语义记忆结构的变化支持成功的解决问题和模拟传输
Théophile Bieth1,2, Yoed N Kenett3, Marcela Ovando-Tellez4
1Sorbonne University, Institut du Cerveau - Paris Brain Institute -ICM-, Inserm, CNRS, AP-HP Hôpital de la Pitié-Salpêtrière, DMU Neuroscience, Paris, France. theo_bieth@hotmail.fr.
创造性问题解决涉及重组语义记忆网络 (SemNets). 在SemNets的变化,特别是与远程概念,帮助解决题和类似的问题.
科学领域:
- 认知心理学 认知心理学
- 网络科学 网络科学
- 神经科学是一个神经科学.
背景情况:
- 创造性解决问题的能力至关重要,但其认知机制尚未完全理解.
- 重组心理表现是一种提出的问题解决机制.
- 重组可以创建抽象的表征来解决类似的问题.
研究的目的:
- 研究语义记忆网络 (SemNet) 重组在创造性问题解决中的作用.
- 量化SemNet在解之前和之后的变化.
- 将SemNet重组与成功的题和类似的问题解决联系起来.
主要方法:
- 采用网络科学来分析参与者的语义记忆网络 (SemNets).
- 在参与者试图解决一个题之前和之后,测量了SemNet指标.
- 量化重组作为解决前阶段和解决后阶段之间的SemNet指标差异.
主要成果:
- 最初的证据表明,SemNet的重组与成功解决题有关.
- 解决者在与解决相关的概念和语义上遥远的概念之间显示出更强的关系.
- 在语义上遥远的概念的变化是积极解决题的关键.
结论:
- 问题解决涉及重组语义记忆网络.
- 语义记忆重组,特别是涉及远程概念,有助于创造性解决问题.
- 解决方案相关概念的变化可能表明先前的接触,而不是积极的解决问题.
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