# A study of notation dependence in fraction magnitude processing using event related potentials

**Authors:** Weimin Lin, Yun Pan, Jun Zhu, Liangzhi Jia, Huanyu Yang, Yajie Bi, Fangwen Yu, Di Zhang

PMC · DOI: 10.1038/s41598-025-23957-1 · Scientific Reports · 2025-11-17

## TL;DR

This study shows that the brain processes symbolic and non-symbolic fractions differently, suggesting two distinct systems for numerical understanding.

## Contribution

The study provides new evidence that symbolic and non-symbolic fraction processing involve distinct neural mechanisms.

## Key findings

- Non-symbolic fractions elicited a more negative N1 component compared to symbolic fractions.
- Processing non-symbolic fractions showed a P3 amplitude difference based on distance, unlike symbolic fractions.

## Abstract

Increasingly, research emphasizes that learning symbolic fractions (i.e., the quotient or ratio of two whole numbers) is challenging for both children and adults. However, humans and certain non-human animals are capable of representing the proportional relationships between non-symbolic magnitudes (e.g., dot arrays presented in different colors). The specific mechanisms underlying the relationship between symbolic and non-symbolic magnitude processing are still not sufficiently clear. In this study, we employed event-related potential (ERP) technology to investigate the relationship between symbolic and non-symbolic fractions in numerical processing. We found that, compared to symbolic fractions, the N1 component amplitude evoked by non-symbolic fractions was significantly more negative. When participants processed non-symbolic fractions, there was a significant difference in P3 amplitude between far distances and close distances; however, such differences were not observed when processing symbolic fractions. These findings lend support to the notion of a representation of fractions that is dependent on notation. This suggests that the processing of symbolic and non-symbolic fractions involves two distinct numerical systems.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12624129/full.md

## References

7 references — full list in the complete paper: https://tomesphere.com/paper/PMC12624129/full.md

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Source: https://tomesphere.com/paper/PMC12624129