Hippocampal-neocortical functional reorganization underlies children's cognitive development

Journal name:
Nature Neuroscience
Volume:
17,
Pages:
1263–1269
Year published:
DOI:
doi:10.1038/nn.3788
Received
Accepted
Published online
Corrected online

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.

At a glance

Figures

  1. Experimental design and behavioral results.
    Figure 1: Experimental design and behavioral results.

    (a) Outline of the longitudinal fMRI study: 28 young children participated twice, first at time 1 (T1) and then 1.2 years later at time 2 (T2). Each child performed two arithmetic problem-solving tasks involving single-digit addition. The first task involved verbal production of the answer, during which problem-solving strategies were assessed, on a trial-by-trial basis (Online Methods), outside the scanner. Based on the child's self-report and experimenter observations, the use of strategies for solving each problem was classified into counting or retrieval or other. The second task involved verification of whether an answer presented with an arithmetic problem was correct or not and was performed during fMRI scanning. The control task involved 'n + 1' problems that are generally solved using a classic rule-based strategy with minimal changes in strategy with development. (b) Outline of the cross-sectional fMRI study: the same strategy assessment and fMRI tasks were performed by an additional group of 20 adolescents and 20 adults. (c) Developmental changes in the mix of strategies used for solving arithmetic problems, showing a gradual increase in memory-based retrieval and decrease in use of counting strategies. Solid lines represent data at T1 and T2 in children, and dotted lines represent data from adolescents and adults. (d) Developmental changes in task performance during fMRI from childhood (n = 28) through adolescence (n = 20) into adulthood (n = 20). *P < 0.05; **P < 0.01; ***P < 0.001. Error bars, s.e.m.

  2. Longitudinal changes in hippocampal engagement during childhood.
    Figure 2: Longitudinal changes in hippocampal engagement during childhood.

    (a) Left and right hippocampus clusters which showed increased engagement during addition problem solving between time 1 (T1) and time 2 (T2). Color bar represents T values. (b) Each line represents individual developmental trajectories of hippocampal engagement over time. Bold red lines represent group means at T1 and T2. (c) Sagittal view of an anatomically defined ROI encompassing the entire right hippocampus (in red) and significant functional clusters from a (in hot orange). (d) Each line represents individual trajectories of hippocampal engagement over time within anatomically defined ROIs. *P < 0.05; **P < 0.01. Error bars, s.e.m. L, left; R, right.

  3. Longitudinal changes in hippocampal-neocortical functional coupling in relation to individual improvements in children's retrieval fluency.
    Figure 3: Longitudinal changes in hippocampal-neocortical functional coupling in relation to individual improvements in children's retrieval fluency.

    (a) Right hippocampus seed region used in task-related functional connectivity (i.e., psychophysiological interaction) analysis. (b,c) Left and right DLPFC, and the left intraparietal sulcus (IPS) regions that showed increased functional connectivity with the hippocampus, as a function of longitudinal improvements in retrieval fluency from time 1 (T1) to time 2 (T2). (df) Longitudinal changes in retrieval fluency versus in functional connectivity strength from T1 to T2. Dashed lines indicate 95% confidence intervals, and solid line indicates the best linear fit. The correlates are plotted for visualization purposes only. L, left; R, right.

  4. Longitudinal changes in hippocampal engagement during childhood and further development through adolescence into adulthood.
    Figure 4: Longitudinal changes in hippocampal engagement during childhood and further development through adolescence into adulthood.

    (a) Right hippocampus showing main effect of group across children (n = 28), adolescents (n = 20) and adults (n = 20) (omnibus F contrast). (b) Developmental changes in the functionally defined hippocampus cluster. T1, time 1; T2, time 2. (c) Developmental changes in the engagement of anatomically defined hippocampal ROIs (ROI mask is shown in Fig. 2c). *P < 0.05; **P < 0.01; ***P < 0.001. Error bars, s.e.m. L, left; R, right.

  5. Interproblem multivoxel pattern stability in the hippocampus in children at time 1 (T1) and time 2 (T2), adolescents and adults.
    Figure 5: Interproblem multivoxel pattern stability in the hippocampus in children at time 1 (T1) and time 2 (T2), adolescents and adults.

    (a) Event-related fMRI design of arithmetic problem-solving task. (b) Sagittal slice of predefined region of interest (ROI) in the hippocampus used for the inter-problem pattern stability analysis. (c) 26 × 26 correlation matrix representing trial-by-trial brain activation pattern stability in the hippocampus during addition problem solving. Color bar represents omnibus F values. (d,e) Results of whole-brain analysis showing hippocampal regions that showed significant increases in interproblem multivoxel pattern stability from childhood through adolescence into adulthood. (f,g) Interproblem pattern stability in the left and right hippocampus for problems correctly solved by children at T1 and T2, adolescents and adults. Note that only correctly performed trials (problems) from each participant's event-related fMRI data were used in the analysis. a.u., arbitrary units; L, left; R, right. *P < 0.05; **P < 0.01. Error bars, s.e.m.

  6. Longitudinal and cross-sectional changes in accuracy and RTs during addition problem solving.
    Supplementary Fig. 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.

  7. Brain areas activated during addition problem solving in children.
    Supplementary Fig. 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.

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

  9. Longitudinal changes in task-related hippocampal functional connectivity.
    Supplementary Fig. 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.

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

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

  12. Developmental changes in interproblem multivoxel pattern stability in frontal cortex and ventral-temporal cortex.
    Supplementary Fig. 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.

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

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

Change history

Corrected online 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, doi: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, 121151 (2004).
  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, 9891001 (2011).
  9. Geary, D.C. Cognitive predictors of achievement growth in mathematics: a 5-year longitudinal study. Dev. Psychol. 47, 15391552 (2011).
  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, 787797 (1991).
  11. Ansari, D. Effects of development and enculturation on number representation in the brain. Natl. Rev. Neurosci. 9, 278291 (2008).
  12. Dehaene, S., Piazza, M., Pinel, P. & Cohen, L. Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487506 (2003).
  13. Baddeley, A. Working memory: looking back and looking forward. Natl. Rev. Neurosci. 4, 829839 (2003).
  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, 301311 (2002).
  15. Cho, S. et al. Hippocampal-prefrontal engagement and dynamic causal interactions in the maturation of children's fact retrieval. J. Cogn. Neurosci. 24, 18491866 (2012).
  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, 82308235 (2013).
  17. Eichenbaum, H. Hippocampus: cognitive processes and neural representations that underlie declarative memory. Neuron 44, 109120 (2004).
  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, 419457 (1995).
  19. Tse, D. et al. Schemas and memory consolidation. Science 316, 7682 (2007).
  20. van Kesteren, M.T., Ruiter, D.J., Fernandez, G. & Henson, R.N. How schema and novelty augment memory formation. Trends Neurosci. 35, 211219 (2012).
  21. Squire, L.R. & Zola-Morgan, S. The medial temporal lobe memory system. Science 253, 13801386 (1991).
  22. Xue, G. et al. Greater neural pattern similarity across repetitions is associated with better memory. Science 330, 97101 (2010).
  23. Kriegeskorte, N. & Kievit, R.A. Representational geometry: integrating cognition, computation, and the brain. Trends Cogn. Sci. 17, 401412 (2013).
  24. Wu, S.S. et al. Standardized assessment of strategy use and working memory in early mental arithmetic performance. Dev. Neuropsychol. 33, 365393 (2008).
  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, 4965 (2012).
  26. Friston, K.J., Zarahn, E., Josephs, O., Henson, R.N.A. & Dale, A.M. Stochastic designs in event-related fMRI. Neuroimage 10, 607619 (1999).
  27. Kriegeskorte, N., Mur, M. & Bandettini, P. Representational similarity analysis - connecting the branches of systems neuroscience. Front. Syst. Neurosci. 2, 4 (2008).
  28. Friston, K.J. et al. Psychophysiological and modulatory interactions in neuroimaging. Neuroimage 6, 218229 (1997).
  29. Cantlon, J.F. et al. The neural development of an abstract concept of number. J. Cogn. Neurosci. 21, 22172229 (2009).
  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, 876885 (2010).
  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).
  32. Kriegeskorte, N., Goebel, R. & Bandettini, P. Information-based functional brain mapping. Proc. Natl. Acad. Sci. USA 103, 38633868 (2006).
  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, 17791790 (2005).
  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, 796808 (2011).
  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, 3444 (2013).
  36. Kuhl, P.K. Early language acquisition: Neural substrates and theoretical models. in The Cognitive Neurosciences (ed. Gazzaniga, M.S.) 837854 (MIT Press, 2009).
  37. Geary, D.C. The problem size effect in mental addition: developmental and cross-national trends. Math. Cogn. 2, 6393 (1996).
  38. Qin, S. et al. Dissecting medial temporal lobe contributions to item and associative memory formation. Neuroimage 46, 874881 (2009).
  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, 889901 (2009).
  41. Friederici, A.D. The brain basis of language processing: from structure to function. Physiol. Rev. 91, 13571392 (2011).
  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, 104110 (2005).
  43. Toga, A.W., Thompson, P.M. & Sowell, E.R. Mapping brain maturation. Trends Neurosci. 29, 148159 (2006).
  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, 79417946 (2012).
  45. Glover, G.H. & Law, C.S. Spiral-in/out BOLD fMRI for increased SNR and reduced susceptibility artifacts. Magn. Reson. Med. 46, 515522 (2001).
  46. Nichols, T. & Hayasaka, S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat. Methods Med. Res. 12, 419446 (2003).
  47. Sanchez, C.E., Richards, J.E. & Almli, C.R. Age-specific MRI templates for pediatric neuroimaging. Dev. Neuropsychol. 37, 379399 (2012).
  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, 433442 (2000).
  49. Duvernoy, H. The Human Hippocampus: Functional Anatomy, Vascularization and Serial Sections with MRI (Springer, Verlag Berlin Heidelberg, 2005).

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Author information

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

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.

Competing financial interests

The authors declare no competing financial interests.

Corresponding authors

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Supplementary information

Supplementary Figures

  1. Supplementary Figure 1: Longitudinal and cross-sectional changes in accuracy and RTs during addition problem solving. (170 KB)

    (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.

  2. Supplementary Figure 2: Brain areas activated during addition problem solving in children. (268 KB)

    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.

  3. Supplementary Figure 3: Longitudinal changes in task-related activation in the prefrontal cortex and the parietal cortex during addition problem solving. (226 KB)

    (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.

  4. Supplementary Figure 4: Longitudinal changes in task-related hippocampal functional connectivity. (549 KB)

    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.

  5. Supplementary Figure 5: Developmental changes in task-related activation in the medial temporal lobe from childhood through adolescence into adulthood. (96 KB)

    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.

  6. Supplementary Figure 6: Correlation between task-related activation and addition task performance across children, adolescents and adults. (321 KB)

    (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.

  7. Supplementary Figure 7: Developmental changes in interproblem multivoxel pattern stability in frontal cortex and ventral-temporal cortex. (188 KB)

    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.

  8. Supplementary Figure 8: Interproblem multivoxel pattern stability analysis with comparable number of correctly solved problems across groups. (249 KB)

    (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.

  9. Supplementary Figure 9: Task-related activation in the hippocampus using AAL masks versus manually drawn ROIs (based on a pediatric brain template). (96 KB)

    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.

PDF files

  1. Supplementary Text and Figures (6,965 KB)

    Supplementary Figures 1–9, Supplementary Results and Supplementary Tables 1–9

  2. Supplementary Methods Checklist (188 KB)

Additional data