神经关联和动态大脑状态在一个空间问题任务任务的创造性洞察力
Takeshi Ogawa1, Takatsugu Aihara2,3, Okito Yamashita2
1Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, 2-2-2, Hikaridai, Seika-cho, Soraku-gun, Kyoto, 619-0288, Japan. t.ogawa@atr.jp.
Scientific reports
|August 2, 2025
概括
解决空间洞察力问题需要不同的大脑网络. 默认模式网络 (DMN) 支持洞察力,而执行控制网络 (ECN) 则有助于分析思维,揭示了认知灵活性中的动态大脑状态.
科学领域:
- 认知神经科学 认知神经科学
- 神经成像是一种神经成像.
背景情况:
- 洞察力解决问题对于创造力至关重要,但它的神经基础,尤其是空间任务,是不清楚的.
- 了解大脑如何克服心理障碍以找到新的解决方案是一个关键的研究问题.
研究的目的:
- 在空间洞察力问题解决过程中研究大脑动态,使用火柴算术问题.
- 区分基于洞察力的基础神经机制与分析和快速解决问题的策略.
主要方法:
- 用功能磁共振成像 (fMRI) 来捕捉大脑活动.
- 一般线性模型 (GLM) 和隐藏马尔科夫模型 (HMM) 的分析被用来识别与不同策略相关的大脑区域和状态.
主要成果:
- 默认模式网络 (DMN) 在洞察解决方案中显示出更高的激活率,而执行控制网络 (ECN) 在快速和分析解决方案中更活跃.
- 隐藏马尔科夫模型 (HMM) 分析为每个解决问题策略确定了不同的大脑状态,与性能和过渡有关.
- 洞察解决方案期间大脑状态动态的变化增加表明认知灵活性增强.
结论:
- 空间洞察力解决问题涉及大规模大脑网络 (如DMN和ECN) 之间的动态相互作用.
- 不同的解决问题的策略与不同的神经状态和时间动态有关.
- 这项研究为神经基础和空间洞察的时间特征提供了新的见解.
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