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The semantic network supports approximate computation.

Mengyi Li1, Yuxin Tan2, Jiaxin Cui1

  • 1State Key Laboratory of Cognitive Neuroscience and Learning.

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Brain imaging reveals distinct neural networks for approximate and exact math. Approximate math engages the semantic network, while exact math relies on the phonological network.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Mathematics

Background:

  • Understanding the neural basis of mathematical computation is crucial for cognitive science.
  • Differentiating brain networks for approximate versus exact arithmetic can elucidate cognitive processes.

Purpose of the Study:

  • To dissociate brain networks underlying strategy-based approximate computation and procedure-based exact computation using complex arithmetic problems.
  • Investigate neural activation patterns and functional connectivity during distinct mathematical tasks.

Main Methods:

  • fMRI scans were conducted on 28 college students solving complex approximate and exact arithmetic problems (addition, subtraction, multiplication, division).
  • Neuroimaging data were analyzed using whole brain, region of interest, and functional connectivity approaches (psychophysiological interaction).

Main Results:

  • Approximate computation showed greater activation in the bilateral inferior frontal gyrus (orbital), middle temporal gyrus, angular gyrus, and dorsomedial prefrontal cortex (semantic network).
  • Exact computation showed greater activation in the left rolandic operculum and bilateral hippocampus.
  • Functional connectivity revealed approximate computation's reliance on the left intraparietal sulcus to semantic areas, while exact computation utilized the left intraparietal sulcus to phonological areas.

Conclusions:

  • Complex approximate computation is supported by the semantic network.
  • Complex exact computation is supported by the phonological network.