在审议过程中编码有风险的选择的神经动态揭示了单独的选择子空间
Logan M Peters1, Alec Roadarmel1, Jacqueline A Overton2
1Dept. of Biomedical Engineering, UC Davis.
Progress in neurobiology
|May 9, 2025
概括
在不确定性下的人类决策需要深思熟虑. 新的研究表明,风险选择过程中的神经动力学显示出不同的模式,表明证据的积累,并提供对大脑计算的见解.
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:
- 人类决策整合了来自多个大脑区域的信息.
- 决策往往发生在不确定性下,需要审议.
- 审议的神经动力学仍然在很大程度上是未知的.
研究的目的:
- 调查决策过程中人类审议的基础的神经动力学.
- 识别与不确定性下的选择相关的潜在大脑状态.
- 为了探索证据积累的神经表征.
主要方法:
- 在行为过程中利用来自数百个大脑位置的内电生理记录.
- 应用动态系统建模来分析高时间分辨率的神经数据.
- 在有风险和无风险的决策任务中检查了神经动态.
主要成果:
- 风险决策的神经动力学汇聚到选择特定的子空间.
- 随着决定的临近,子空间重叠减少了,这表明证据的积累.
- 这些动态是特定于有风险的决策,而不是没有风险的决策.
- 确定了潜态模型和回归分析之间的联系.
结论:
- 风险决策中的审议和证据积累是由共享的神经动态所代表的.
- 这些发现为控制人类选择的神经计算提供了新的见解.
- 建议在决策过程中积累证据的网络层次表示.
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