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Related Experiment Video

Updated: Feb 6, 2026

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
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Neural and behavioural differences in multisensory statistical and reinforcement learning across development and task

Nina Raduner1,2,3,4,5, Carmen Providoli1,2,4,5, Sarah V Di Pietro1,2

  • 1URPP Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zurich, Zurich, Switzerland.

Imaging Neuroscience (Cambridge, Mass.)
|February 5, 2026
PubMed
Summary

Adults show more advanced multisensory learning than children, particularly in detecting statistical regularities. This study reveals developmental differences in reinforcement and statistical learning processes.

Keywords:
computational modellingdevelopmental cognitive neurosciencefMRImultisensory learningreward prediction errorssurprise processing

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Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Cognitive Science

Background:

  • Multisensory processing and integration are crucial for development, relying on pattern detection and feedback-based behavioral adjustments.
  • The precise developmental trajectories of these multisensory learning mechanisms remain incompletely understood.

Purpose of the Study:

  • To investigate neural and behavioral differences in multisensory statistical and reinforcement learning between adults and children.
  • To examine these learning processes across varying task difficulties in children.

Main Methods:

  • Utilized discriminative choice and match recognition tasks with audio-visual or tactile-visual stimuli and embedded statistical regularities.
  • Compared learning in 28 adults (19.0-30.9 years) and two groups of children (N=28 and N=29, 8.5-12.8 years).
  • Employed computational modeling and neuroimaging (fMRI) to analyze behavioral and neural data.

Main Results:

  • All groups showed improved accuracy and faster reaction times over time; adults outperformed children, and audio-visual learning surpassed tactile-visual.
  • Adults exhibited more sophisticated learning strategies, higher sensitivity to value differences, and more deterministic choices.
  • Statistical surprise modulated specific brain regions (lateral prefrontal cortex, intraparietal sulcus, anterior cingulate cortex), while reward prediction errors engaged other areas (striatum, medial frontal, hippocampus).
  • Reward prediction errors were consistent across groups and tasks, but neural processing of statistical surprise showed developmental differences, suggesting immaturity in children's statistical regularity detection.

Conclusions:

  • Task design significantly influences the comparison of learning differences across developmental groups.
  • Reinforcement learning and statistical learning can be studied concurrently, revealing distinct developmental patterns in their neural underpinnings.
  • Children demonstrate less mature abilities in detecting statistical regularities compared to adults, highlighting developmental changes in multisensory learning.