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Temporal Synchrony in Bodily Interaction Enhances the Aha! Experience: Evidence for an Implicit Metacognitive
Jiajia Su1,2, Haosheng Ye2
1School of Educational Science, Jiangsu Second Normal University, Nanjing 211200, China.
Bodily interaction significantly impacts the Aha! experience through implicit metacognitive predictive processing. This study introduces a new mechanism and paradigm for understanding insight, linking embodied cognition to metacognition.
Area of Science:
- Cognitive Neuroscience
- Embodied Cognition
- Metacognition
Background:
- The Aha! experience, or insight, has been traditionally viewed holistically.
- The role of bodily interaction and predictive processing in insight remains underexplored.
Purpose of the Study:
- To propose and validate the mechanism of implicit metacognitive predictive processing.
- To investigate how bodily interaction influences the Aha! experience.
- To establish a quantifiable, three-stage paradigm for insight research.
Main Methods:
- Three experimental groups manipulated temporal synchrony in bodily interaction (Immediate Mirror, Delayed Mirror, No-Interaction Control).
- A three-stage paradigm (Prediction, Execution, Feedback) decomposed insight tasks.
- Functional near-infrared spectroscopy (fNIRS) and functional connectivity analyses were employed.
Main Results:
- Bodily interaction significantly modulated the intensity of the Aha! experience, mediated by metacognitive predictive processing.
- fNIRS revealed the Somato-Cognitive Action Network (SCAN) involvement in early prediction stages.
- Shared neural mechanisms, including the Reward Network (RN), Dorsal Attention Network (DAN), and Ventral Attention Network (VAN), were identified for bodily interaction and insight.
Conclusions:
- Implicit metacognitive predictive processing offers a novel mechanism linking bodily interaction to the Aha! experience.
- The three-stage paradigm provides a quantifiable approach to studying insight.
- Findings integrate embodied cognition, enactive cognition, and metacognitive predictive processing for a unified account of insight.
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