Abstract
Human ventral temporal cortex contains category-selective regions that respond preferentially to ecologically relevant categories such as faces, bodies, places and words and that are causally involved in the perception of these categories. How do these regions develop during childhood? We used functional magnetic resonance imaging to measure longitudinal development of category selectivity in school-age children over 1 to 5 years. We discovered that, from young childhood to the teens, face- and word-selective regions in ventral temporal cortex expand and become more category selective, but limb-selective regions shrink and lose their preference for limbs. Critically, as a child develops, increases in face and word selectivity are directly linked to decreases in limb selectivity, revealing that during childhood, limb selectivity in ventral temporal cortex is repurposed into word and face selectivity. These data provide evidence for cortical recycling during childhood development. This has important implications for understanding typical as well as atypical brain development and necessitates a rethinking of how cortical function develops during childhood.
Similar content being viewed by others
Data availability
The data required to generate the main figures are available in the GitHub repository (https://github.com/VPNL/corticalRecycling). Due to the large size of the raw data, it will be made available from the corresponding author upon request.
Code availability
Code is available at https://github.com/VPNL/corticalRecycling.
References
Kanwisher, N., McDermott, J. & Chun, M. M. The fusiform face area: a module in human extrastriate cortex specialized for face perception. J. Neurosci. 17, 4302–4311 (1997).
Peelen, M. V. & Downing, P. E. Selectivity for the human body in the fusiform gyrus. J. Neurophysiol. 93, 603–608 (2005).
Epstein, R. & Kanwisher, N. A cortical representation of the local visual environment. Nature 392, 598–601 (1998).
Cohen, L. et al. The visual word form area. Spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients. Brain 123, 291–307 (2000).
Deen, B. et al. Organization of high-level visual cortex in human infants. Nat. Commun. 8, 13995 (2017).
de Heering, A. & Rossion, B. Rapid categorization of natural face images in the infant right hemisphere. eLife 4, e06564 (2015).
Livingstone, M. S. et al. Development of the macaque face-patch system. Nat. Commun. 8, 14897 (2017).
Golarai, G. et al. Differential development of high-level visual cortex correlates with category-specific recognition memory. Nat. Neurosci. 10, 512–522 (2007).
Dehaene-Lambertz, G., Monzalvo, K. & Dehaene, S. The emergence of the visual word form: longitudinal evolution of category-specific ventral visual areas during reading acquisition. PLoS Biol. 16, 1–34 (2018).
Srihasam, K., Vincent, J. L. & Livingstone, M. S. Novel domain formation reveals proto-architecture in inferotemporal cortex. Nat. Neurosci. 17, 1776–1783 (2014).
Gomez, J., Natu, V., Jeska, B., Barnett, M. & Grill-Spector, K. Development differentially sculpts receptive fields across early and high-level human visual cortex. Nat. Commun. 9, 788 (2018).
Nordt, M. et al. Learning to read increases the informativeness of distributed ventral temporal responses. Cereb. Cortex https://doi.org/10.1093/cercor/bhy178 (2019).
Behrmann, M. & Plaut, D. C. A vision of graded hemispheric specialization. Ann. N. Y. Acad. Sci. 1359, 30–46 (2015).
Dehaene, S., Cohen, L., Morais, J. & Kolinsky, R. Illiterate to literate: behavioural and cerebral changes induced by reading acquisition. Nat. Rev. Neurosci. 16, 234–244 (2015).
Levy, I., Hasson, U., Avidan, G., Hendler, T. & Malach, R. Center–periphery organization of human object areas. Nat. Neurosci. 4, 533–539 (2001).
Cantlon, J. F., Pinel, P., Dehaene, S. & Pelphrey, K. A. Cortical representations of symbols, objects, and faces are pruned back during early childhood. Cereb. Cortex 21, 191–199 (2011).
Dehaene, S. et al. How learning to read changes cortical networks for vision and language. Science 1359, 1359–1364 (2010).
Frost, M. A. & Goebel, R. Measuring structural-functional correspondence: spatial variability of specialised brain regions after macro-anatomical alignment. Neuroimage 59, 1369–1381 (2012).
Weiner, K. S. et al. The mid-fusiform sulcus: a landmark identifying both cytoarchitectonic and functional divisions of human ventral temporal cortex. Neuroimage 84, 453–465 (2014).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–3300 (1995).
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, F15–30 (2007).
Peelen, M. V., Glaser, B., Vuilleumier, P. & Eliez, S. Differential development of selectivity for faces and bodies in the fusiform gyrus. Dev. Sci. 12, 16–25 (2009).
Golarai, G., Liberman, A., Yoon, J. M. & Grill-Spector, K. Differential development of the ventral visual cortex extends through adolescence. Front. Hum. Neurosci. 3, 80 (2010).
Kobatake, E., Wang, G. & Tanaka, K. Effects of shape-discrimination training on the selectivity of inferotemporal cells in adult monkeys. J. Neurophysiol. 80, 324–330 (1998).
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).
Fausey, C. M., Jayaraman, S. & Smith, L. B. From faces to hands: changing visual input in the first two years. Cognition 152, 101–107 (2016).
Frank, M. C., Vul, E. & Saxe, R. Measuring the development of social attention using free-viewing. Infancy 17, 355–375 (2012).
Long, B., Kachergis, G., Agrawal, K., & Frank, M. C. Detecting social information in a dense database of infants’ natural visual experience. Preprint at PsyArXiv https://doi.org/10.31234/osf.io/z7tdg (2020).
Liszkowski, U., Carpenter, M. & Tomasello, M. Pointing out new news, old news, and absent referents at 12 months of age. Dev. Sci. 10, F1–F7 (2007).
Haber, N., Mrowca, D., Wang, S., Fei-Fei, L. & Yamins, D. L. K. Learning to play with intrinsically-motivated, self-aware agents. Adv. Neural Inf. Process. Syst. 31, 8388–8399 (2018).
Khaligh-Razavi, S. M. & Kriegeskorte, N. Deep supervised, but not unsupervised, models may explain IT cortical representation. PLoS Comput. Biol. 10, e1003915 (2014).
Zhuang, C.; Zhai, A. L.; Yamins, D. in Proceedings of the IEEE/CVF International Conference on Computer Vision (2019).
Gomez, J. et al. Microstructural proliferation in human cortex is coupled with the development of face processing. Science 355, 68–71 (2017).
Natu, V. S. et al. Development of neural sensitivity to face identity correlates with perceptual discriminability. J. Neurosci. 36, 10893–10907 (2016).
Wandell, B. A., Rauschecker, A. M. & Yeatman, J. D. Learning to see words. Annu. Rev. Psychol. 63, 31–53 (2012).
Ben-Shachar, M., Dougherty, R. F., Deutsch, G. K. & Wandell, B. A. The development of cortical sensitivity to visual word forms. J. Cogn. Neurosci. 23, 2387–2399 (2011).
Feldstein Ewing, S. W., Bjork, J. M. & Luciana, M. Implications of the ABCD study for developmental neuroscience. Dev. Cogn. Neurosci. 32, 161–164 (2018).
Constantino, J. N. et al. Infant viewing of social scenes is under genetic control and is atypical in autism. Nature 547, 340–344 (2017).
Duchaine, B. C. & Nakayama, K. Developmental prosopagnosia: a window to content-specific face processing. Curr. Opin. Neurobiol. 16, 166–173 (2006).
Amedi, A., Raz, N., Pianka, P., Malach, R. & Zohary, E. Early ‘visual’ cortex activation correlates with superior verbal memory performance in the blind. Nat. Neurosci. 6, 758–766 (2003).
Liu, T. T. et al. Successful reorganization of category-selective visual cortex following occipito-temporal lobectomy in childhood. Cell Rep. 24, 1113–1122.e6 (2018).
Norton, E. S., Beach, S. D. & Gabrieli, J. D. E. Neurobiology of dyslexia. Curr. Opin. Neurobiol. 30, 73–78 (2015).
Srihasam, K., Mandeville, J. B., Morocz, I. A., Sullivan, K. J. & Livingstone, M. S. Behavioral and anatomical consequences of early versus late symbol training in macaques. Neuron 73, 608–619 (2012).
Büchel, C., Price, C. & Friston, K. A multimodal language region in the ventral visual pathway. Nature 394, 274–277 (1998).
Emmorey, K., McCullough, S. & Weisberg, J. Neural correlates of fingerspelling, text, and sign processing in deaf American sign language–English bilinguals. Lang. Cogn. Neurosci. 30, 749–767 (2015).
Bi, Y., Wang, X. & Caramazza, A. Object domain and modality in the ventral visual pathway. Trends Cogn. Sci. 20, 282–290 (2016).
Reich, L., Szwed, M., Cohen, L. & Amedi, A. A ventral visual stream reading center independent of visual experience. Curr. Biol. 21, 363–368 (2011).
Dehaene, S. & Cohen, L. Cultural recycling of cortical maps. Neuron 56, 384–398 (2007).
Lucas, T. H., McKhann, G. M. & Ojemann, G. A. Functional separation of languages in the bilingual brain: a comparison of electrical stimulation language mapping in 25 bilingual patients and 117 monolingual control patients. J. Neurosurg. 101, 449–457 (2004).
Green, D. W., Crinion, J. & Price, C. J. Convergence, degeneracy, and control. Lang. Learn. 56, 99–125 (2006).
Amalric, M. & Dehaene, S. Origins of the brain networks for advanced mathematics in expert mathematicians. Proc. Natl Acad. Sci. USA 113, 4909–4917 (2016).
Kersey, A. J. & Cantlon, J. F. Neural tuning to numerosity relates to perceptual tuning in 3–6-year-old children. J. Neurosci. 37, 512–522 (2017).
Pica, P., Lemer, C., Izard, V. & Dehaene, S. Exact and approximate arithmetic in an Amazonian indigene group. Science 306, 499–503 (2004).
Natu, V. S. et al. Apparent thinning of human visual cortex during childhood is associated with myelination. Proc. Natl Acad. Sci. USA 116, 20750–20759 (2019).
Mezer, A. et al. Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging. Nat. Med. 19, 1667–1672 (2013).
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).
Weiner, K. S. & Grill-Spector, K. Sparsely-distributed organization of face and limb activations in human ventral temporal cortex. Neuroimage 52, 1559–1573 (2010).
Weiner, K. S., Sayres, R., Vinberg, J. & Grill-Spector, K. fMRI-adaptation and category selectivity in human ventral temporal cortex: regional differences across time scales. J. Neurophysiol. 103, 3349–3365 (2010).
Stigliani, A., Weiner, K. S. & Grill-Spector, K. Temporal processing capacity in high-level visual cortex is domain specific. J. Neurosci. 35, 12412–12424 (2015).
Kanwisher, N. Domain specificity in face perception. Nat. Neurosci. 3, 759–763 (2000).
Reuter, M., Schmansky, N. J., Rosas, H. D. & Fischl, B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage 61, 1402–1418 (2012).
Haxby, J. V. et al. Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science 293, 2425–2430 (2001).
Glasser, M. F. et al. A multi-modal parcellation of human cerebral cortex. Nature 536, 171–178 (2016).
Acknowledgements
The authors thank L. Villalobos, E. Y. Hwang, S. Huskins, A. Fitisemanu, and P. Eykamp for manually editing grey–white matter brain segmentations, B. Jeska, M. Barnett, C. Estrada and N. Lopez-Alvarez for help with data collection, R. Hinds for help with data entry and management. Funding was provided by a fellowship from the German National Academic Foundation NO 1448/1-1 (M.N.), NIH grant 2RO1 EY 022318 (K.G.-S.), NIH training grant 5T32EY020485 (V.S.N.), NSF Graduate Research Development Program DGE-114747 (J.G.) and Ruth L. Kirschstein National Research Service Award F31EY027201 (J.G.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Author information
Authors and Affiliations
Contributions
M.N. collected data, developed and coded the analysis pipeline, analysed the data and wrote the manuscript. V.S.N. and J.G. designed the experiment, collected data and contributed to the manuscript. A.A.R. collected the data, contributed to data analysis and contributed to the manuscript. D.F. and H.K. collected the data and contributed to the manuscript. K.G.-S. designed the experiment, contributed to the analysis pipeline and data analyses and wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Peer review information Nature Human Behaviour thanks Marius Peelen and Frank Tong for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Control analyses examining developmental increases and decreases in category-selective activation in lateral VTC.
LMM slopes indicating change in category-selective activation volume per month (n = 128 sessions, 29 children). Error bars: 95% CI. If the CI does not cross the y = 0 line, this indicates that the slope is significantly different than 0 (before FDR-correction). (a) Slopes for the age predictor for models in which adult faces, child faces, limbs, and words are excluded as control categories from the contrast. No effects survive FDR-correction. (b) Slopes for the age predictor for models including both age and time series signal-to-noise ratio (tSNR) as predictors. Significant development after FDR-correction (p < 0.05) is indicated by asterisks. (c) Slopes for the main analysis (filled bars), the contrast control (open bars with gray outline) and the tSNR control (open bars with red outline) are overlaid to illustrate the changes in effect size across the different analyses. Full statistics in Supplementary Tables 3-4,6-7. Related to Fig. 1.
Extended Data Fig. 2 Control analyses examining functional changes underlying the development of category-selective ROIs.
Left panel: Colored bars: Slopes of LMMs indicating changes in selectivity by age for all 10 categories in emerging and waning ROIs. Open bars with gray outline: LMM slopes for contrasts in which adult faces, child faces, limbs, and words are excluded as control categories in contrasts. Error bars: 95% CI. If the CI does not cross the y = 0 line, this indicates that the slope is significantly different than 0 (before FDR-correction). Asterisks: significant development after FDR-correction (p < 0.05) for colored bars, circles: significant after FDR-correction for open bars. Right panel: Response amplitudes for 5–9-year-olds and 13–17-year-olds. Lighter colors indicate younger ages. One functional session per child is included per boxplot. Boxplots show the 75% and 25% percentiles (colored areas) and median (horizontal lines). Whiskers extend to the most extreme data points not considered outliers (minimum, maximum). Crosses: outliers (values more than 1.5 times the interquartile range away from the bottom or top of the box). Black diamonds: LMM prediction for the response at the mean age of each age group. (a) Left emerging pOTS-words. Left panel: n = 24 (112 sessions). (b) Left waning OTS-limbs. n = 26, 122 sessions. (c) Left emerging pFus-faces. n = 22, 105 sessions. (d) Right waning OTS-limbs. n = 21, 100 sessions. (e) Right emerging pFus-faces. n = 21, 96 sessions. Full statistics in Supplementary Tables 9-10. As we observed a significant decrease in limb-selectivity in emerging parts of word- and face-selective regions and word-, face- and limb-selective regions neighbor, we tested if emerging parts of word- and face-selective regions overlap with waning parts of the limb-selective regions. However, the overlap between the developing parts of the ROIs (difference between initial and end ROIs) assessed by the dice coefficient (DC) was small (overlap between developing parts of OTS-limbs and pFus-faces, left: DC = 0.025 ± 0.01 (mean ± SD), n = 22; right: DC = 0.026 ± 0.01, n = 18; overlap between developing parts of left OTS-limbs and pOTS-words: DC = 0.006±SD = 0.004, n = 21). Related to Fig. 3.
Extended Data Fig. 3 Developmental changes in word-, face-, and limb-selectivity are also linked in the right hemisphere.
(a) Limb-selectivity vs face- and word-selectivity in the waning right OTS-limbs. (b) Face-selectivity vs. limb- and word-selectivity in the emerging right pFus faces. Left: Model prediction for 5–9-year-olds and 13–17-year-olds for the selectivity that defines the ROI as a function of the selectivity to the other two variables. Middle: Individual participant data visualized in 3D. In each panel the variable on the z-axis is related to the x- and y-variables. LMM βs, 95%-CIs, t-values, df, and p-values are shown on top. Full statistics are reported in Supplementary Table 11. Orange arrows: Individual child data. Blue arrows: LMM, same as left panel. Right: Rotated version of the plots in the middle column to increase visibility of changes along the horizontal axes. Related to Fig. 4.
Extended Data Fig. 4 Pairwise preferences of the ROI-defining category in the right hemisphere.
In each plot we show the pairwise preference of the ROI-defining category vs. each of the other two developing categories as a function of age. Thin lines: individual participant data showing the pairwise preference from the initial to end session. Gray line: LMM prediction of pairwise preference based on data from all sessions. Shaded gray: 95%-CI. LMM results (intercept: βintercept and slope: βage (rate of change in preference, t/month) and their significance are reported under each panel. (a) Waning right OTS-limbs (n = 21 participants, n = 100 sessions). Left: Limbs vs faces. Right: Limbs vs words. (b) Emerging right pFus-faces (n = 21 participants, n = 96 sessions). Left: Faces vs limbs. Right: Faces vs words. Related to Fig. 5. Statistics in Supplementary Table 15.
Supplementary information
Supplementary information
Supplementary Figs. 1–13 and Supplementary Tables 1–15.
Rights and permissions
About this article
Cite this article
Nordt, M., Gomez, J., Natu, V.S. et al. Cortical recycling in high-level visual cortex during childhood development. Nat Hum Behav 5, 1686–1697 (2021). https://doi.org/10.1038/s41562-021-01141-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41562-021-01141-5
- Springer Nature Limited
This article is cited by
-
Selective activations and functional connectivities to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus
Brain Structure and Function (2024)
-
Longitudinal development of category representations in ventral temporal cortex predicts word and face recognition
Nature Communications (2023)
-
Free viewing biases for complex scenes in preschoolers and adults
Scientific Reports (2023)
-
Development of visual object recognition
Nature Reviews Psychology (2023)
-
Is human face recognition lateralized to the right hemisphere due to neural competition with left-lateralized visual word recognition? A critical review
Brain Structure and Function (2022)