在场景识别过程中,先前体重的个体差异的神经机制
Tien Cuong Phi1, Kojiro Hayashi2, Risa Katayama2
1Department of Systems Science, Graduate School of Informatics, Kyoto University, Kyoto, Japan.
NeuroImage
|November 26, 2025
概括
大脑连接模式预测了个人如何使用先前知识进行场景识别. 这一发现有助于理解在不确定的情况下的感知变化和认知策略.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 计算神经科学是一种神经科学.
背景情况:
- 人类的感知将感官数据与先前的知识整合在一起.
- 在使用先前知识方面,个体差异很大,但在网络层面并未得到充分理解.
- 以前的研究已经确定了用于预先引导视觉识别的皮质区域,但缺乏网络层面对变异性的洞察力.
研究的目的:
- 调查任务唤起的功能连接如何预测先前知识利用中的个体差异.
- 模拟与现场识别期间的先前知识相关的区域间连接调制.
- 使用大脑连接模式预测个人对先前信息的依赖.
主要方法:
- 从场景识别任务中重新分析功能磁共振成像 (fMRI) 数据集.
- 应用通用心理生理相互作用 (gPPI) 分析来识别连接性差异.
- 利用基于连接组的预测建模 (CPM) 来将连接模式与行为措施联系起来.
主要成果:
- 在皮层和皮层下节点的特定功能连接模式可以预测个体的先前重量.
- 这些预测性连接模式涉及多个大规模的功能性大脑网络.
- 这项研究成功地模拟了视觉场景识别过程中先前知识使用的个体差异.
结论:
- 任务唤起的功能连接可靠地预测了先前知识利用中的个体变化.
- 这项研究为理解感知变化提供了一个机制框架.
- 这些发现为在不确定的环境中识别认知策略的个性化标志物奠定了基础.
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