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Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
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Related Experiment Video

Updated: Dec 18, 2025

Training Synesthetic Letter-color Associations by Reading in Color
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Functional network activity during errorless and trial-and-error color-name association learning.

Madoka Yamashita1,2,3, Tetsuya Shimokawa1,2, Ferdinand Peper1,2

  • 1Department of Rehabilitation Science, Graduate School of Health Sciences Discipline, Life and Medical Sciences Area, Kobe University, Kobe, Japan.

Brain and Behavior
|June 20, 2020
PubMed
Summary

Trial-and-error (T&E) learning shows higher default mode network (DMN) connectivity than errorless (EL) learning. Differences in learning benefits may stem from how the DMN and fronto-parietal network (FPN) integrate information.

Keywords:
cognitive functionfMRIlearningrehabilitation

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Area of Science:

  • Cognitive Neuroscience
  • Neuroimaging
  • Learning Sciences

Background:

  • Errorless (EL) and trial-and-error (T&E) learning are established cognitive rehabilitation techniques.
  • The underlying neural mechanisms differentiating EL and T&E learning remain largely unexplored.

Purpose of the Study:

  • To investigate the neural mechanisms associated with EL and T&E learning using functional magnetic resonance imaging (fMRI).
  • To compare functional network connectivity during these two distinct learning paradigms in healthy adults.

Main Methods:

  • fMRI data were acquired from healthy adults undergoing both EL and T&E learning tasks.
  • Participants learned unfamiliar Japanese color-name associations.
  • Graph theory analysis was applied to assess within-network (default mode network [DMN] and fronto-parietal network [FPN]) and between-network connectivity.

Main Results:

  • Significantly higher within-DMN connectivity was observed during T&E learning compared to EL learning.
  • A weak correlation was found between memory score differences and between-network connectivity variations between the two learning methods.

Conclusions:

  • Within-DMN connectivity plays a crucial role in T&E learning.
  • The differential learning benefits of EL versus T&E approaches may be linked to the functional integration strength between the DMN and FPN.