一个神经代码,支持对人类仪器信息需求的前概率推理
Nicholas M Singletary1,2,3,4, Guillermo Horga5,6, Jacqueline Gottlieb7,8,9
1Doctoral Program in Neurobiology and Behavior, Columbia University, New York, NY, USA. nicholas.singletary@nyspi.columbia.edu.
Communications biology
|October 2, 2024
概括
大脑通过整合先前的确定性和来源可靠性来估计信息获取. 后壁和外层皮层代表预期的后部确定性,对于积极的信息收集至关重要.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 决策科学 决策科学 决策科学
背景情况:
- 积极的决策涉及寻找信息,但估计信息获取的机制不太清楚.
- 大脑必须前性地估计来自不同来源的信息的价值.
研究的目的:
- 为了研究大脑如何估计未来的信息获取.
- 确定在主动决策过程中信息估值的基础的神经机制.
主要方法:
- 功能磁共振成像 (fMRI) 用于观察大脑活动.
- 参与者在一个具有不同奖励,不确定性和诊断性的任务中竞价信息.
- 多维素模式分析 (MVPA) 解码了神经表征.
主要成果:
- 报价反映了对先前确定性和预期后期确定性的敏感性,与信息价值理论保持一致.
- 预期的后部确定性是从后壁和外层皮层的活动中解码出来的.
- 预期后期确定性的神经表示独立于仪器奖励.
结论:
- 后顶层和外层皮层参与预测信息获取.
- 这些地区可以调解对积极搜索信息的后期概率的前性估计.
- 了解这些机制是适应性决策的关键.
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