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Related Experiment Video

Updated: May 9, 2026

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The Neural Correlates of Numerical Symbol Processing During Symbol-and-Numerosity Paired Learning.

Shuangrao Qi¹, Mengyi Li², Zhijun Cui³

¹State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.

The European Journal of Neuroscience

|May 8, 2026

Summary

This summary is machine-generated.

Neural mechanisms of numerical symbol processing were explored using event-related potentials (ERPs). The P2 component, not N1, emerged as a key marker for developing numerical skills and math achievement.

Keywords:

neural marker numerical symbol processing trial‐based interindividual ERP‐behavioural correlation

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Area of Science:

Cognitive Neuroscience
Developmental Psychology
Neuroscience

Background:

Numerical symbol processing is crucial for mathematical abilities.
The neural basis of skill acquisition in numerical processing is not well understood.
Event-related potentials (ERPs) offer insights into neural dynamics of cognitive tasks.

Purpose of the Study:

To investigate the neural mechanisms underlying the development of numerical symbol processing.
To correlate neural responses with behavioral performance and math achievement.
To identify specific ERP components associated with numerical processing proficiency.

Main Methods:

An artificial symbol learning paradigm was used to train participants on numerical symbols.
Event-related potential (ERP) data were recorded during numerical comparison tasks.
Trial-based ERP-behavior correlation analyses were performed with math achievement scores.

Main Results:

Significant correlations were found between N1/P2 components and reaction time in numerical comparison.
N1/P2 components also correlated with overall math achievement scores.
The association of occipital P2 with reaction time increased over sessions, while parietal P2 with math achievement decreased.

Conclusions:

The P2 component is a critical neural marker for the development of numerical symbol processing, surpassing the N1 component.
Brain-behavior correlations are essential for understanding developmental trajectories in numerical cognition.
Neural plasticity in numerical processing is reflected in dynamic changes in ERP-behavior associations.