{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T16:31:18Z","timestamp":1785429078596,"version":"3.56.0"},"posted":{"date-parts":[[2024,6,11]]},"group-title":"Neuroscience","reference-count":59,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T00:00:00Z","timestamp":1718064000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"award":["T32DC017703"],"award-info":[{"award-number":["T32DC017703"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["F31HD107944"],"award-info":[{"award-number":["F31HD107944"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["R01HD094834"],"award-info":[{"award-number":["R01HD094834"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["R01HD096261"],"award-info":[{"award-number":["R01HD096261"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["U24AT011281"],"award-info":[{"award-number":["U24AT011281"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["R01DC013064"],"award-info":[{"award-number":["R01DC013064"]}],"id":[{"id":"https:\/\/ror.org\/01cwqze88","id-type":"ROR","asserted-by":"publisher"}]},{"award":["NRT-UtB1735225"],"award-info":[{"award-number":["NRT-UtB1735225"]}],"id":[{"id":"https:\/\/ror.org\/021nxhr62","id-type":"ROR","asserted-by":"publisher"}]},{"award":["NRT-2152202"],"award-info":[{"award-number":["NRT-2152202"]}],"id":[{"id":"https:\/\/ror.org\/021nxhr62","id-type":"ROR","asserted-by":"publisher"}]},{"award":["MCA-2120888"],"award-info":[{"award-number":["MCA-2120888"]}],"id":[{"id":"https:\/\/ror.org\/021nxhr62","id-type":"ROR","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000199","name":"United States Department of Agriculture","doi-asserted-by":"crossref","award":["2023-70440-40144"],"award-info":[{"award-number":["2023-70440-40144"]}],"id":[{"id":"10.13039\/100000199","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Department of Education, US","award":["GAANN P200A210098"],"award-info":[{"award-number":["GAANN P200A210098"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,8,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>The construction of growth charts trained to predict age or developmental deviation (the \u2018brain-age index\u2019) based on structural\/functional properties of the brain may be informative of children\u2019s neurodevelopmental trajectories. When applied to both typically and atypically developing populations, results may indicate that a particular condition is associated with atypical maturation of certain brain networks. Here, we focus on the relationship between reading disorder (RD) and maturation of functional connectivity (FC) patterns in the prototypical reading\/language network using a cross-sectional sample of N = 742 participants aged 6-21 years. A support vector regression model is trained to predict chronological age from FC data derived from a whole-brain model as well as multiple \u2018reduced\u2019 models, which are trained on FC data generated from a successively smaller number of regions in the brain\u2019s reading network. We hypothesized that the trained models would show systematic underestimation of brain network maturity for poor readers, particularly for the models trained with reading\/language regions. Comparisons of the different models\u2019 predictions revealed that while the whole-brain model outperforms the others in terms of overall prediction accuracy, all models successfully predicted brain maturity, including the one trained with the smallest amount of FC data. In addition, all models showed that reading ability affected the \u2018brain-age\u2019 gap, with poor readers\u2019 ages being underestimated and advanced readers\u2019 ages being overestimated. Exploratory results demonstrated that the most important regions and connections for prediction were derived from the default mode and frontoparietal control networks.<\/jats:p>\n                <jats:sec>\n                  <jats:title>Glossary<\/jats:title>\n                  <jats:p>Developmental dyslexia \/ reading disorder (RD): A specific learning disorder affecting reading ability in the absence of any other explanatory condition such as intellectual disability or visual impairment<\/jats:p>\n                  <jats:p>Support vector regression (SVR): A supervised machine learning technique which predicts continuous outcomes (such as chronological age) rather than classifying each observation; finds the best-fit function within a defined error margin<\/jats:p>\n                  <jats:p>Principal component analysis (PCA): A dimensionality reduction technique that transforms a high-dimensional dataset with many features per observation into a reduced set of \u2018principal components\u2019 for each observation; each component is a linear combination of several original (correlated) features, and the final set of components are all orthogonal (uncorrelated) to one another<\/jats:p>\n                  <jats:p>Brain-age index: A numerical index quantifying deviation from the brain\u2019s typical developmental trajectory for a single individual; may be based on a variety of morphometric or functional properties of the brain, resulting in different estimates for the same participant depending on the imaging modality used<\/jats:p>\n                  <jats:p>Brain-age gap (BAG): The difference, given in units of time, between a participant\u2019s true chronological age and a predictive model\u2019s estimated age for that participant based on brain data (Actual \u2013 Predicted); may be used as a brain-age index<\/jats:p>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:list list-type=\"bullet\">\n                      <jats:list-item>\n                        <jats:p>A machine learning model trained on functional data predicted participants\u2019 ages<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>The model showed variability in age prediction accuracy based on reading skills<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>The model highly weighted data from frontoparietal and default mode regions<\/jats:p>\n                      <\/jats:list-item>\n                      <jats:list-item>\n                        <jats:p>Neural markers of reading and language are diffusely represented in the brain<\/jats:p>\n                      <\/jats:list-item>\n                    <\/jats:list>\n                  <\/jats:sec>\n                <\/jats:sec>","DOI":"10.1101\/2024.06.10.597945","type":"posted-content","created":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T19:55:14Z","timestamp":1718135714000},"source":"Crossref","is-referenced-by-count":0,"title":["Modeling differences in neurodevelopmental maturity of the reading network using support vector regression on functional connectivity data"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5724-4135","authenticated-orcid":false,"given":"Oliver H.M.","family":"Lasnick","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brianna","family":"Kinnie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaan","family":"Kamal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Spencer","family":"Low","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4984-0812","authenticated-orcid":false,"given":"Natasza","family":"Marrouch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3932-9201","authenticated-orcid":false,"given":"Fumiko","family":"Hoeft","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2025080716050698000_2024.06.10.597945v2.1","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2017.181"},{"key":"2025080716050698000_2024.06.10.597945v2.2","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-020-00680-2"},{"key":"2025080716050698000_2024.06.10.597945v2.3","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-25089-1"},{"key":"2025080716050698000_2024.06.10.597945v2.4","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2024.101493"},{"key":"2025080716050698000_2024.06.10.597945v2.5","doi-asserted-by":"publisher","DOI":"10.1186\/s11689-018-9251-z"},{"key":"2025080716050698000_2024.06.10.597945v2.6","doi-asserted-by":"publisher","DOI":"10.1523\/ENEURO.0003-15.2015"},{"key":"2025080716050698000_2024.06.10.597945v2.7","doi-asserted-by":"publisher","DOI":"10.1196\/annals.1440.011"},{"key":"2025080716050698000_2024.06.10.597945v2.8","doi-asserted-by":"publisher","DOI":"10.3109\/03014460.2012.694475"},{"key":"2025080716050698000_2024.06.10.597945v2.9","doi-asserted-by":"publisher","DOI":"10.1037\/bul0000270"},{"key":"2025080716050698000_2024.06.10.597945v2.10","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2021.100928"},{"key":"2025080716050698000_2024.06.10.597945v2.11","doi-asserted-by":"publisher","DOI":"10.1016\/j.scib.2020.07.027"},{"key":"2025080716050698000_2024.06.10.597945v2.12","doi-asserted-by":"publisher","DOI":"10.1126\/science.1194144"},{"key":"2025080716050698000_2024.06.10.597945v2.13","unstructured":"Drucker, H. , Burges, C. J. C. , Kaufman, L. , Smola, A. , & Vapnik, V . (1997). Support vector regression machines. In Advances in neural information processing systems (Vol. 9). MIT Press."},{"key":"2025080716050698000_2024.06.10.597945v2.14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.09.017"},{"key":"2025080716050698000_2024.06.10.597945v2.15","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20718"},{"key":"2025080716050698000_2024.06.10.597945v2.16","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0184661"},{"key":"2025080716050698000_2024.06.10.597945v2.17","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-018-0235-4"},{"key":"2025080716050698000_2024.06.10.597945v2.18","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0800376105"},{"key":"2025080716050698000_2024.06.10.597945v2.19","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0705843104"},{"key":"2025080716050698000_2024.06.10.597945v2.20","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2007.07.043"},{"key":"2025080716050698000_2024.06.10.597945v2.21","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2018.00101"},{"key":"2025080716050698000_2024.06.10.597945v2.22","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.4931-05.2006"},{"key":"2025080716050698000_2024.06.10.597945v2.23","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1008950108"},{"key":"2025080716050698000_2024.06.10.597945v2.24","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpsc.2024.01.009"},{"key":"2025080716050698000_2024.06.10.597945v2.25","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2019.00001"},{"key":"2025080716050698000_2024.06.10.597945v2.26","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2016.0088"},{"key":"2025080716050698000_2024.06.10.597945v2.27","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2019.05.031"},{"key":"2025080716050698000_2024.06.10.597945v2.28","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.02.048"},{"key":"2025080716050698000_2024.06.10.597945v2.29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2010.07.013"},{"key":"2025080716050698000_2024.06.10.597945v2.30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.07.019"},{"key":"2025080716050698000_2024.06.10.597945v2.31","doi-asserted-by":"publisher","DOI":"10.1162\/jocn_a_00710"},{"key":"2025080716050698000_2024.06.10.597945v2.32","doi-asserted-by":"publisher","DOI":"10.1196\/annals.1416.024"},{"key":"2025080716050698000_2024.06.10.597945v2.33","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.22749"},{"key":"2025080716050698000_2024.06.10.597945v2.34","doi-asserted-by":"publisher","DOI":"10.1186\/s12993-024-00241-2"},{"key":"2025080716050698000_2024.06.10.597945v2.35","doi-asserted-by":"publisher","DOI":"10.1016\/S0006-3495(93)81441-3"},{"key":"2025080716050698000_2024.06.10.597945v2.36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neubiorev.2017.04.029"},{"key":"2025080716050698000_2024.06.10.597945v2.37","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2006.11.017"},{"key":"2025080716050698000_2024.06.10.597945v2.38","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-clinpsy-032814-112842"},{"key":"2025080716050698000_2024.06.10.597945v2.39","doi-asserted-by":"publisher","DOI":"10.1016\/j.visres.2019.03.007"},{"key":"2025080716050698000_2024.06.10.597945v2.40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2011.10.018"},{"key":"2025080716050698000_2024.06.10.597945v2.41","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2020.00155"},{"key":"2025080716050698000_2024.06.10.597945v2.42","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-7610.1975.tb01269.x"},{"key":"2025080716050698000_2024.06.10.597945v2.43","doi-asserted-by":"publisher","DOI":"10.22237\/JMASM\/1257035100"},{"key":"2025080716050698000_2024.06.10.597945v2.44","doi-asserted-by":"publisher","DOI":"10.1093\/cercor\/bhx179"},{"key":"2025080716050698000_2024.06.10.597945v2.45","doi-asserted-by":"publisher","DOI":"10.1016\/j.dcn.2023.101217"},{"key":"2025080716050698000_2024.06.10.597945v2.46","doi-asserted-by":"publisher","DOI":"10.1038\/s41583-021-00474-4"},{"key":"2025080716050698000_2024.06.10.597945v2.47","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2023.148668"},{"key":"2025080716050698000_2024.06.10.597945v2.48","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2019.00924"},{"key":"2025080716050698000_2024.06.10.597945v2.49","doi-asserted-by":"publisher","DOI":"10.1016\/j.bandl.2015.07.008"},{"key":"2025080716050698000_2024.06.10.597945v2.50","unstructured":"Torgesen, J.K. , Wagner, R.K. , & Rashotte, C.A . (2012). Test of word reading efficiency\u20132nd ed. (TOWRE-2). Austin, TX: Pro-Ed."},{"key":"2025080716050698000_2024.06.10.597945v2.51","doi-asserted-by":"publisher","DOI":"10.1038\/s42003-018-0073-z"},{"key":"2025080716050698000_2024.06.10.597945v2.52","doi-asserted-by":"publisher","DOI":"10.1177\/0022219413479673"},{"key":"2025080716050698000_2024.06.10.597945v2.53","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00783.2009"},{"key":"2025080716050698000_2024.06.10.597945v2.54","doi-asserted-by":"publisher","DOI":"10.1016\/j.bandl.2012.12.016"},{"key":"2025080716050698000_2024.06.10.597945v2.55","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.25660"},{"key":"2025080716050698000_2024.06.10.597945v2.56","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.23517"},{"key":"2025080716050698000_2024.06.10.597945v2.57","doi-asserted-by":"publisher","DOI":"10.1089\/brain.2012.0073"},{"key":"2025080716050698000_2024.06.10.597945v2.58","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuropsychologia.2015.12.003"},{"key":"2025080716050698000_2024.06.10.597945v2.59","doi-asserted-by":"publisher","DOI":"10.1152\/jn.00338.2011"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1101\/2024.06.10.597945","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T05:11:31Z","timestamp":1782277891000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.1101\/2024.06.10.597945"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,11]]},"references-count":59,"URL":"https:\/\/doi.org\/10.1101\/2024.06.10.597945","relation":{"is-preprint-of":[{"id-type":"doi","id":"10.1016\/j.dcn.2026.101716","asserted-by":"subject"}]},"subject":[],"published":{"date-parts":[[2024,6,11]]},"subtype":"preprint"}}