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Related Concept Videos

Cognitive Learning01:21

Cognitive Learning

707
Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
707
Problem-Solving01:29

Problem-Solving

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Effective problem-solving consists of two steps: 1. identifying the problem and 2. selecting the appropriate problem-solving strategy (i.e., a plan of action used to find a solution). Humans use four problem-solving strategies:
289

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Pre-stimulus brain oscillations predict insight versus analytic problem-solving in an anagram task.

Xinyi Zhu1, Yongtaek Oh1, Christine Chesebrough1

  • 1Department of Psychology, Drexel University, 3201 Chestnut Street, Philadelphia, PA, 19104, USA.

Neuropsychologia
|October 5, 2021
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Summary

Brain activity before a problem predicts solving strategy. Higher beta-band activity in specific brain regions suggests analytical problem-solving, while lower activity may indicate insight-based solutions.

Keywords:
AllostasisEEGInsightMid-cingulate cortexMoodProblem-solving

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Area of Science:

  • Cognitive Neuroscience
  • Neuroscience
  • Psychology

Background:

  • Problem-solving occurs via insight (sudden realization) or analysis (deliberate process).
  • Prestimulus brain activity can predict subsequent problem-solving strategies (insight vs. analysis).
  • Prior research utilized compound remote associates (CRA) tasks.

Purpose of the Study:

  • To investigate if prestimulus electroencephalogram (EEG) activity predicts insight versus analytic solving for anagrams.
  • To explore the role of brain activity in the preparation phase for different problem-solving approaches.

Main Methods:

  • High-density electroencephalograms (EEGs) were recorded during a 2-second prestimulus interval before anagram presentation.
  • EEG source reconstruction identified the origin of brain activity.
  • Statistical analyses examined the relationship between prestimulus activity, mood, and solving strategy.

Main Results:

  • Greater beta-band activity over right central-parietal cortex preceded analytic solving compared to insightful solving.
  • This activity originated from the left mid-cingulate cortex (MCC) and right postcentral gyrus.
  • Positive mood correlated with anterior cingulate cortex activity and more insight solutions, but did not interact with insight-related prestimulus activity.

Conclusions:

  • Prestimulus activity in the MCC may reflect allostasis, predicting analytic (high MCC activity) or insight (low MCC activity) problem-solving based on resource allocation.
  • Findings suggest task-type dependent interactions in prestimulus preparation, differing from previous CRA task studies.
  • Understanding these neural mechanisms can inform educational strategies for teaching problem-solving.