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The development of numerical knowledge in early childhood: brain-environment considerations
Doctoral Thesis   Open access

The development of numerical knowledge in early childhood: brain-environment considerations

Elizaveta Ivanova
University of Surrey
Doctor of Philosophy (PhD), University of Surrey
28/08/2026
DOI:
https://doi.org/10.15126/thesis.902208

Abstract

fNIRS, numerical cognition, child development

Sometime between 3 and 5 years old, for the first time, a child begins to understand that the number words correspond to exact quantities. This understanding signifies a developmental milestone that plays a major role in shaping success beyond formal school performance. In this PhD, I investigated the lesser-known neural and environmental underpinnings that support symbolic numerical knowledge in early childhood. After a brief literature review, in Chapter 2, I investigated neural differences between preschoolers who linked number words to respective quantities and preschoolers who had yet to learn this ability. The findings revealed that symbolic numerical knowledge is associated with the emergence of the left parietal engagement and increased support from the right parietal region. In Chapter 3, I measured longitudinal changes in preschoolers’ brain responses before and after they built cardinal representations of number words. I found that the acquisition of symbolic numerical knowledge represents a frontoparietal reorganisation. Interestingly, neural changes in the bilateral parietal regions were observed before behavioural performance. Next, in Chapter 4, I investigated whether the role of the prefrontal region in early numerical development extends beyond domain-general support and includes number-specific involvement. The findings suggested that preschoolers rely on the domain-general prefrontal engagement during symbolic numerical processing. Going beyond the neural correlates, in Chapter 5, I explored how common environmental factors influence early numerical development across diverse cultures. I found that such environmental factors predicted performance in the UK, but not in South African preschoolers, suggesting that relevant environmental factors may differ between cultures. Finally, in Chapter 6, I developed a new pipeline for dealing with motion artefacts in fNIRS data. This methodological study supported statistical robustness in Chapters 1-4 and contributed to the research field by offering a more reliable and standardised method.

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