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Processing number and length in the parietal cortex: Sharing resources, not a common code.

Valentina Borghesani1, Maria Dolores de Hevia2, Arnaud Viarouge3

  • 1Université Pierre et Marie Curie, Paris, France; Cognitive Neuroimaging Unit, CEA DRF/I2BM, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin center, Gif/Yvette, France; Center for Mind/Brain Sciences, University of Trento, Italy.

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Summary
This summary is machine-generated.

Brain imaging reveals that processing numbers and other quantities like length involves overlapping brain regions. However, these regions do not use a shared neural code, suggesting distinct representations despite shared resources.

Keywords:
LengthMagnitudesNumerosityRepresentational similarity analysisfMRI

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Area of Science:

  • Cognitive Neuroscience
  • Numerical Cognition
  • Neuroimaging

Background:

  • Debate exists on whether numerical cognition and non-numerical quantity processing share brain representations.
  • Investigating a common generalized magnitude representation versus separate processing is crucial.

Purpose of the Study:

  • To determine if the brain uses a common neural code for processing numerosity and line length.
  • To explore the neural basis of magnitude representation in numerical cognition.

Main Methods:

  • Acquired high-resolution functional MRI data during magnitude comparison tasks (numerosity vs. line length).
  • Employed multivariate pattern analysis (MVPA) to decode quantity representations.
  • Compared brain activation patterns between discrete and continuous quantity processing.

Main Results:

  • Observed common recruitment of occipital and parietal cortices for both numerosity and line length processing.
  • MVPA indicated similar distance-dependent magnitude coding in some overlapping regions.
  • Found no evidence of a dimension-invariant, generalized quantity code across representations.

Conclusions:

  • Numerical cognition and non-numerical quantity processing utilize partially overlapping neural resources.
  • Representations within these shared brain regions are not based on a common, dimension-invariant neural code.
  • Findings suggest distinct neural codes for discrete and continuous quantities despite shared brain areas.