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Core number representations are shaped by language.

Elena Salillas1, Manuel Carreiras2

  • 1Basque Center on Cognition Brain and Language, San Sebastian, Spain.

Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
|March 11, 2014
PubMed
Summary
This summary is machine-generated.

Early math learning language shapes quantity representation. Bilinguals whose earliest math instruction was in Basque showed unique brain responses (N1-P2 effects) when comparing numbers using a base-20 system, suggesting language influences basic numerical cognition.

Keywords:
BilingualismDistance effectERPsMath cognitionQuantity code

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Linguistics

Background:

  • The relationship between language and mathematics is often viewed through calculation.
  • A more fundamental link may exist in how basic quantity representation is shaped by language.

Purpose of the Study:

  • To investigate if language influences the fundamental representation of numerical quantities.
  • To explore the impact of the language of early mathematics instruction on quantity representation.

Main Methods:

  • Comparing event-related potential (ERP) distance effects in Basque-Spanish bilinguals.
  • Analyzing brain responses (N1-P2 component) during numerical comparison tasks.
  • Utilizing digit pairs related through decimal (base-10) and vigesimal (base-20) systems.

Main Results:

  • Both bilingual groups showed N1-P2 distance effects for base-10 comparisons.
  • An N1-P2 distance effect for base-20 comparisons emerged only in the group with Basque as their language of learning mathematics (LL(math)).
  • This suggests the N1-P2 component is sensitive to verbal aspects of quantity representation influenced by early learning.

Conclusions:

  • Quantity representation appears to retain verbal traces from early learning experiences.
  • The language used for initial mathematics instruction (LL(math)) significantly impacts numerical cognition.
  • Early language of math learning may be crucial for optimal numerical communication and understanding.