默认模式子网络和多重需求区域对社会内容,地点和时间的变化做出专业反应
Ashley X Zhou1, Reza Rajimehr2, Arsalan Firoozi3
1MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK; Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, China.
Neuropsychologia
|June 24, 2025
概括
这项研究揭示了默认模式网络 (DMN) 子网络在处理自然事件中的独特作用. 这些大脑区域有助于我们感知和细分连续的经验,更新我们对世界的上下文理解.
科学领域:
- 神经科学是一个神经科学.
- 认知神经科学 认知神经科学
背景情况:
- 默认模式网络 (DMN) 对于内部定向的思维和自我参考处理至关重要.
- 了解DMN子网络如何促进处理连续的自然刺激是一个活跃的研究领域.
研究的目的:
- 研究DMN子网络在自然刺激过渡期间的特定作用.
- 检查DMN子网络的不同激活模式,以应对社会,位置和时间转变.
主要方法:
- 分析了来自StudyForrest数据集的功能磁共振成像 (fMRI) 数据.
- 在自然刺激过程中检查了DMN子网络 (dmPFC,MTL,Core) 和多重需求网络中的激活模式.
主要成果:
- 该dmPFC子网络显示了针对社会和位置转换的特定激活.
- 在MTL子网络中,首选的位置和时间过渡.
- 核心DMN子网络响应了所有过渡类型,而多重需求网络选择性地响应了时间过渡.
- 所有子网络都对主观事件边界呈现分级反应,不论语义距离如何.
结论:
- 在自然主义事件感知和细分过程中,DMN子网络表现出不同的功能配置文件.
- 这些发现支持一个合作模式,DMN子网络解释连续的外部事件,并保持一个更新的世界的上下文模型.
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