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Related Experiment Video

Updated: Mar 13, 2026

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Self-similarity and recursion as default modes in human cognition.

Florian P Fischmeister1, Mauricio J D Martins2, Roland Beisteiner1

  • 1Department of Neurology, Medical University of Vienna, Vienna, Austria; High-Field Magnetic Resonance Center, Vienna, Austria.

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The brain

Keywords:
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Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging
  • Human Cognition

Background:

  • Humans naturally create recursive hierarchies across language, social structures, and visual-spatial domains.
  • Representing recursive structures may enhance processing efficiency by compressing information through internalized neural rules.
  • Previous research suggests a link between internal representations, information compression, and efficient hierarchical processing.

Purpose of the Study:

  • To investigate whether the brain's representation of recursive hierarchies relies on internalized rules.
  • To compare neural processing of recursive versus non-recursive visual hierarchies.
  • To examine the relationship between task-evoked functional networks and resting-state brain architecture.

Main Methods:

  • Used task-free resting-state functional magnetic resonance imaging (fMRI).
  • Compared brain activity during the mental representation of visual hierarchies (recursive vs. non-recursive).
  • Analyzed functional connectivity within brain networks, specifically the Default Mode Network and Fronto-Parietal Control Network.

Main Results:

  • Increased connectivity within Default Mode Network (DMN) areas was observed during recursion representation.
  • Increased connectivity within the Fronto-Parietal Control Network was found during non-recursive representation.
  • These findings link the DMN to the processing of recursive hierarchical information.

Conclusions:

  • Human hierarchical information processing, particularly with recursion, is supported by the Default Mode Network (DMN).
  • Recursion representation engages an internally-biased processing mode mediated by DMN subsystems.
  • Internalized, compressed rule representations via the DMN may reduce cognitive load for processing complex hierarchical structures.