sample during movie- and resting-state fMRI","volume":"17","author":"Frew","year":"2022","journal-title":"PLoS One"},{"key":"ref23","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1002\/mrm.1910350312","article-title":"Movement-related effects in fMRI time-series","volume":"35","author":"Friston","year":"1996","journal-title":"Magn. Reson. Med."},{"key":"ref24","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.neuroimage.2013.04.127","article-title":"The minimal preprocessing pipelines for the human connectome project","volume":"80","author":"Glasser","year":"2013","journal-title":"Neuroimage"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1093\/cercor\/bhu239","article-title":"Generation and evaluation of a cortical area Parcellation from resting-state correlations","volume":"26","author":"Gordon","year":"2016","journal-title":"Cereb. Cortex"},{"key":"ref26","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1097\/WCO.0b013e328306f2c5","article-title":"Resting-state functional connectivity in neuropsychiatric disorders","volume":"21","author":"Greicius","year":"2008","journal-title":"Curr. Opin. Neurol."},{"key":"ref27","doi-asserted-by":"publisher","first-page":"801","DOI":"10.1007\/s10548-014-0358-6","article-title":"Head motion parameters in fMRI differ between patients with mild cognitive impairment and Alzheimer disease versus elderly control subjects","volume":"27","author":"Haller","year":"2014","journal-title":"Brain Topogr."},{"key":"ref28","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1006\/nimg.2002.1179","article-title":"The amygdala response to emotional stimuli: a comparison of faces and scenes","volume":"17","author":"Hariri","year":"2002","journal-title":"Neuroimage"},{"key":"ref29","doi-asserted-by":"publisher","first-page":"150031","DOI":"10.1038\/sdata.2015.31","article-title":"Brain genomics Superstruct project initial data release with structural, functional, and behavioral measures","volume":"2","author":"Holmes","year":"2015","journal-title":"Sci Data"},{"key":"ref30","doi-asserted-by":"publisher","first-page":"1022","DOI":"10.1038\/s41467-019-08944-1","article-title":"Atypical functional connectome hierarchy in autism","volume":"10","author":"Hong","year":"2019","journal-title":"Nat. Commun."},{"key":"ref31","doi-asserted-by":"publisher","first-page":"825","DOI":"10.1006\/nimg.2002.1132","article-title":"Improved optimization for the robust and accurate linear registration and motion correction of brain images","volume":"17","author":"Jenkinson","year":"2002","journal-title":"Neuroimage"},{"key":"ref32","doi-asserted-by":"publisher","first-page":"825","DOI":"10.3389\/fnins.2019.00825","article-title":"Resting state fMRI: going through the motions","volume":"13","author":"Maknojia","year":"2019","journal-title":"Front. Neurosci."},{"key":"ref33","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1038\/s41586-022-04492-9","article-title":"Reproducible brain-wide association studies require thousands of individuals","volume":"603","author":"Marek","year":"2022","journal-title":"Nature"},{"key":"ref34","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1007\/s00247-00019-04514-00241","article-title":"Impact on child and parent anxiety level of a teddy bear-scale mock magnetic resonance scanner","volume":"50","author":"Morel","year":"2019","journal-title":"Pediatr. Radiol."},{"key":"ref35","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1148\/radiology.216.3.r00au46891","article-title":"Optimized single-slab three-dimensional spin-echo MR imaging of the brain","volume":"216","author":"Mugler","year":"2000","journal-title":"Radiology"},{"key":"ref36","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1002\/mrm.1910150117","article-title":"Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE)","volume":"15","author":"Mugler","year":"1990","journal-title":"Magn. Reson. Med."},{"key":"ref37","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1053\/j.semnuclmed.2008.01.002","article-title":"Respiratory motion in positron emission tomography\/computed tomography: a review","volume":"38","author":"Nehmeh","year":"2008","journal-title":"Semin. Nucl. Med."},{"key":"ref38","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1007\/978-3-030-59728-3_45","article-title":"The constrained network-based statistic: a new level of inference for neuroimaging","volume":"12267","author":"Noble","year":"2020","journal-title":"Med Image Comput Comput Assist Interven"},{"key":"ref39","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1097\/00002142-200202000-00005","article-title":"Pediatric functional magnetic resonance imaging: progress and challenges","volume":"13","author":"Poldrack","year":"2002","journal-title":"Top. Magn. Reson. Imaging"},{"key":"ref40","doi-asserted-by":"publisher","first-page":"2142","DOI":"10.1016\/j.neuroimage.2011.10.018","article-title":"Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion","volume":"59","author":"Power","year":"2012","journal-title":"Neuroimage"},{"key":"ref41","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1016\/j.neuroimage.2013.08.048","article-title":"Methods to detect, characterize, and remove motion artifact in resting state fMRI","volume":"84","author":"Power","year":"2014","journal-title":"Neuroimage"},{"key":"ref42","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1016\/j.neuroimage.2014.10.044","article-title":"Recent progress and outstanding issues in motion correction in resting state fMRI","volume":"105","author":"Power","year":"2015","journal-title":"Neuroimage"},{"key":"ref43","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.neuroimage.2015.02.064","article-title":"ICA-AROMA: a robust ICA-based strategy for removing motion artifacts from fMRI data","volume":"112","author":"Pruim","year":"2015","journal-title":"Neuroimage"},{"key":"ref44","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.neuroimage.2014.06.065","article-title":"Does motion-related brain functional connectivity reflect both artifacts and genuine neural activity?","volume":"101","author":"Pujol","year":"2014","journal-title":"Neuroimage"},{"key":"ref45","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1002\/mrm.10677","article-title":"Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI","volume":"51","author":"Rohde","year":"2004","journal-title":"Magn. Reson. Med."},{"key":"ref46","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1038\/nn.4179","article-title":"A neuromarker of sustained attention from whole-brain functional connectivity","volume":"19","author":"Rosenberg","year":"2016","journal-title":"Nat. Neurosci."},{"key":"ref47","doi-asserted-by":"publisher","first-page":"109084","DOI":"10.1016\/j.jneumeth.2021.109084","article-title":"Aging effect on head motion: a machine learning study on resting state fMRI data","volume":"352","author":"Sacc\u00e0","year":"2021","journal-title":"J. Neurosci. Methods"},{"key":"ref48","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/j.neuroimage.2013.11.046","article-title":"Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers","volume":"90","author":"Salimi-Khorshidi","year":"2014","journal-title":"Neuroimage"},{"key":"ref49","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1016\/j.neuroimage.2012.08.052","article-title":"An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data","volume":"64","author":"Satterthwaite","year":"","journal-title":"Neuroimage"},{"key":"ref50","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1016\/j.neuroimage.2011.12.063","article-title":"Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth","volume":"60","author":"Satterthwaite","year":"2012","journal-title":"Neuroimage"},{"key":"ref51","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.neuroimage.2013.06.045","article-title":"Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth","volume":"83","author":"Satterthwaite","year":"","journal-title":"Neuroimage"},{"key":"ref52","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1006\/nimg.2001.0829","article-title":"Quantifying head motion associated with motor tasks used in fMRI","volume":"14","author":"Seto","year":"2001","journal-title":"Neuroimage"},{"key":"ref53","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1093\/biomet\/52.3-4.591","article-title":"An analysis of variance test for normality (complete samples)","volume":"52","author":"Shapiro","year":"1965","journal-title":"Biometrika"},{"key":"ref54","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1038\/nprot.2016.178","article-title":"Using connectome-based predictive modeling to predict individual behavior from brain connectivity","volume":"12","author":"Shen","year":"2017","journal-title":"Nat. Protoc."},{"key":"ref55","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/j.neuroimage.2013.05.081","article-title":"Groupwise whole-brain parcellation from resting-state fMRI data for network node identification","volume":"82","author":"Shen","year":"2013","journal-title":"Neuroimage"},{"key":"ref56","doi-asserted-by":"publisher","first-page":"4492","DOI":"10.1093\/cercor\/bhw253","article-title":"Data quality influences observed links between functional connectivity and behavior","volume":"27","author":"Siegel","year":"2017","journal-title":"Cereb. Cortex"},{"key":"ref57","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.neuroimage.2013.05.039","article-title":"Resting-state fMRI in the human connectome project","volume":"80","author":"Smith","year":"2013","journal-title":"Neuroimage"},{"key":"ref58","doi-asserted-by":"publisher","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","article-title":"Advances in functional and structural MR image analysis and implementation as FSL","volume":"23","author":"Smith","year":"2004","journal-title":"Neuroimage"},{"key":"ref59","doi-asserted-by":"publisher","first-page":"1387","DOI":"10.1016\/j.neuroimage.2007.04.032","article-title":"Localizing the rostrolateral prefrontal cortex at the individual level","volume":"36","author":"Smith","year":"2007","journal-title":"Neuroimage"},{"key":"ref60","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1037\/0033-2909.87.2.245","article-title":"Tests for comparing elements of a correlation matrix","volume":"87","author":"Steiger","year":"1980","journal-title":"Psychol. Bull."},{"key":"ref61","doi-asserted-by":"publisher","first-page":"9885","DOI":"10.1073\/pnas.1001414107","article-title":"Functional connectivity density mapping","volume":"107","author":"Tomasi","year":"2010","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"ref62","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1006\/nimg.2001.0978","article-title":"Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain","volume":"15","author":"Tzourio-Mazoyer","year":"2002","journal-title":"Neuroimage"},{"key":"ref63","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.neuroimage.2013.05.012","article-title":"Pushing spatial and temporal resolution for functional and diffusion MRI in the human connectome project","volume":"80","author":"U\u011furbil","year":"2013","journal-title":"Neuroimage"},{"key":"ref64","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.neuroimage.2007.12.025","article-title":"Brain morphometry with multiecho MPRAGE","volume":"40","author":"Van Der Kouwe","year":"2008","journal-title":"Neuroimage"},{"key":"ref65","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1016\/j.neuroimage.2011.07.044","article-title":"The influence of head motion on intrinsic functional connectivity MRI","volume":"59","author":"Van Dijk","year":"2012","journal-title":"Neuroimage"},{"key":"ref66","doi-asserted-by":"publisher","first-page":"396","DOI":"10.1111\/j.2517-6161.1959.tb00346.x","article-title":"The comparison of regression variables","volume":"21","author":"Williams","year":"1959","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"ref67","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.neuroimage.2013.03.004","article-title":"A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics","volume":"76","author":"Yan","year":"2013","journal-title":"Neuroimage"},{"key":"ref68","doi-asserted-by":"publisher","first-page":"1126","DOI":"10.1152\/jn.00338.2011","article-title":"The organization of the human cerebral cortex estimated by intrinsic functional connectivity","volume":"106","author":"Yeo","year":"2011","journal-title":"J. Neurophysiol."},{"key":"ref69","doi-asserted-by":"publisher","first-page":"1481","DOI":"10.1002\/hbm.20616","article-title":"Quantification of head motion in children during various fMRI language tasks","volume":"30","author":"Yuan","year":"2009","journal-title":"Hum. Brain Mapp."},{"key":"ref70","doi-asserted-by":"publisher","first-page":"6058","DOI":"10.1073\/pnas.1317424111","article-title":"Neurobiological basis of head motion in brain imaging","volume":"111","author":"Zeng","year":"2014","journal-title":"Proc. Natl. Acad. Sci. U. S. A."}],"container-title":["Frontiers in Neuroscience"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1096232\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T05:07:46Z","timestamp":1681189666000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1096232\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,11]]},"references-count":70,"alternative-id":["10.3389\/fnins.2023.1096232"],"URL":"https:\/\/doi.org\/10.3389\/fnins.2023.1096232","relation":{},"ISSN":["1662-453X"],"issn-type":[{"value":"1662-453X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,11]]},"article-number":"1096232"}}