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Updated: Jan 13, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures
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A geometric shape regularity effect in the human brain.

Mathias Sablé-Meyer1,2,3, Lucas Benjamin2, Cassandra Potier Watkins1

  • 1Collège de France, Université Paris-Sciences-Lettres (PSL), Paris, France.

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|January 12, 2026
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Summary
This summary is machine-generated.

Humans perceive geometric shapes using unique brain mechanisms. This study reveals specific neural pathways involved in processing shapes like hexagons and triangles, suggesting a symbolic mode of visual perception.

Keywords:
MEGbehaviorfMRIgeometryhumanneuroscienceoddballshape perception

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computer Vision

Background:

  • Human cultures have long recognized and produced regular geometric shapes, yet the underlying neural mechanisms remain unclear.
  • Behavioral evidence indicates humans are sensitive to geometric regularities like symmetry and parallelism, using them for efficient shape encoding.

Purpose of the Study:

  • To investigate the neural systems and dynamics involved in the perception of regular geometric shapes.
  • To compare brain activity during geometric shape perception with computational models.

Main Methods:

  • Functional magnetic resonance imaging (fMRI) was used in adults and 6-year-olds.
  • Magnetoencephalography (MEG) data were collected from adults.
  • Participants viewed simple geometric shapes (e.g., hexagons, triangles, quadrilaterals).

Main Results:

  • Geometric shapes, compared to other visual categories, showed hypoactivation in ventral visual areas.
  • Increased activation was observed in the intraparietal and inferior temporal regions, areas linked to mathematical processing.
  • Convolutional neural networks (CNNs) modeled early visual activity but not later dorsal and prefrontal signals.

Conclusions:

  • The perception of abstract geometric regularities involves distinct neural pathways beyond early visual processing.
  • These findings suggest that geometric shape perception engages an additional symbolic mode of visual perception.
  • Advanced deep-learning models incorporating discrete geometric features are needed to fully capture these neural signals.