Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Hippocampal-neocortical functional reorganization underlies children's cognitive development

Nature Neuroscience volume 17, pages 1263–1269 (2014)Cite this article

Subjects

An Erratum to this article was published on 25 November 2015

This article has been updated

Abstract

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development—the transition from procedure-based to memory-based problem-solving strategies—are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7–9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Experimental design and behavioral results.
Figure 2: Longitudinal changes in hippocampal engagement during childhood.
Figure 3: Longitudinal changes in hippocampal-neocortical functional coupling in relation to individual improvements in children's retrieval fluency.
Figure 4: Longitudinal changes in hippocampal engagement during childhood and further development through adolescence into adulthood.
Figure 5: Interproblem multivoxel pattern stability in the hippocampus in children at time 1 (T1) and time 2 (T2), adolescents and adults.

Similar content being viewed by others

Change history

  • 04 June 2015

    In the version of this article initially published, the second set of hippocampal coordinates in the fourth Results section was given as (−26,−22,−1). The correct coordinates are (−26,−22,−16). The error has been corrected in the HTML and PDF versions of the article.

References

  1. Siegler, R.S. Emerging Minds: The Process of Change in Children's Thinking (Oxford University Press, New York, 1996).

  2. Butterworth, B. The Mathematical Brain (Macmillan, London, 1999).

  3. Geary, D.C. Children's Mathematical Development: Research and Practical Applications (Washington, D.C., American Psychological Association, 1994).

  4. Menon, V. Arithmetic in child and adult brain. in Handbook of Mathematical Cognition (eds. Cohen Kadosh, R. & Dowker, A.) (Oxford University Press, 10.1093/oxfordhb/9780199642342.013.041; published online July, 2014).

  5. Siegler, R.S., DeLoache, J.S. & Eisenberg, N.E. How Children Develop (Worth Publishers, New York, 2006).

  6. McClelland, J.L. & Siegler, R.S. (eds.) Mechanisms of Cognitive Development: Behavioral and Neural Perspectives (Lawrence Erlbaum Associates, 2001).

  7. Geary, D.C., Hoard, M.K., Byrd-Craven, J. & DeSoto, M.C. Strategy choices in simple and complex addition: Contributions of working memory and counting knowledge for children with mathematical disability. J. Exp. Child Psychol. 88, 121–151 (2004).

    Article  Google Scholar 

  8. Cho, S., Ryali, S., Geary, D.C. & Menon, V. How does a child solve 7 + 8? Decoding brain activity patterns associated with counting and retrieval strategies. Dev. Sci. 14, 989–1001 (2011).

    Article  Google Scholar 

  9. Geary, D.C. Cognitive predictors of achievement growth in mathematics: a 5-year longitudinal study. Dev. Psychol. 47, 1539–1552 (2011).

    Article  Google Scholar 

  10. Geary, D.C., Brown, S.C. & Samaranayake, V.A. Cognitive addition—a short longitudinal-study of strategy choice and speed-of-processing differences in normal and mathematically disabled-children. Dev. Psychol. 27, 787–797 (1991).

    Article  Google Scholar 

  11. Ansari, D. Effects of development and enculturation on number representation in the brain. Natl. Rev. Neurosci. 9, 278–291 (2008).

    Article  CAS  Google Scholar 

  12. Dehaene, S., Piazza, M., Pinel, P. & Cohen, L. Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487–506 (2003).

    Article  Google Scholar 

  13. Baddeley, A. Working memory: looking back and looking forward. Natl. Rev. Neurosci. 4, 829–839 (2003).

    Article  CAS  Google Scholar 

  14. Bunge, S.A., Dudukovic, N.M., Thomason, M.E., Vaidya, C.J. & Gabrieli, J.D. Immature frontal lobe contributions to cognitive control in children: evidence from fMRI. Neuron 33, 301–311 (2002).

    Article  CAS  Google Scholar 

  15. Cho, S. et al. Hippocampal-prefrontal engagement and dynamic causal interactions in the maturation of children's fact retrieval. J. Cogn. Neurosci. 24, 1849–1866 (2012).

    Article  Google Scholar 

  16. Supekar, K. et al. Neural predictors of individual differences in response to math tutoring in primary-grade school children. Proc. Natl. Acad. Sci. USA 110, 8230–8235 (2013).

    Article  CAS  Google Scholar 

  17. Eichenbaum, H. Hippocampus: cognitive processes and neural representations that underlie declarative memory. Neuron 44, 109–120 (2004).

    Article  CAS  Google Scholar 

  18. McClelland, J.L., McNaughton, B.L. & O'Reilly, R.C. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychol. Rev. 102, 419–457 (1995).

    Article  Google Scholar 

  19. Tse, D. et al. Schemas and memory consolidation. Science 316, 76–82 (2007).

    Article  CAS  Google Scholar 

  20. van Kesteren, M.T., Ruiter, D.J., Fernandez, G. & Henson, R.N. How schema and novelty augment memory formation. Trends Neurosci. 35, 211–219 (2012).

    Article  CAS  Google Scholar 

  21. Squire, L.R. & Zola-Morgan, S. The medial temporal lobe memory system. Science 253, 1380–1386 (1991).

    Article  CAS  Google Scholar 

  22. Xue, G. et al. Greater neural pattern similarity across repetitions is associated with better memory. Science 330, 97–101 (2010).

    Article  CAS  Google Scholar 

  23. Kriegeskorte, N. & Kievit, R.A. Representational geometry: integrating cognition, computation, and the brain. Trends Cogn. Sci. 17, 401–412 (2013).

    Article  Google Scholar 

  24. Wu, S.S. et al. Standardized assessment of strategy use and working memory in early mental arithmetic performance. Dev. Neuropsychol. 33, 365–393 (2008).

    Article  Google Scholar 

  25. Geary, D.C., Hoard, M.K. & Nugent, L. Independent contributions of the central executive, intelligence, and in-class attentive behavior to developmental change in the strategies used to solve addition problems. J. Exp. Child Psychol. 113, 49–65 (2012).

    Article  Google Scholar 

  26. Friston, K.J., Zarahn, E., Josephs, O., Henson, R.N.A. & Dale, A.M. Stochastic designs in event-related fMRI. Neuroimage 10, 607–619 (1999).

    Article  CAS  Google Scholar 

  27. Kriegeskorte, N., Mur, M. & Bandettini, P. Representational similarity analysis - connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 4 (2008).

    Article  Google Scholar 

  28. Friston, K.J. et al. Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 6, 218–229 (1997).

    Article  CAS  Google Scholar 

  29. Cantlon, J.F. et al. The neural development of an abstract concept of number. J. Cogn. Neurosci. 21, 2217–2229 (2009).

    Article  Google Scholar 

  30. Houde, O., Rossi, S., Lubin, A. & Joliot, M. Mapping numerical processing, reading, and executive functions in the developing brain: an fMRI meta-analysis of 52 studies including 842 children. Dev. Sci. 13, 876–885 (2010).

    Article  Google Scholar 

  31. Cohen, J.R. et al. Decoding developmental differences and individual variability in response inhibition through predictive analyses across individuals. Front. Hum. Neurosci. 4, 47 (2010).

    PubMed  PubMed Central  Google Scholar 

  32. Kriegeskorte, N., Goebel, R. & Bandettini, P. Information-based functional brain mapping. Proc. Natl. Acad. Sci. USA 103, 3863–3868 (2006).

    Article  CAS  Google Scholar 

  33. Rivera, S.M., Reiss, A.L., Eckert, M.A. & Menon, V. Developmental changes in mental arithmetic: evidence for increased functional specialization in the left inferior parietal cortex. Cereb. Cortex 15, 1779–1790 (2005).

    Article  CAS  Google Scholar 

  34. Rosenberg-Lee, M., Barth, M. & Menon, V. What difference does a year of schooling make? Maturation of brain response and connectivity between 2nd and 3rd grades during arithmetic problem solving. Neuroimage 57, 796–808 (2011).

    Article  Google Scholar 

  35. Deniz Can, D., Richards, T. & Kuhl, P.K. Early gray-matter and white-matter concentration in infancy predict later language skills: a whole brain voxel-based morphometry study. Brain Lang. 124, 34–44 (2013).

    Article  Google Scholar 

  36. Kuhl, P.K. Early language acquisition: Neural substrates and theoretical models. in The Cognitive Neurosciences (ed. Gazzaniga, M.S.) 837–854 (MIT Press, 2009).

  37. Geary, D.C. The problem size effect in mental addition: developmental and cross-national trends. Math. Cogn. 2, 63–93 (1996).

    Article  Google Scholar 

  38. Qin, S. et al. Dissecting medial temporal lobe contributions to item and associative memory formation. Neuroimage 46, 874–881 (2009).

    Article  Google Scholar 

  39. McClelland, J.L. Parallel Distributed Processing: Implications for Cognition and Development (Oxford University Press, 1989).

  40. Kumaran, D., Summerfield, J.J., Hassabis, D. & Maguire, E.A. Tracking the emergence of conceptual knowledge during human decision making. Neuron 63, 889–901 (2009).

    Article  CAS  Google Scholar 

  41. Friederici, A.D. The brain basis of language processing: from structure to function. Physiol. Rev. 91, 1357–1392 (2011).

    Article  Google Scholar 

  42. Casey, B.J., Tottenham, N., Liston, C. & Durston, S. Imaging the developing brain: what have we learned about cognitive development? Trends Cogn. Sci. 9, 104–110 (2005).

    Article  CAS  Google Scholar 

  43. Toga, A.W., Thompson, P.M. & Sowell, E.R. Mapping brain maturation. Trends Neurosci. 29, 148–159 (2006).

    Article  CAS  Google Scholar 

  44. Qin, S., Young, C.B., Supekar, K., Uddin, L.Q. & Menon, V. Immature integration and segregation of emotion-related brain circuitry in young children. Proc. Natl. Acad. Sci. USA 109, 7941–7946 (2012).

    Article  CAS  Google Scholar 

  45. Glover, G.H. & Law, C.S. Spiral-in/out BOLD fMRI for increased SNR and reduced susceptibility artifacts. Magn. Reson. Med. 46, 515–522 (2001).

    Article  CAS  Google Scholar 

  46. Nichols, T. & Hayasaka, S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat. Methods Med. Res. 12, 419–446 (2003).

    Article  Google Scholar 

  47. Sanchez, C.E., Richards, J.E. & Almli, C.R. Age-specific MRI templates for pediatric neuroimaging. Dev. Neuropsychol. 37, 379–399 (2012).

    Article  Google Scholar 

  48. Pruessner, J.C. et al. Volumetry of hippocampus and amygdala with high-resolution MRI and three-dimensional analysis software: minimizing the discrepancies between laboratories. Cereb. Cortex 10, 433–442 (2000).

    Article  CAS  Google Scholar 

  49. Duvernoy, H. The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI (Springer, Verlag Berlin Heidelberg, 2005).

Download references

Acknowledgements

This work was supported by grants from US National Institutes of Health (HD047520, HD059205 and MH101394), Child Health Research Institute at Stanford University, Lucile Packard Foundation for Children's Health and Stanford CTAS (UL1RR025744) and Netherlands Organization for Scientific Research (NWO446.10.010).

Author information

Authors and Affiliations

  1. Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, USA

    Shaozheng Qin, Soohyun Cho, Tianwen Chen, Miriam Rosenberg-Lee & Vinod Menon

  2. Department of Psychology, Chung-Ang University, Seoul, South Korea

    Soohyun Cho

  3. Department of Psychological Sciences, Interdisciplinary Neuroscience, University of Missouri, Columbia Missouri, USA.,

    David C Geary

  4. Department of Neurology and Neurological Sciences & Program of Neuroscience, Stanford University, Stanford, California, USA

    Vinod Menon

Authors
  1. Shaozheng Qin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Soohyun Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tianwen Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Miriam Rosenberg-Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David C Geary
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Vinod Menon
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.Q. and V.M. designed research; S.Q., S.C., T.C. and M.R.-L. performed research; S.Q. and T.C. analyzed data; S.Q., D.C.G. and V.M. wrote the paper.

Corresponding authors

Correspondence to Shaozheng Qin or Vinod Menon.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Longitudinal and cross-sectional changes in accuracy and RTs during addition problem solving.

(a) Accuracy in the block design fMRI task, (b) Accuracy in the event-related fMRI task, (c) RTs in the block design fMRI task, (d) RTs in the event-related fMRI task. Data are plotted separately for children at Time-1 and Time-2 (N = 28), adolescents (N = 20) and adults (N = 20). Error bars represent standard error (s.e.m.) of the mean. Notes: T1, time-1; T2-, time-2; Addition, addition problems; Control, control problems; sec, seconds; *, P < 0.05; **, P < 0.01; ***, P < 0.001.

Supplementary Figure 2 Brain areas activated during addition problem solving in children.

Surface rendering of brain regions in the left and right hemispheres showing a significant main effect of task (Addition vs. Control). Data were collapsed across Time-1 and Time-2 of the longitudinal fMRI sample. Hippocampus and prefrontal cortex areas are highlighted in panels (a), (b) and (c). These regions can be broadly classified into the following three functional systems: (1) a fronto-parietal network, including the dorsolateral prefrontal cortex (DLPFC), the inferior frontal gyrus (IFG) extending into the insula (a), and the inferior parietal sulcus (IPS), regions important for working memory and mathematical cognition; (2) an anterior and medial temporal lobe network, including the hippocampus and the anterior temporal lobe, regions critical for episodic and semantic memory; (3) a motor, basal ganglia and cerebellar network, including the supplemental motor area and primary motor cortex (PMC), the striatum and cerebellum, regions (see Table S2) important for learning procedures and sequencing operations. Significant clusters of activation are overlaid on a high-resolution anatomical template in MNI space. Notes: L, left; R, right.

Supplementary Figure 3 Longitudinal changes in task-related activation in the prefrontal cortex and the parietal cortex during addition problem solving.

(a-c) Bilateral dorsolateral prefrontal cortex (DLPFC), left superior parietal lobule (SPL), right parietal-occipital regions (i.e., angular gyrus, AG) that show significant decreases in task-related activation from Time-2 to Time-1. (d-f) Each line represents each individual’s developmental trajectories of the DLPFC, SPL, AG engagement over time. Bold green lines represent the mean across all individuals for Time-1 and Time-2 separately. Significant clusters of activation are overlaid on a high-resolution anatomical template in MNI space. Notes: L, left; R, right.

Supplementary Figure 4 Longitudinal changes in task-related hippocampal functional connectivity.

Right hippocampus seed region (red circle) used in task-dependent functional connectivity analysis using a psychophysiological interaction (PPI) approach1. Between Time-1 and Time 2, significant increases in the hippocampal functional connectivity were observed with (a) ventromedial prefrontal cortex (vmPFC), (b) left inferior frontal gyrus (IFG) and left anterior temporal lobe (ATL), and (c) right dorsolateral prefrontal cortex (DLPFC). Significant clusters of activation are overlaid on a high-resolution anatomical template in MNI space. (d-g) Individual trajectories representing longitudinal changes in connectivity strength were plotted for corresponding brain regions. Notes: L, left; R, Right; T1 & T2, two time points in the longitudinal fMRI in children.

Supplementary Figure 5 Developmental changes in task-related activation in the medial temporal lobe from childhood through adolescence into adulthood.

Coronal view of activation patterns in the medial temporal lobe during Addition (vs. Control) problem solving in children at Time-1 (a), Time-2 (b), adolescents (c) and adults (d). The most prominent activation of the medial temporal lobe was observed in children at Time-2, but not in children at Time-1, adolescents or adults. Details about other brain regions are listed in Table S2 and S6. Notes: Hipp, hippocampus; BG, basal ganglia; L, left; R, right.

Supplementary Figure 6 Correlation between task-related activation and addition task performance across children, adolescents and adults.

(a-c) Significant clusters in the left dorsolateral prefrontal cortex (DLPFC), the left middle temporal gyrus (MTG), and the right temporal pole (TP) show negative correlations with accuracy; (d) A significant cluster in the right motor cortex (MC) shows positive correlation with accuracy; (e) A significant cluster in the left superior parietal lobe (SPL) shows negative correlation with reaction times (RTs) – that is, a positive correlation with improved performance. (f) A significant cluster in the left insula shows positive correlations with RTs, or negative correlation with improved performance. (g-j) No reliable associations between hippocampal mean activation (extracted from the entire AAL hippocampal masks), accuracy and RTs were observed. The red box highlights null correlations between hippocampal activation and improvement in accuracy and RTs.

Supplementary Figure 7 Developmental changes in interproblem multivoxel pattern stability in frontal cortex and ventral-temporal cortex.

Significant clusters were derived from an omnibus F-contrast in children at Time-2, adolescents, and adults. Separate paired t-tests were conducted for longitudinal changes between Time-1 and Time-2 in children for each region. Separate ANOVAs were conducted to define cross-sectional changes from childhood through adolescence into adulthood, and post-hoc Scheffe’s procedures were used to control for multiple group comparisons. Notes: IFS, inferior frontal sulcus; IFG, inferior frontal gyrus; In, insula; PCG, postcentral gyrus; FG, fusiform gyrus; MTG, middle temporal gyrus. L, left; R, right.

Supplementary Figure 8 Interproblem multivoxel pattern stability analysis with comparable number of correctly solved problems across groups.

(a-b) Increases in inter-problem pattern stability for those problems correctly solved in the anatomically-defined left and right hippocampus in adolescents and adults compared to children at Time-1 (T1) or Time-2 (T2). Mean and standard deviation of the number of correctly solved problems was matched across groups (see Table S10). (c-d) Results of whole-brain analysis showing significant increases in pattern stability in the bilateral hippocampus in childhood compared to adolescence and adulthood. Notes: * P < 0.05; **, P < 0.01; m.s., marginally significant (P value, 0.08; two-tailed); L, left; R, right.

Supplementary Figure 9 Task-related activation in the hippocampus using AAL masks versus manually drawn ROIs (based on a pediatric brain template).

Pediatric brain template images are derived from twelve 8.5 year-old children2 and adult automated anatomical labelling (AAL) masks of the hippocampus. Left panel: Results using hippocampal AAL masks are reported in the main text. Right panel: Results from hand-drawn hippocampal ROIs (see online Methods for details). Notes: * P < 0.05; **, P < 0.01; L, left; R, right.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9, Supplementary Results and Supplementary Tables 1–9 (PDF 6802 kb)

Supplementary Methods Checklist (PDF 183 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qin, S., Cho, S., Chen, T. et al. Hippocampal-neocortical functional reorganization underlies children's cognitive development. Nat Neurosci 17, 1263–1269 (2014). https://doi.org/10.1038/nn.3788

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3788

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing