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相关概念视频

Cause and Effect01:53

Cause and Effect

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While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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相关实验视频

Updated: Jun 30, 2025

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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预先获得的功能连接预测了选择不一致性.

Asaf Madar1, Vered Kurtz-David2,3, Adam Hakim4

  • 1Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 69978, Israel asafmadar@mail.tau.ac.il.

The Journal of neuroscience : the official journal of the Society for Neuroscience
|March 20, 2024
PubMed
概括
此摘要是机器生成的。

在选择任务之前测量的神经倾向,可以预测不一致的经济选择. 价值和运动大脑网络之间的静止状态功能连接 (rsfMRI FC) 是选择不一致的关键预测因素.

关键词:
选择不一致性 不一致性在决策过程中做出决定.功能连接性的功能连接性预测建模预测建模

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科学领域:

  • 神经科学是一个神经科学.
  • 认知科学 认知科学
  • 行为经济学是一种行为经济学.

背景情况:

  • 经济理论经常假设合理的效用最大化.
  • 即使没有外部影响,人类的选择也可能是不一致和不理想的.
  • 以前的研究将选择过程中的大脑活动与不一致性联系起来.

研究的目的:

  • 调查神经倾向是否预测未来的选择不一致性.
  • 要确定静止状态功能连接 (FC) 是否可以预测选择行为.
  • 探索价值和汽车网络同步在选择不一致中的作用.

主要方法:

  • 休息状态功能磁共振成像 (rsfMRI) 用于在风险选择任务之前测量FC.
  • 来自价值和运动区域的FC测量,以及整个大脑的FC,被用来预测不一致性.
  • 一个神经网络在一个大数据集 (37,000名受试者) 上进行了外部验证.

主要成果:

  • 假设 (价值/运动) 和全脑FC模型都显著预测了选择不一致性.
  • 全脑模型主要依赖于价值和运动区域之间的FC.
  • 外部验证证实了FC对选择不一致性的预测能力.

结论:

  • 选择不一致的倾向植根于神经倾向.
  • 运动和价值大脑网络之间的同步对于预测选择不一致性至关重要.
  • rsfMRI FC提供了一个有前途的生物标志物,用于了解低于最佳的经济选择.