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  • Review Article
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Development of visual object recognition

Abstract

Object recognition is the process by which humans organize the visual world into meaningful perceptual units. In this Review, we examine the developmental origins and maturation of object recognition by synthesizing research from developmental psychology, cognitive neuroscience and computational modelling. We describe the extent to which infants demonstrate early traces of adult visual competencies within their first year. The rapid development of these competencies is supported by infant-specific biological and experiential constraints, including blurry vision and ‘self-curation’ of object viewpoints that best support learning. We also discuss how the neural mechanisms that support object-recognition abilities in infancy seem to differ from those in adulthood, with less engagement of the ventral visual pathway. We conclude that children’s specific developmental niche shapes early object-recognition abilities and their neural underpinnings.

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Fig. 1: Different retinal projections of a dog.
Fig. 2: Procedures for studying the development of visual perception and object recognition.
Fig. 3: Shape sensitivity in the infant brain.
Fig. 4: One-shot object categorization in human infants.
Fig. 5: Experience is necessary for the development of category-selectivity.
Fig. 6: Development of visual functions.

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References

  1. Feldman, J. What is a visual object? Trends Cogn. Sci. 7, 252–256 (2003).

    Article  PubMed  Google Scholar 

  2. Spelke, E. S. Principles of object perception. Cogn. Sci. 14, 29–56 (1990).

    Article  Google Scholar 

  3. Grill-Spector, K. & Kanwisher, N. Visual recognition: as soon as you know it is there, you know what it is. Psychol. Sci. 16, 152–160 (2005).

    Article  PubMed  Google Scholar 

  4. Thorpe, S., Fize, D. & Marlot, C. Speed of processing in the human visual system. Nature 381, 520–522 (1996).

    Article  CAS  PubMed  ADS  Google Scholar 

  5. Keysers, C., Xiao, D.-K., Földiák, P. & Perrett, D. I. The speed of sight. J. Cogn. Neurosci. 13, 90–101 (2001).

    Article  CAS  PubMed  Google Scholar 

  6. Shepard, R. N. Toward a universal law of generalization for psychological science. Science 237, 1317–1323 (1987).

    Article  MathSciNet  CAS  PubMed  ADS  Google Scholar 

  7. Tenenbaum, J. B. & Griffiths, T. L. Generalization, similarity, and Bayesian inference. Behav. Brain. Sci. 24, 629–640 (2001).

    Article  CAS  PubMed  Google Scholar 

  8. Morgenstern, Y., Schmidt, F. & Fleming, R. W. One-shot categorization of novel object classes in humans. Vis. Res. 165, 98–108 (2019).

    Article  PubMed  Google Scholar 

  9. Lake, B., Salakhutdinov, R., Gross, J. & Tenenbaum, J. One shot learning of simple visual concepts. In Proc. Ann. Meet. Cogn. Sci. Soc. (CogSci, 2011).

  10. Tiedemann, H., Morgenstern, Y., Schmidt, F. & Fleming, R. W. One-shot generalization in humans revealed through a drawing task. eLife 11, e75485 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Marr, D. & Nishihara, H. K. Representation and recognition of the spatial organization of three-dimensional shapes. Proc. R. Soc. Lond. Ser. B 200, 269–294 (1978).

    Article  CAS  ADS  Google Scholar 

  12. Hubel, D. H. & Wiesel, T. N. Receptive fields of single neurones in the cat’s striate cortex. J. Physiol. 148, 574–591 (1959).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kanwisher, N. & Dilks, D. D. in The New Visual Neuroscience (eds Chalupa, L. & J. Werner, J.) 733–748 (MIT Press, 2012).

  14. Ayzenberg, V. & Behrmann, M. Does the brain’s ventral visual pathway compute object shape? Trends Cogn. Sci. 26, 1119–1132 (2022).

    Article  PubMed  Google Scholar 

  15. Freud, E., Behrmann, M. & Snow, J. C. What does dorsal cortex contribute to perception? Open Mind 4, 40–56 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Welchman, A. E. The human brain in depth: how we see in 3D. Annu. Rev. Vis. Sci. 2, 345–376 (2016).

    Article  PubMed  Google Scholar 

  17. Van Dromme, I. C., Premereur, E., Verhoef, B.-E., Vanduffel, W. & Janssen, P. Posterior parietal cortex drives inferotemporal activations during three-dimensional object vision. PLoS Biol. 14, e1002445 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ayzenberg, V. & Behrmann, M. The dorsal visual pathway represents object-centered spatial relations for object recognition. J. Neurosci. 42, 4693–4710 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zachariou, V., Nikas, C. V., Safiullah, Z. N., Gotts, S. J. & Ungerleider, L. G. Spatial mechanisms within the dorsal visual pathway contribute to the configural processing of faces. Cereb. Cortex 27, 4124–4138 (2017).

    PubMed  Google Scholar 

  20. Kar, K., Kubilius, J., Schmidt, K., Issa, E. B. & DiCarlo, J. J. Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior. Nat. Neurosci. 22, 974–983 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bar, M. et al. Top-down facilitation of visual recognition. Proc. Natl Acad. Sci. USA 103, 449–454 (2006).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  22. Zamir, A. R. et al. Taskonomy: disentangling task transfer learning. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 3712–3722 (IEEE, 2018).

  23. Blauch, N. M., Behrmann, M. & Plaut, D. C. A connectivity-constrained computational account of topographic organization in high-level visual cortex. Proc. Natl Acad. Sci. USA 119, e2112566119 (2022).

    Article  MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  24. Doerig, A. et al. The neuroconnectionist research programme. Nat. Rev. Neurosci. 24, 431–450 (2023).

    Article  CAS  PubMed  Google Scholar 

  25. Zador, A. M. A critique of pure learning and what artificial neural networks can learn from animal brains. Nat. Commun. 10, 3770 (2019).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  26. Geirhos, R. et al. Partial success in closing the gap between human and machine vision. Adv. Neural Inf. Process. Syst. 34, 23885–23899 (2021).

    Google Scholar 

  27. Biederman, I. Recognition-by-components: a theory of human image understanding. Psychol. Rev. 94, 115–147 (1987).

    Article  PubMed  Google Scholar 

  28. Mervis, C. B. & Rosch, E. Categorization of natural objects. Annu. Rev. Psychol. 32, 89–115 (1981).

    Article  Google Scholar 

  29. Elder, J. H. & Velisavljević, L. Cue dynamics underlying rapid detection of animals in natural scenes. J. Vision 9, https://doi.org/10.1167/9.7.7 (2009).

  30. Geirhos, R. et al. ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. Preprint at arXiv https://arxiv.org/abs/1811.12231 (2018).

  31. Landau, B., Smith, L. B. & Jones, S. S. The importance of shape in early lexical learning. Cogn. Dev. 3, 299–321 (1988).

    Article  Google Scholar 

  32. Wagemans, J. et al. Identification of everyday objects on the basis of silhouette and outline versions. Perception 37, 207–244 (2008).

    Article  PubMed  Google Scholar 

  33. Biederman, I. & Ju, G. Surface versus edge-based determinants of visual recognition. Cogn. Psychol. 20, 38–64 (1988).

    Article  CAS  PubMed  Google Scholar 

  34. Fantz, R. L. Visual experience in infants: decreased attention to familiar patterns relative to novel ones. Science 146, 668–670 (1964).

    Article  CAS  PubMed  ADS  Google Scholar 

  35. Slater, A., Morison, V. & Rose, D. Perception of shape by the new‐born baby. Br. J. Dev. Psychol. 1, 135–142 (1983).

    Article  Google Scholar 

  36. Slater, A. & Morison, V. Shape constancy and slant perception at birth. Perception 14, 337-344 (1985).

    Article  CAS  PubMed  Google Scholar 

  37. Quinn, P. C., Eimas, P. D. & Tarr, M. J. Perceptual categorization of cat and dog silhouettes by 3-to 4-month-old infants. J. Exp. Child. Psychol. 79, 78–94 (2001).

    Article  CAS  PubMed  Google Scholar 

  38. Behrmann, M., Peterson, M. A., Moscovitch, M. & Suzuki, S. Independent representation of parts and the relations between them: evidence from integrative agnosia. J. Exp. Psychol. Hum. Percept. Perform. 32, 1169–1184 (2006).

    Article  PubMed  Google Scholar 

  39. Grill-Spector, K., Kourtzi, Z. & Kanwisher, N. The lateral occipital complex and its role in object recognition. Vis. Res. 41, 1409–1422 (2001).

    Article  CAS  PubMed  Google Scholar 

  40. Emberson, L. L., Crosswhite, S. L., Richards, J. E. & Aslin, R. N. The lateral occipital cortex is selective for object shape, not texture/color, at six months. J. Neurosci. 37, 3698–3703 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Aslin, R. N. & Mehler, J. Near-infrared spectroscopy for functional studies of brain activity in human infants: promise, prospects, and challenges. J. Biomed. Opt. 10, 1083–3668 (2005).

    Article  Google Scholar 

  42. Wilcox, T. & Biondi, M. fNIRS in the developmental sciences. Wiley Interdisc. Rev. Cogn. Sci. 6, 263–283 (2015).

    Article  Google Scholar 

  43. Wilcox, T. et al. Hemodynamic changes in the infant cortex during the processing of featural and spatiotemporal information. Neuropsychologia 47, 657–662 (2009).

    Article  PubMed  Google Scholar 

  44. Wilcox, T., Hawkins, L. B., Hirshkowitz, A. & Boas, D. A. Cortical activation to object shape and speed of motion during the first year. NeuroImage 99, 129–141 (2014).

    Article  PubMed  Google Scholar 

  45. Wilcox, T., Bortfeld, H., Woods, R., Wruck, E. & Boas, D. A. Hemodynamic response to featural changes in the occipital and inferior temporal cortex in infants: a preliminary methodological exploration. Dev. Sci. 11, 361–370 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Golarai, G. et al. Differential development of high-level visual cortex correlates with category-specific recognition memory. Nat. Neurosci. 10, 512–522 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Scherf, K. S., Behrmann, M., Humphreys, K. & Luna, B. Visual category‐selectivity for faces, places and objects emerges along different developmental trajectories. Dev. Sci. 10, F15–F30 (2007).

    Article  PubMed  Google Scholar 

  48. Freud, E., Plaut, D. C. & Behrmann, M. Protracted developmental trajectory of shape processing along the two visual pathways. J. Cogn. Neurosci. 31, 1589–1597 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Nishimura, M., Scherf, K. S., Zachariou, V., Tarr, M. J. & Behrmann, M. Size precedes view: developmental emergence of invariant object representations in lateral occipital complex. J. Cogn. Neurosci. 27, 474–491 (2015).

    Article  PubMed  Google Scholar 

  50. Dekker, T., Mareschal, D., Sereno, M. I. & Johnson, M. H. Dorsal and ventral stream activation and object recognition performance in school-age children. NeuroImage 57, 659–670 (2011).

    Article  PubMed  Google Scholar 

  51. Wilcox, T., Stubbs, J., Hirshkowitz, A. & Boas, D. A. Functional activation of the infant cortex during object processing. NeuroImage 62, 1833–1840 (2012).

    Article  PubMed  Google Scholar 

  52. Lourenco, S. F. & Huttenlocher, J. The representation of geometric cues in infancy. Infancy 13, 103–127 (2008).

    Article  PubMed  Google Scholar 

  53. Dillon, M. R., Izard, V. & Spelke, E. S. Infants’ sensitivity to shape changes in 2D visual forms. Infancy 25, 618–639 (2020).

    Article  PubMed  Google Scholar 

  54. Slater, A., Mattock, A., Brown, E. & Bremner, J. G. Form perception at birth: revisited. J. Exp. Child. Psychol. 51, 395–406 (1991).

    Article  CAS  PubMed  Google Scholar 

  55. Cohen, L. B. & Younger, B. A. Infant perception of angular relations. Infant. Behav. Dev. 7, 37–47 (1984).

    Article  Google Scholar 

  56. Bhatt, R. S. & Waters, S. E. Perception of three-dimensional cues in early infancy. J. Exp. Child. Psychol. 70, 207–224 (1998).

    Article  CAS  PubMed  Google Scholar 

  57. Kavšek, M., Yonas, A. & Granrud, C. E. Infants’ sensitivity to pictorial depth cues: a review and meta-analysis of looking studies. Infant. Behav. Dev. 35, 109–128 (2012).

    Article  PubMed  Google Scholar 

  58. Biederman, I. & Cooper, E. E. Priming contour-deleted images: evidence for intermediate representations in visual object recognition. Cogn. Psychol. 23, 393–419 (1991).

    Article  CAS  PubMed  Google Scholar 

  59. Ayzenberg, V. & Lourenco, S. F. Skeletal descriptions of shape provide unique perceptual information for object recognition. Sci. Rep. 9, 9359 (2019).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  60. Wagemans, J. et al. A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure–ground organization. Psychol. Bull. 138, 1172–1217 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Quinn, P. C., Bhatt, R. S., Brush, D., Grimes, A. & Sharpnack, H. Development of form similarity as a Gestalt grouping principle in infancy. Psychol. Sci. 13, 320–328 (2002).

    Article  PubMed  Google Scholar 

  62. Schmidt, H. & Spelke, E. Gestalt relations and object perception in infancy. Infant. Behav. Dev. 7, 319 (1984).

    Article  Google Scholar 

  63. Farroni, T., Valenza, E., Simion, F. & Umiltà, C. Configural processing at birth: evidence for perceptual organisation. Perception 29, 355–372 (2000).

    Article  CAS  PubMed  Google Scholar 

  64. Johnson, S. P. & Aslin, R. N. Perception of object unity in 2-month-old infants. Dev. Psychol. 31, 739–745 (1995).

    Article  Google Scholar 

  65. Slater, A., Johnson, S. P., Brown, E. & Badenoch, M. Newborn infant’s perception of partly occluded objects. Infant. Behav. Dev. 19, 145–148 (1996).

    Article  Google Scholar 

  66. Kellman, P. J. & Spelke, E. S. Perception of partly occluded objects in infancy. Cogn. Psychol. 15, 483–524 (1983).

    Article  CAS  PubMed  Google Scholar 

  67. Slater, A. et al. Newborn and older infants’ perception of partly occluded objects. Infant. Behav. Dev. 13, 33–49 (1990).

    Article  Google Scholar 

  68. Cassia, V. M., Simion, F., Milani, I. & Umiltà, C. Dominance of global visual properties at birth. J. Exp. Psychol. Gen. 131, 398 (2002).

    Article  PubMed  Google Scholar 

  69. Ayzenberg, V. & Lourenco, S. Perception of an object’s global shape is best described by a model of skeletal structure in human infants. eLife 11, e74943 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Ghim, H.-R. & Eimas, P. D. Global and local processing by 3-and 4-month-old infants. Percept. Psychophys. 43, 165–171 (1988).

    Article  CAS  PubMed  Google Scholar 

  71. von der Heydt, R. Figure–ground organization and the emergence of proto-objects in the visual cortex. Front. Psychol. 6, 1695 (2015).

    PubMed  PubMed Central  Google Scholar 

  72. Lee, T. S., Mumford, D., Romero, R. & Lamme, V. A. The role of the primary visual cortex in higher level vision. Vis. Res. 38, 2429–2454 (1998).

    Article  CAS  PubMed  Google Scholar 

  73. Wokke, M. E., Vandenbroucke, A. R., Scholte, H. S. & Lamme, V. A. Confuse your illusion: feedback to early visual cortex contributes to perceptual completion. Psychol. Sci. 24, 63–71 (2013).

    Article  PubMed  Google Scholar 

  74. Tang, H. et al. Recurrent computations for visual pattern completion. Proc. Natl Acad. Sci. USA 115, 8835–8840 (2018).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  75. Kietzmann, T. C. et al. Recurrence is required to capture the representational dynamics of the human visual system. Proc. Natl Acad. Sci. USA 116, 21854–21863 (2019).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  76. Schrimpf, M. et al. Brain-score: which artificial neural network for object recognition is most brain-like? Preprint at bioRxiv https://doi.org/10.1101/407007 (2018).

  77. Batardière, A. et al. Early specification of the hierarchical organization of visual cortical areas in the macaque monkey. Cereb. Cortex 12, 453–465 (2002).

    Article  PubMed  Google Scholar 

  78. Burkhalter, A. Development of forward and feedback connections between areas V1 and V2 of human visual cortex. Cereb. Cortex 3, 476–487 (1993).

    Article  CAS  PubMed  Google Scholar 

  79. Coogan, T. A. & Van Essen, D. C. Development of connections within and between areas V1 and V2 of macaque monkeys. J. Comp. Neurol. 372, 327–342 (1996).

    Article  CAS  PubMed  Google Scholar 

  80. Burkhalter, A., Bernardo, K. L. & Charles, V. Development of local circuits in human visual cortex. J. Neurosci. 13, 1916–1931 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Smyser, C. D. et al. Longitudinal analysis of neural network development in preterm infants. Cereb. Cortex 20, 2852–2862 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Nagy, Z., Westerberg, H. & Klingberg, T. Maturation of white matter is associated with the development of cognitive functions during childhood. J. Cogn. Neurosci. 16, 1227–1233 (2004).

    Article  PubMed  Google Scholar 

  83. Emberson, L. L., Richards, J. E. & Aslin, R. N. Top-down modulation in the infant brain: learning-induced expectations rapidly affect the sensory cortex at 6 months. Proc. Natl Acad. Sci. USA 112, 9585–9590 (2015).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  84. Kouider, S. et al. A neural marker of perceptual consciousness in infants. Science 340, 376–380 (2013).

    Article  CAS  PubMed  ADS  Google Scholar 

  85. Ayzenberg, V. & Lourenco, S. Young children outperform feed-forward and recurrent neural networks on challenging object recognition tasks. J. Vis. 20, 310–310 (2020).

    Article  Google Scholar 

  86. Káldy, Z. & Kovács, I. Visual context integration is not fully developed in 4-year-old children. Perception 32, 657–666 (2003).

    Article  PubMed  Google Scholar 

  87. Kovács, I. Human development of perceptual organization. Vis. Res. 40, 1301–1310 (2000).

    Article  PubMed  Google Scholar 

  88. Kovács, I., Kozma, P., Fehér, Á. & Benedek, G. Late maturation of visual spatial integration in humans. Proc. Natl Acad. Sci. USA 96, 12204–12209 (1999).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  89. Scherf, K. S., Behrmann, M., Kimchi, R. & Luna, B. Emergence of global shape processing continues through adolescence. Child. Dev. 80, 162–177 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  90. Atkinson, J. Human visual development over the first 6 months of life. A review and a hypothesis. Hum. Neurobiol. 3, 61–74 (1983).

    Google Scholar 

  91. Banks, M. S. & Salapatek, P. Infant pattern vision: a new approach based on the contrast sensitivity function. J. Exp. Child. Psychol. 31, 1–45 (1981).

    Article  CAS  PubMed  Google Scholar 

  92. Atkinson, J., Braddick, O. & Braddick, F. Acuity and contrast sensivity of infant vision. Nature 247, 403–404 (1974).

    Article  CAS  PubMed  ADS  Google Scholar 

  93. Brown, A. M. & Yamamoto, M. Visual acuity in newborn and preterm infants measured with grating acuity cards. Am. J. Ophthalmol. 102, 245–253 (1986).

    Article  CAS  PubMed  Google Scholar 

  94. Sokol, S. Measurement of infant visual acuity from pattern reversal evoked potentials. Vis. Res. 18, 33–39 (1978).

    Article  CAS  PubMed  Google Scholar 

  95. Newport, E. L. Maturational constraints on language learning. Cogn. Sci. 14, 11–28 (1990).

    Article  Google Scholar 

  96. Elman, J. L. Learning and development in neural networks: the importance of starting small. Cognition 48, 71–99 (1993).

    Article  CAS  PubMed  Google Scholar 

  97. Bjorklund, D. F. The role of immaturity in human development. Psychol. Bull. 122, 153–169 (1997).

    Article  CAS  PubMed  Google Scholar 

  98. Lickliter, R. Premature visual stimulation accelerates intersenory functioning in bobwhite quail neonates. Dev. Psychobiol. 23, 15–27 (1990).

    Article  CAS  PubMed  Google Scholar 

  99. Lickliter, R. & Hellewell, T. B. in Developmental Time and Timing (eds Lurkewitz, G. & Devenny, D. A.) 105–124 (Lawrence Erlbaum, 1993).

  100. Kenny, P. A. & Turkewitz, G. Effects of unusually early visual stimulation on the development of homing behavior in the rat pup. Dev. Psychobiol. 19, 57–66 (1986).

    Article  CAS  PubMed  Google Scholar 

  101. Harlow, H. F. The development of learning in the rhesus monkey. Sci. Prog. 12, 239–269 (1959).

    Google Scholar 

  102. Ostrovsky, Y., Meyers, E., Ganesh, S., Mathur, U. & Sinha, P. Visual parsing after recovery from blindness. Psychol. Sci. 20, 1484–1491 (2009).

    Article  PubMed  Google Scholar 

  103. Le Grand, R., Mondloch, C. J., Maurer, D. & Brent, H. P. Early visual experience and face processing. Nature 410, 890–890 (2001).

    Article  PubMed  ADS  Google Scholar 

  104. Ellemberg, D., Lewis, T. L., Maurer, D., Brar, S. & Brent, H. P. Better perception of global motion after monocular than after binocular deprivation. Vis. Res. 42, 169–179 (2002).

    Article  PubMed  Google Scholar 

  105. Vogelsang, L. et al. Potential downside of high initial visual acuity. Proc. Natl Acad. Sci. USA 115, 11333–11338 (2018).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  106. Jang, H. & Tong, F. Convolutional neural networks trained with a developmental sequence of blurry to clear images reveal core differences between face and object processing. J. Vis. 21, 6 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Jinsi, O., Henderson, M. M. & Tarr, M. J. Early experience with low-pass filtered images facilitates visual category learning in a neural network model. PLoS One 18, e0280145 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Wang, W., Zhou, T., Chen, L. & Huang, Y. A subcortical magnocellular pathway is responsible for the fast processing of topological properties of objects: a transcranial magnetic stimulation study. Hum. Brain Mapp. 44, 1617–1628 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  109. Felleman, D. J. & Van Essen, D. C. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1–47 (1991).

    Article  CAS  PubMed  Google Scholar 

  110. Rakic, P., Barlow, H. B. & Gaze, R. M. Prenatal development of the visual system in rhesus monkey. Phil. Trans. R. Soc. Lond. B 278, 245–260 (1977).

    Article  CAS  ADS  Google Scholar 

  111. Kogan, C. S., Zangenehpour, S. & Chaudhuri, A. Developmental profiles of SMI-32 immunoreactivity in monkey striate cortex. Dev. Brain Res. 119, 85–95 (2000).

    Article  CAS  Google Scholar 

  112. Hammarrenger, B. et al. Magnocellular and parvocellular developmental course in infants during the first year of life. Doc. Ophthalmol. 107, 225–233 (2003).

    Article  PubMed  Google Scholar 

  113. Arsenovic, A., Ischebeck, A. & Zaretskaya, N. Dissociation between attention-dependent and spatially specific illusory shape responses within the topographic areas of the posterior parietal cortex. J. Neurosci. 42, 8125–8135 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Grassi, P. R., Zaretskaya, N. & Bartels, A. A generic mechanism for perceptual organization in the parietal cortex. J. Neurosci. 38, 7158–7169 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Riddoch, M. J. et al. A tale of two agnosias: distinctions between form and integrative agnosia. Cogn. Neuropsychol. 25, 56–92 (2008).

    Article  PubMed  Google Scholar 

  116. Romei, V., Driver, J., Schyns, P. G. & Thut, G. Rhythmic TMS over parietal cortex links distinct brain frequencies to global versus local visual processing. Curr. Biol. 21, 334–337 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Zaretskaya, N., Anstis, S. & Bartels, A. Parietal cortex mediates conscious perception of illusory gestalt. J. Neurosci. 33, 523–531 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Guo, C. et al. Adversarially trained neural representations are already as robust as biological neural representations. In Proc. Int. Conf. Machine Learning Vol. 162 (eds Chaudhuri, K. et al.) 8072–8081 (Proc. Machine Learning Research, 2022).

  119. Waidmann, E. N., Koyano, K. W., Hong, J. J., Russ, B. E. & Leopold, D. A. Local features drive identity responses in macaque anterior face patches. Nat. Commun. 13, 5592 (2022).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  120. Ayzenberg, V., Simmons, C. & Behrmann, M. Temporal asymmetries and interactions between dorsal and ventral visual pathways during object recognition. Cereb. Cortex Comm. 4, tgad003 (2022).

    Article  Google Scholar 

  121. Tarr, M. J. & Bülthoff, H. H. Image-based object recognition in man, monkey and machine. Cognition 67, 1–20 (1998).

    Article  CAS  PubMed  Google Scholar 

  122. Humphrey, G. K. & Jolicoeur, P. An examination of the effects of axis foreshortening, monocular depth cues, and visual field on object identification. Q. J. Exp. Psychol. 46, 137–159 (1993).

    Article  CAS  Google Scholar 

  123. Le Vay, S., Wiesel, T. N. & Hubel, D. H. The development of ocular dominance columns in normal and visually deprived monkeys. J. Comp. Neurol. 191, 1–51 (1980).

    Article  Google Scholar 

  124. Chino, Y. M., Smith, E. L. III, Hatta, S. & Cheng, H. Postnatal development of binocular disparity sensitivity in neurons of the primate visual cortex. J. Neurosci. 17, 296–307 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Slater, A., Mattock, A. & Brown, E. Size constancy at birth: newborn infants’ responses to retinal and real size. J. Exp. Child. Psychol. 49, 314–322 (1990).

    Article  CAS  PubMed  Google Scholar 

  126. Slater, A., Morison, V. & Rose, D. New‐born infants’ perception of similarities and differences between two‐and three‐dimensional stimuli. Br. J. Dev. Psychol. 2, 287–294 (1984).

    Article  Google Scholar 

  127. Jandó, G. et al. Early-onset binocularity in preterm infants reveals experience-dependent visual development in humans. Proc. Natl Acad. Sci. USA 109, 11049–11052 (2012).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  128. Fox, R., Aslin, R. N., Shea, S. L. & Dumais, S. T. Stereopsis in human infants. Science 207, 323–324 (1980).

    Article  CAS  PubMed  ADS  Google Scholar 

  129. Hirshkowitz, A. & Wilcox, T. Infants’ ability to extract three-dimensional shape from coherent motion. Infant. Behav. Dev. 36, 863–872 (2013).

    Article  PubMed  Google Scholar 

  130. Kellman, P. J. & Short, K. R. Development of three-dimensional form perception. J. Exp. Psychol. Hum. Percept. Perform. 13, 545 (1987).

    Article  CAS  PubMed  Google Scholar 

  131. Kellman, P. J. Perception of three-dimensional form by human infants. Percept. Psychophys. 36, 353–358 (1984).

    Article  CAS  PubMed  Google Scholar 

  132. Shuwairi, S. M., Albert, M. K. & Johnson, S. P. Discrimination of possible and impossible objects in infancy. Psychol. Sci. 18, 303–307 (2007).

    Article  PubMed  Google Scholar 

  133. Tsuruhara, A., Sawada, T., Kanazawa, S., Yamaguchi, M. K. & Yonas, A. Infant’s ability to form a common representation of an object’s shape from different pictorial depth cues: a transfer-across-cues study. Infant Behav. Dev. 32, 468–475 (2009).

    Article  PubMed  Google Scholar 

  134. Mash, C., Arterberry, M. E. & Bornstein, M. H. Mechanisms of visual object tecognition in infancy: five‐month‐olds generalize beyond the interpolation of familiar views. Infancy 12, 31–43 (2007).

    Article  PubMed  Google Scholar 

  135. Ruff, H. A. Infant recognition of the invariant form of objects. Child. Dev. 49, 293–306 (1978).

    Article  CAS  PubMed  Google Scholar 

  136. Kraebel, K. S. & Gerhardstein, P. C. Three-month-old infants’ object recognition across changes in viewpoint using an operant learning procedure. Infant Behav. Dev. 29, 11–23 (2006).

    Article  PubMed  Google Scholar 

  137. Georgieva, S., Peeters, R., Kolster, H., Todd, J. T. & Orban, G. A. The processing of three-dimensional shape from disparity in the human brain. J. Neurosci. 29, 727–742 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. Georgieva, S. S., Todd, J. T., Peeters, R. & Orban, G. A. The extraction of 3D shape from texture and shading in the human brain. Cereb. Cortex 18, 2416–2438 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Orban, G. A. The extraction of 3D shape in the visual system of human and nonhuman primates. Annu. Rev. Neurosci. 34, 361–388 (2011).

    Article  CAS  PubMed  Google Scholar 

  140. Yamane, Y., Carlson, E. T., Bowman, K. C., Wang, Z. & Connor, C. E. A neural code for three-dimensional object shape in macaque inferotemporal cortex. Nat. Neurosci. 11, 1352–1360 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Murphy, A. P., Leopold, D. A., Humphreys, G. W. & Welchman, A. E. Lesions to right posterior parietal cortex impair visual depth perception from disparity but not motion cues. Phil. Trans. R. Soc. B 371, 20150263 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  142. Tarr, M. J. & Bülthoff, H. H. Is human object recognition better described by geon structural descriptions or by multiple views? Comment on Biederman and Gerhardstein. J. Exp. Psychol. Hum. Percept. Perform. 21, 1494–1505 (1995).

    Article  CAS  PubMed  Google Scholar 

  143. Wood, J. N. Newborn chickens generate invariant object representations at the onset of visual object experience. Proc. Natl Acad. Sci. USA 110, 14000–14005 (2013).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  144. Wood, J. N. & Wood, S. M. W. One-shot learning of view-invariant object representations in newborn chicks. Cognition 199, 104192 (2020).

    Article  PubMed  Google Scholar 

  145. Kellman, P. J. & Shipley, T. F. A theory of visual interpolation in object perception. Cogn. Psychol. 23, 141–221 (1991).

    Article  CAS  PubMed  Google Scholar 

  146. Wood, J. N. & Wood, S. M. The development of invariant object recognition requires visual experience with temporally smooth objects. Cogn. Sci. 42, 1391–1406 (2018).

    Article  PubMed  Google Scholar 

  147. Ye, J. et al. Resilience of temporal processing to early and extended visual deprivation. Vis. Res. 186, 80–86 (2021).

    Article  PubMed  Google Scholar 

  148. Ben-Ami, S. et al. Human (but not animal) motion can be recognized at first sight — after treatment for congenital blindness. Neuropsychologia 174, 108307 (2022).

    Article  PubMed  Google Scholar 

  149. Bourne, J. A. & Rosa, M. G. Hierarchical development of the primate visual cortex, as revealed by neurofilament immunoreactivity: early maturation of the middle temporal area (MT). Cereb. Cortex 16, 405–414 (2006).

    Article  PubMed  Google Scholar 

  150. Ciesielski, K. T. et al. Maturational changes in human dorsal and ventral visual networks. Cereb. Cortex 29, 5131–5149 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  151. Distler, C., Bachevalier, J., Kennedy, C., Mishkin, M. & Ungerleider, L. Functional development of the corticocortical pathway for motion analysis in the macaque monkey: a 14C-2-deoxyglucose study. Cereb. Cortex 6, 184–195 (1996).

    Article  CAS  PubMed  Google Scholar 

  152. Biagi, L., Tosetti, M., Crespi, S. A. & Morrone, M. C. Development of BOLD response to motion in human infants. J. Neurosci. 43, 3825–3837 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Rosch, E. in Cognition and Categorization (eds Rosch, E. & Lloyd, B.) 27–48 (Erlbaum, 1978).

  154. Rosch, E., Mervis, C. B., Gray, W. D., Johnson, D. M. & Boyes-Braem, P. in Cognitive Psychology: Key Readings (eds Balota, D. A. & Marsh, E. J.) 448–471 (Psychology Press, 2004).

  155. Mareschal, D. & Quinn, P. C. Categorization in infancy. Trends Cogn. Sci. 5, 443–450 (2001).

    Article  PubMed  Google Scholar 

  156. Turati, C., Simion, F. & Zanon, L. Newborns’ perceptual categorization for closed and open geometric forms. Infancy 4, 309–325 (2003).

    Article  Google Scholar 

  157. Quinn, P. C., Slater, A. M., Brown, E. & Hayes, R. A. Developmental change in form categorization in early infancy. Br. J. Dev. Psychol. 19, 207–218 (2001).

    Article  Google Scholar 

  158. Bomba, P. C. & Siqueland, E. R. The nature and structure of infant form categories. J. Exp. Child. Psychol. 35, 294–328 (1983).

    Article  Google Scholar 

  159. Quinn, P. C., Eimas, P. D. & Rosenkrantz, S. L. Evidence for representations of perceptually similar natural categories by 3-month-old and 4-month-old infants. Perception 22, 463–475 (1993).

    Article  CAS  PubMed  Google Scholar 

  160. Quinn, P. C. & Johnson, M. H. Global-before-basic object categorization in connectionist networks and 2-month-old infants. Infancy 1, 31–46 (2000).

    Article  PubMed  Google Scholar 

  161. Mareschal, D., French, R. M. & Quinn, P. C. A connectionist account of asymmetric category learning in early infancy. Dev. Psychol. 36, 635–645 (2000).

    Article  PubMed  Google Scholar 

  162. Oakes, L. M. & Spalding, T. L. The role of exemplar distribution in infants’ differentiation of categories. Infant. Behav. Dev. 20, 457–475 (1997).

    Article  Google Scholar 

  163. Quinn, P. C. The categorical representation of visual pattern information by young infants. Cognition 27, 145–179 (1987).

    Article  CAS  PubMed  Google Scholar 

  164. Sorscher, B., Ganguli, S. & Sompolinsky, H. Neural representational geometry underlies few-shot concept learning. Proc. Natl Acad. Sci. USA 119, e2200800119 (2022).

    Article  MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  165. Feldman, J. The structure of perceptual categories. J. Math. Psychol. 41, 145–170 (1997).

    Article  MathSciNet  CAS  PubMed  Google Scholar 

  166. Feldman, J. & Singh, M. Bayesian estimation of the shape skeleton. Proc. Natl Acad. Sci. USA 103, 18014–18019 (2006).

    Article  MathSciNet  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  167. Landau, B., Smith, L. & Jones, S. Object perception and object naming in early development. Trends Cogn. Sci. 2, 19–24 (1998).

    Article  CAS  PubMed  Google Scholar 

  168. Smith, L. B., Jones, S. S. & Landau, B. Naming in young children: a dumb attentional mechanism? Cognition 60, 143–171 (1996).

    Article  CAS  PubMed  Google Scholar 

  169. Smith, L. B. Learning to recognize objects. Psychol. Sci. 14, 244–250 (2003).

    Article  PubMed  Google Scholar 

  170. Clerkin, E. M., Hart, E., Rehg, J. M., Yu, C. & Smith, L. B. Real-world visual statistics and infants’ first-learned object names. Phil. Trans. R. Soc. B 372, 20160055 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  171. Jayaraman, S., Fausey, C. M. & Smith, L. B. The faces in infant-perspective scenes change over the first year of life. PLoS One 10, e0123780 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  172. Jayaraman, S. & Smith, L. B. Faces in early visual environments are persistent not just frequent. Vis. Res. 157, 213–221 (2019).

    Article  PubMed  Google Scholar 

  173. Tartaglini, A. R., Vong, W. K. & Lake, B. M. A developmentally-inspired examination of shape versus texture bias in machines. Preprint at arXiv https://arxiv.org/abs/1811.12231 (2022).

  174. Huber, L. S., Geirhos, R. & Wichmann, F. A. A four-year-old can outperform ResNet-50: out-of-distribution robustness may not require large-scale experience. In 3rd Worksh. on Shared Visual Representations in Human and Machine Intelligence (SVRHM) (NeurIPS, 2021).

  175. Smith, L. B., Jayaraman, S., Clerkin, E. & Yu, C. The developing infant creates a curriculum for statistical learning. Trends Cogn. Sci. 22, 325–336 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  176. Slone, L. K., Smith, L. B. & Yu, C. Self-generated variability in object images predicts vocabulary growth. Dev. Sci. 22, e12816 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  177. James, K. H., Jones, S. S., Smith, L. B. & Swain, S. N. Young children’s self-generated object views and object recognition. J. Cogn. Dev. 15, 393–401 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  178. Perez, J. & Feigenson, L. Violations of expectation trigger infants to search for explanations. Cognition 218, 104942 (2022).

    Article  PubMed  Google Scholar 

  179. Stahl, A. E. & Feigenson, L. Observing the unexpected enhances infants’ learning and exploration. Science 348, 91–94 (2015).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  180. Lee, D., Gujarathi, P. & Wood, J. N. Controlled-rearing studies of newborn chicks and deep neural networks. In 3rd Worksh. on Shared Visual Representations in Human and Machine Intelligence (SVRHM) (NeurIPS, 2021).

  181. Orhan, E. A., Gupta, P. V. & Lake, B. M. Self-supervised learning through the eyes of a child. In Advances in Neural Information Processing Systems 116 (NeurIPS, 2021).

  182. Zhuang, C. et al. Unsupervised neural network models of the ventral visual stream. Proc. Natl Acad. Sci. USA 118, e2014196118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  183. Bambach, S., Crandall, D. J., Smith, L. B. & Yu, C. in Joint Int. Conf. on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) 290–295 (IEEE, 2017).

  184. Pak, D., Lee, D., Wood, S. M. & Wood, J. N. A newborn embodied Turing test for view-invariant object recognition. Preprint at arXiv https://arxiv.org/abs/2306.05582 (2023).

  185. Rajalingham, R. & DiCarlo, J. J. Reversible inactivation of different millimeter-scale regions of primate IT results in different patterns of core object recognition deficits. Neuron 102, 493–505. e495 (2019).

    Article  CAS  PubMed  Google Scholar 

  186. Dehaene, S. et al. How learning to read changes the cortical networks for vision and language. Science 330, 1359–1364 (2010).

    Article  CAS  PubMed  ADS  Google Scholar 

  187. Saygin, Z. M. et al. Connectivity precedes function in the development of the visual word form area. Nat. Neurosci. 19, 1250–1255 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  188. Arcaro, M. J., Schade, P. F., Vincent, J. L., Ponce, C. R. & Livingstone, M. S. Seeing faces is necessary for face-domain formation. Nat. Neurosci. 20, 1404–1412 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  189. Gauthier, I., Tarr, M. J., Anderson, A. W., Skudlarski, P. & Gore, J. C. Activation of the middle fusiform ‘face area’ increases with expertise in recognizing novel objects. Nat. Neurosci. 2, 568–573 (1999).

    Article  CAS  PubMed  Google Scholar 

  190. Srihasam, K., Vincent, J. L. & Livingstone, M. S. Novel domain formation reveals proto-architecture in inferotemporal cortex. Nat. Neurosci. 17, 1776–1783 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  191. Kosakowski, H. L. et al. Selective responses to faces, scenes, and bodies in the ventral visual pathway of infants. Curr. Biol. 32, 265–274.e5 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  192. Deen, B. et al. Organization of high-level visual cortex in human infants. Nat. Commun. 8, 13995 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  193. Powell, L. J., Deen, B. & Saxe, R. Using individual functional channels of interest to study cortical development with fNIRS. Dev. Sci. 21, e12595 (2018).

    Article  PubMed  Google Scholar 

  194. Yan, X. et al. When do visual category representations emerge in infants’ brains? Preprint at bioRxiv https://doi.org/10.1101/2023.05.11.539934 (2023).

  195. Germine, L. T., Duchaine, B. & Nakayama, K. Where cognitive development and aging meet: face learning ability peaks after age 30. Cognition 118, 201–210 (2011).

    Article  PubMed  Google Scholar 

  196. Cohen, M. A. et al. Representational similarity precedes category selectivity in the developing ventral visual pathway. NeuroImage 197, 565–574 (2019).

    Article  PubMed  Google Scholar 

  197. Xie, S. et al. Visual category representations in the infant brain. Curr. Biol. 32, 5422–5432.e5426 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  198. Kiat, J. E. et al. Linking patterns of infant eye movements to a neural network model of the ventral stream using representational similarity analysis. Dev. Sci. 25, e13155 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  199. Yamins, D. L. et al. Performance-optimized hierarchical models predict neural responses in higher visual cortex. Proc. Natl Acad. Sci. USA 111, 8619–8624 (2014).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  200. Gao, W. et al. Temporal and spatial evolution of brain network topology during the first two years of life. PLoS One 6, e25278 (2011).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  201. Gogtay, N. et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Natl Acad. Sci. USA 101, 8174–8179 (2004).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  202. Keunen, K., Counsell, S. J. & Benders, M. J. N. L. The emergence of functional architecture during early brain development. NeuroImage 160, 2–14 (2017).

    Article  PubMed  Google Scholar 

  203. Natu, V. S. et al. Infants’ cortex undergoes microstructural growth coupled with myelination during development. Commun. Biol. 4, 1191 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  204. Spriet, C., Abassi, E., Hochmann, J.-R. & Papeo, L. Visual object categorization in infancy. Proc. Natl Acad. Sci. USA 119, e2105866119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  205. Ayzenberg, V., Granovetter, M. C., Robert, S., Patterson, C. & Behrmann, M. Differential functional reorganization of ventral and dorsal visual pathways following childhood hemispherectomy. Dev. Cogn. Neurosci. 64, 101323 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  206. Kamps, F. S., Hendrix, C. L., Brennan, P. A. & Dilks, D. D. Connectivity at the origins of domain specificity in the cortical face and place networks. Proc. Natl Acad. Sci. USA 117, 6163–6169 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  207. Hasson, U., Levy, I., Behrmann, M., Hendler, T. & Malach, R. Eccentricity bias as an organizing principle for human high-order object areas. Neuron 34, 479–490 (2002).

    Article  CAS  PubMed  Google Scholar 

  208. Yetter, M. et al. Curvilinear features are important for animate/inanimate categorization in macaques. J. Vis. 21, 3 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  209. Yue, X., Robert, S. & Ungerleider, L. G. Curvature processing in human visual cortical areas. NeuroImage 222, 117295 (2020).

    Article  PubMed  Google Scholar 

  210. Ponce, C. R., Hartmann, T. S. & Livingstone, M. S. End-stopping predicts curvature tuning along the ventral stream. J. Neurosci. 37, 648–659 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  211. Cassia, V. M., Valenza, E., Simion, F. & Leo, I. Congruency as a nonspecific perceptual property contributing to newborns’ face preference. Child. Dev. 79, 807–820 (2008).

    Article  PubMed  Google Scholar 

  212. Cassia, V. M., Turati, C. & Simion, F. Can a nonspecific bias toward top-heavy patterns explain newborns’ face preference? Psychol. Sci. 15, 379–383 (2004).

    Article  PubMed  Google Scholar 

  213. Turati, C., Simion, F., Milani, I. & Umiltà, C. Newborns’ preference for faces: what is crucial? Dev. Psychol. 38, 875–882 (2002).

    Article  PubMed  Google Scholar 

  214. Johnson, M. H. Subcortical face processing. Nat. Rev. Neurosci. 6, 766–774 (2005).

    Article  CAS  PubMed  Google Scholar 

  215. Hafed, Z. M. & Chen, C.-Y. Sharper, stronger, faster upper visual field representation in primate superior colliculus. Curr. Biol. 26, 1647–1658 (2016).

    Article  CAS  PubMed  Google Scholar 

  216. Versace, E., Damini, S. & Stancher, G. Early preference for face-like stimuli in solitary species as revealed by tortoise hatchlings. Proc. Natl Acad. Sci. USA 117, 24047–24049 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  217. Johnson, M. H., Dziurawiec, S., Ellis, H. & Morton, J. Newborns’ preferential tracking of face-like stimuli and its subsequent decline. Cognition 40, 1–19 (1991).

    Article  CAS  PubMed  Google Scholar 

  218. Reid, V. M. et al. The human fetus preferentially engages with face-like visual stimuli. Curr. Biol. 27, 1825–1828.e1823 (2017).

    Article  CAS  PubMed  Google Scholar 

  219. Simion, F., Valenza, E., Umilta, C. & Barba, B. D. Preferential orienting to faces in newborns: a temporal–nasal asymmetry. J. Exp. Psychol. Hum. Percept. Perform. 24, 1399 (1998).

    Article  CAS  PubMed  Google Scholar 

  220. Arcaro, M. J. & Livingstone, M. S. On the relationship between maps and domains in inferotemporal cortex. Nat. Rev. Neurosci. 22, 573–583 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  221. Gomez, J., Barnett, M. & Grill-Spector, K. Extensive childhood experience with Pokémon suggests eccentricity drives organization of visual cortex. Nat. Hum. Behav. 3, 611–624 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  222. Xu, S., Zhang, Y., Zhen, Z. & Liu, J. The face module emerges from domain-general visual experience: a deprivation study on deep convolution neural network. Front. Comput. Neurosci. 15, 626259 (2020).

    Article  Google Scholar 

  223. Baek, S., Song, M., Jang, J., Kim, G. & Paik, S.-B. Face detection in untrained deep neural networks. Nat. Commun. 12, 7328 (2021).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  224. Hannagan, T., Agrawal, A., Cohen, L. & Dehaene, S. Emergence of a compositional neural code for written words: recycling of a convolutional neural network for reading. Proc. Natl Acad. Sci. USA 118, e2104779118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  225. Nordt, M. et al. Cortical recycling in high-level visual cortex during childhood development. Nat. Hum. Behav. 5, 1686–1697 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  226. Dehaene, S. & Cohen, L. Cultural recycling of cortical maps. Neuron 56, 384–398 (2007).

    Article  CAS  PubMed  Google Scholar 

  227. Behrmann, M. & Plaut, D. C. Hemispheric organization for visual object recognition: a theoretical account and empirical evidence. Perception 49, 373–404 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  228. Bakhtiari, S., Mineault, P., Lillicrap, T., Pack, C. & Richards, B. The functional specialization of visual cortex emerges from training parallel pathways with self-supervised predictive learning. Adv. Neural Inf. Process. Syst. 34, 25164–25178 (2021).

    Google Scholar 

  229. Zhu, M. & Gupta, S. To prune, or not to prune: exploring the efficacy of pruning for model compression. Preprint at arXiv https://arxiv.org/abs/1710.01878 (2017).

  230. Lu, H. & Erlikhman, G. Enhancement of representational sparsity in deep neural networks can improve generalization. J. Vis. 19, 209b (2019).

    Article  Google Scholar 

  231. Yuan, L., Xiang, V., Crandall, D. & Smith, L. Learning the generative principles of a symbol system from limited examples. Cognition 200, 104243 (2020).

    Article  PubMed  Google Scholar 

  232. Smith, L. B. & Slone, L. K. A developmental approach to machine learning? Front. Psychol. 8, 2124 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  233. Blauch, N. M., Behrmann, M. & Plaut, D. C. Computational insights into human perceptual expertise for familiar and unfamiliar face recognition. Cognition 208, 104341 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  234. Stojnić, G., Gandhi, K., Yasuda, S., Lake, B. M. & Dillon, M. R. Commonsense psychology in human infants and machines. Cognition 235, 105406 (2023).

    Article  PubMed  Google Scholar 

  235. Wichmann, F. A. et al. Methods and measurements to compare men against machines. Electron. Imaging 2017, 36–45 (2017).

    Article  Google Scholar 

  236. Yermolayeva, Y. & Rakison, D. H. Connectionist modeling of developmental changes in infancy: approaches, challenges, and contributions. Psychol. Bull. 140, 224–255 (2014).

    Article  PubMed  Google Scholar 

  237. Yates, T. S. et al. Neural event segmentation of continuous experience in human infants. Proc. Natl Acad. Sci. USA 119, e2200257119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  238. Yates, T. S., Ellis, C. T. & Turk-Browne, N. B. Emergence and organization of adult brain function throughout child development. NeuroImage 226, 117606 (2021).

    Article  PubMed  Google Scholar 

  239. Lerner, Y., Scherf, K. S., Katkov, M., Hasson, U. & Behrmann, M. Changes in cortical coherence supporting complex visual and social processing in adolescence. J. Cogn. Neurosci. 33, 2215–2230 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  240. Wilcox, T., Haslup, J. A. & Boas, D. A. Dissociation of processing of featural and spatiotemporal information in the infant cortex. NeuroImage 53, 1256–1263 (2010).

    Article  PubMed  Google Scholar 

  241. Bachevalier, J., Hagger, C. & Mishkin, M. in Alfred Benzon Symposium Vol. 31 Brain Work And Mental Activity (eds Lassen, N. A. et al.) 231–240 (Munksgaard, 1991).

  242. Arcaro, M. J. & Livingstone, M. S. A hierarchical, retinotopic proto-organization of the primate visual system at birth. eLife 6, e26196 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  243. Ellis, C. T. et al. Retinotopic organization of visual cortex in human infants. Neuron 109, 2616–2626.e2616 (2021).

    Article  CAS  PubMed  Google Scholar 

  244. Hubel, D. H. & Wiesel, T. N. Receptive fields of cells in striate cortex of very young, visually inexperienced kittens. J. Neurophysiol. 26, 994–1002 (1963).

    Article  CAS  PubMed  Google Scholar 

  245. Mohammed, C. P. D. & Khalil, R. Postnatal development of visual cortical function in the mammalian brain. Front. Syst. Neuro. 14, 29 (2020).

    Article  Google Scholar 

  246. Rodman, H. R., Scalaidhe, S. & Gross, C. G. Response properties of neurons in temporal cortical visual areas of infant monkeys. J. Neurophysiol. 70, 1115–1136 (1993).

    Article  CAS  PubMed  Google Scholar 

  247. Rodman, H. R. Development of inferior temporal cortex in the monkey. Cereb. Cortex 4, 484–498 (1994).

    Article  CAS  PubMed  Google Scholar 

  248. Kamps, F. S., Pincus, J. E., Radwan, S. F., Wahab, S. & Dilks, D. D. Late development of navigationally relevant motion processing in the occipital place area. Curr. Biol. 30, 544–550.e543 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  249. Grotheer, M. et al. Human white matter myelination rate slows down at birth. Preprint at bioRxiv https://doi.org/10.1101/2023.03.02.530800v1 (2023).

  250. Ahmad, Z., Behrmann, M., Patterson, C. & Freud, E. Unilateral resection of both cortical visual pathways in a pediatric patient alters action but not perception. Neuropsychologia 168, 108182 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  251. Grinter, E. J., Maybery, M. T. & Badcock, D. R. Vision in developmental disorders: is there a dorsal stream deficit? Brain Res. Bull. 82, 147–160 (2010).

    Article  PubMed  Google Scholar 

  252. Pitcher, D. & Ungerleider, L. G. Evidence for a third visual pathway specialized for social perception. Trends Cogn. Sci. 25, 100–110 (2021).

    Article  PubMed  Google Scholar 

  253. Weiner, K. S. & Gomez, J. Third visual pathway, anatomy, and cognition across species. Trends Cogn. Sci. 25, 548–549 (2021).

    Article  PubMed  Google Scholar 

  254. Braddick, O. & Atkinson, J. Development of human visual function. Vis. Res. 51, 1588–1609 (2011).

    Article  PubMed  Google Scholar 

  255. Dubowitz, L. M. S., De Vries, L., Mushin, J. & Arden, G. B. Visual function in the newborn infant: is it cortically mediated? Lancet 327, 1139–1141 (1986).

    Article  Google Scholar 

  256. Ma, Z., Tu, W. & Zhang, N. Increased wiring cost during development is driven by long-range cortical, but not subcortical connections. NeuroImage 225, 117463 (2021).

    Article  PubMed  Google Scholar 

  257. King, A. J., Schnupp, J. W. H., Carlile, S., Smith, A. L. & Thompson, I. D. The development of topographically-aligned maps of visual and auditory space in the superior colliculus. Prog. Brain Res. 112, 335–350 (1996).

    Article  CAS  PubMed  Google Scholar 

  258. O’Reilly, R. C., Russin, J. L., Zolfaghar, M. & Rohrlich, J. Deep predictive learning in neocortex and pulvinar. J. Cogn. Neurosci. 33, 1158–1196 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  259. Sewards, T. V. & Sewards, M. A. Innate visual object recognition in vertebrates: some proposed pathways and mechanisms. Comp. Biochem. Physiol. A 132, 861–891 (2002).

    Article  Google Scholar 

  260. Arcaro, M. J., Pinsk, M. A., Chen, J. & Kastner, S. Organizing principles of pulvino-cortical functional coupling in humans. Nat. Commun. 9, 5382 (2018).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  261. Arcaro, M. J., Pinsk, M. A. & Kastner, S. The anatomical and functional organization of the human visual pulvinar. J. Neurosci. 35, 9848–9871 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  262. Baizer, J. S., Desimone, R. & Ungerleider, L. G. Comparison of subcortical connections of inferior temporal and posterior parietal cortex in monkeys. Vis. Neuro. 10, 59–72 (1993).

    Article  CAS  Google Scholar 

  263. Gattass, R., Galkin, T. W., Desimone, R. & Ungerleider, L. G. Subcortical connections of area V4 in the macaque. J. Comp. Neurol. 522, 1941–1965 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  264. Ungerleider, L. G., Galkin, T. W., Desimone, R. & Gattass, R. Subcortical projections of area V2 in the macaque. J. Cogn. Neurosci. 26, 1220–1233 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  265. Webster, M. J., Bachevalier, J. & Ungerleider, L. G. Connections of inferior temporal areas TEO and TE with parietal and frontal cortex in macaque monkeys. Cereb. Cortex 4, 470–483 (1994).

    Article  CAS  PubMed  Google Scholar 

  266. Mercuri, E. et al. Basal ganglia damage and impaired visual function in the newborn infant. Arch. Dis. Child. Fet. Neonat. Edn 77, F111–F114 (1997).

    Article  CAS  Google Scholar 

  267. Blumberg, M. S. & Adolph, K. E. Protracted development of motor cortex constrains rich interpretations of infant cognition. Trends Cogn. Sci. https://doi.org/10.1016/j.tics.2022.12.014 (2023).

  268. Güçlü, U. & van Gerven, M. A. Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream. J. Neurosci. 35, 10005–10014 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  269. Conwell, C., Prince, J. S., Alvarez, G. A. & Konkle, T. What can 5.17 billion regression fits tell us about artificial models of the human visual system? In 3rd Worksh. on Shared Visual Representations in Human and Machine Intelligence (SVRHM) (NeurIPS, 2021).

  270. Baker, N., Lu, H., Erlikhman, G. & Kellman, P. J. Deep convolutional networks do not classify based on global object shape. PLoS Comp. Biol. 14, e1006613 (2018).

    Article  ADS  Google Scholar 

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Ayzenberg, V., Behrmann, M. Development of visual object recognition. Nat Rev Psychol 3, 73–90 (2024). https://doi.org/10.1038/s44159-023-00266-w

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