{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T14:20:18Z","timestamp":1783088418074,"version":"3.54.6"},"reference-count":40,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100022604","name":"Johanna Quandt Stiftung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100022604","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HD074601"],"award-info":[{"award-number":["R01HD074601"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HD093792"],"award-info":[{"award-number":["R01HD093792"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["533717223"],"award-info":[{"award-number":["533717223"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["5368"],"award-info":[{"award-number":["5368"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Developmental Science"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:label\/>\n                    <jats:p>Toddlers learn to recognize objects from different viewpoints with almost no supervision. During this learning, they execute frequent eye and head movements that shape their visual experience. It is presently unclear if and how these behaviors contribute to toddlers\u2019 emerging object recognition abilities. To answer this question, we here combine head\u2010mounted eye tracking during dyadic play with unsupervised machine learning. We approximate toddlers\u2019 central visual field experience by cropping image regions from a head\u2010mounted camera centered on the current gaze location estimated via eye tracking. This visual stream feeds a neural network model, which uses a biologically plausible unsupervised learning objective. Our experiments demonstrate that a few minutes of such first\u2010person experience suffice to learn strong object representations permitting invariant object recognition. Importantly, by simulating alternative gaze behaviors we show that toddlers\u2019 eye movement patterns play a crucial role in this. Our analysis also reveals that the limited size of the central visual field where visual acuity is high plays an important role for successful learning. Together, this highlights the benefits of temporally structured visual experience arising from toddlers\u2019 natural interactions with objects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>We combine recordings of toddlers\u2019 first\u2010person central visual field experience with biologically inspired self\u2010supervised learning algorithms to model toddlers\u2019 development of invariant object recognition.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Just a few minutes of toddlers\u2019 central visual field experience captured with head\u2010mounted eye tracking suffice to learn strong object representations.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Simulated alternative gaze behaviors produce weaker representations, demonstrating the importance of toddlers\u2019 active gaze strategies for learning.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Our results emphasize the importance of toddlers\u2019 eye movements for learning object representations.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/desc.70231","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T08:03:26Z","timestamp":1781597006000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Toddlers\u2019 Active Gaze Behavior Supports Self\u2010Supervised Object Learning"],"prefix":"10.1111","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2335-5288","authenticated-orcid":false,"given":"Zhengyang","family":"Yu","sequence":"first","affiliation":[{"name":"Frankfurt Institute for Advanced Studies  Frankfurt Hessen Germany"},{"name":"Xidian\u2010FIAS International Joint Research Center  Frankfurt Hessen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3495-4323","authenticated-orcid":false,"given":"Arthur","family":"Aubret","sequence":"additional","affiliation":[{"name":"Frankfurt Institute for Advanced Studies  Frankfurt Hessen Germany"},{"name":"Xidian\u2010FIAS International Joint Research Center  Frankfurt Hessen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7990-5629","authenticated-orcid":false,"given":"Marcel C.","family":"Raabe","sequence":"additional","affiliation":[{"name":"Frankfurt Institute for Advanced Studies  Frankfurt Hessen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3946-1811","authenticated-orcid":false,"given":"Jane","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Psychology Center for Perceptual Systems University of Texas at Austin  Austin Texas USA"},{"name":"Department of Psychology University of California  San Diego California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1473-3179","authenticated-orcid":false,"given":"Chen","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Psychology Center for Perceptual Systems University of Texas at Austin  Austin Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8166-2441","authenticated-orcid":false,"given":"Jochen","family":"Triesch","sequence":"additional","affiliation":[{"name":"Frankfurt Institute for Advanced Studies  Frankfurt Hessen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,16]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"crossref","unstructured":"Abbas A. andS.Deny.2023. \u201cProgress and Limitations of Deep Networks to Recognize Objects in Unusual Poses.\u201d InProceedings of the AAAI Conference on Artificial Intelligence vol.37:160\u2013168.","DOI":"10.1609\/aaai.v37i1.25087"},{"key":"e_1_2_11_3_1","unstructured":"Aubret A. M.Ernst C.Teuli\u00e8re andJ.Triesch.2022a. \u201cTime to Augment Self\u2010Supervised Visual Representation Learning.\u201d InThe Eleventh International Conference on Learning Representations (ICLR).https:\/\/openreview.net\/forum?id=o8xdgmwCP8l."},{"key":"e_1_2_11_4_1","doi-asserted-by":"crossref","unstructured":"Aubret A. C.Teuli\u00e8r andJ.Triesch.2022b. \u201cToddler\u2010Inspired Embodied Vision for Learning Object Representations.\u201d In2022 IEEE International Conference on Development and Learning (ICDL) 81\u201387.IEEE.","DOI":"10.1109\/ICDL53763.2022.9962190"},{"key":"e_1_2_11_5_1","doi-asserted-by":"crossref","unstructured":"Aubret A. C.Teuli\u00e8re andJ.Triesch.2024. \u201cSelf\u2010Supervised Visual Learning From Interactions With Objects.\u201d InEuropean Conference on Computer Vision (ECCV) 54\u201371.","DOI":"10.1007\/978-3-031-73226-3_4"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s44159-023-00266-w"},{"key":"e_1_2_11_7_1","first-page":"1209","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems (NeurlPS)","author":"Bambach S.","year":"2018"},{"key":"e_1_2_11_8_1","unstructured":"Chen T. S.Kornblith M.Norouzi andG.Hinton.2020. \u201cA Simple Framework for Contrastive Learning of Visual Representations.\u201d InInternational Conference on Machine Learning 1597\u20131607.PMLR."},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2666"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.2.194"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/infa.12119"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00171"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/0166-2236(92)90344-8"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00181769"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.infbeh.2005.10.002"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.1160028"},{"key":"e_1_2_11_17_1","unstructured":"Lotter W. G.Kreiman andD.Cox.2016. \u201cDeep Predictive Coding Networks for Video Prediction and Unsupervised Learning.\u201d InThe Fifth International Conference on Learning Representations (ICLR).https:\/\/openreview.net\/forum?id=B1ewdt9xe."},{"issue":"11","key":"e_1_2_11_18_1","first-page":"2579","article-title":"Visualizing Data Using T\u2010SNE","volume":"9","author":"Maaten L.","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cogdev.2017.02.006"},{"key":"e_1_2_11_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/335817a0"},{"key":"e_1_2_11_21_1","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-024-00802-0"},{"key":"e_1_2_11_22_1","first-page":"363","volume-title":"Proceedings of the Annual Meeting of the Cognitive Science Society, 46 (CogSci)","author":"Orhan A. E.","year":"2024"},{"key":"e_1_2_11_23_1","first-page":"9960","article-title":"Self\u2010Supervised Learning Through the Eyes of a Child","volume":"33","author":"Orhan E.","year":"2020","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_2_11_24_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-7687.2008.00747.x"},{"key":"e_1_2_11_25_1","doi-asserted-by":"publisher","DOI":"10.1002\/cne.902330403"},{"key":"e_1_2_11_26_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnbeh.2024.1425496"},{"key":"e_1_2_11_27_1","doi-asserted-by":"crossref","unstructured":"Raabe M. C. F. M.L\u00f3pez Z.Yu et\u00a0al.2023. \u201cSaccade Amplitude Statistics are Explained by Cortical Magnification.\u201d In2023 IEEE International Conference on Development and Learning (ICDL) 300\u2013305.IEEE.","DOI":"10.1109\/ICDL55364.2023.10364440"},{"key":"e_1_2_11_28_1","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195142938.003.0007"},{"key":"e_1_2_11_29_1","doi-asserted-by":"publisher","DOI":"10.1038\/4580"},{"key":"e_1_2_11_30_1","doi-asserted-by":"crossref","unstructured":"Ruan S. Y.Dong H.Su J.Peng N.Chen andX.Wei.2023. \u201cTowards Viewpoint\u2010 Invariant Visual Recognition via Adversarial Training.\u201d InProceedings of the IEEE\/CVF International Conference on Computer Vision 4709\u20134719.","DOI":"10.1109\/ICCV51070.2023.00434"},{"key":"e_1_2_11_31_1","unstructured":"Schneider F. X.Xu M. R.Ernst Z.Yu andJ.Triesch.2021. \u201cContrastive Learning Through Time.\u201d InSVRHM 2021 Workshop NeurIPS."},{"key":"e_1_2_11_32_1","first-page":"54199","article-title":"Curriculum Learning With Infant Egocentric Videos","volume":"36","author":"Sheybani S.","year":"2024","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_2_11_33_1","doi-asserted-by":"publisher","DOI":"10.1167\/jov.23.9.4685"},{"key":"e_1_2_11_34_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9280.03439"},{"key":"e_1_2_11_35_1","volume-title":"EPIC 2021 Workshop CVPR","author":"Tsutsui S.","year":"2021"},{"key":"e_1_2_11_36_1","unstructured":"Wang B. D.Mayo A.Deza A.Barbu andC.Conwell.2021. \u201cOn the Use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation.\u201d InSVRHM 2021 Workshop NeurIPS."},{"key":"e_1_2_11_37_1","doi-asserted-by":"publisher","DOI":"10.1162\/089976602317318938"},{"key":"e_1_2_11_38_1","doi-asserted-by":"crossref","unstructured":"Xu X. andJ.Triesch.2023. \u201cCiper: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning.\u201d InInternational Conference on Artificial Neural Networks 320\u2013331.Springer.","DOI":"10.1007\/978-3-031-44213-1_27"},{"key":"e_1_2_11_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cognition.2012.06.016"},{"key":"e_1_2_11_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neures.2014.09.004"},{"key":"e_1_2_11_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neures.2023.11.006"}],"container-title":["Developmental Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/desc.70231","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/desc.70231","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/desc.70231","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T13:31:00Z","timestamp":1783085460000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/desc.70231"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,16]]},"references-count":40,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["10.1111\/desc.70231"],"URL":"https:\/\/doi.org\/10.1111\/desc.70231","archive":["Portico"],"relation":{},"ISSN":["1363-755X","1467-7687"],"issn-type":[{"value":"1363-755X","type":"print"},{"value":"1467-7687","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,16]]},"assertion":[{"value":"2025-11-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-05-18","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-06-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70231"}}