鼠类运动反映了证据积累任务中的内部决策动态
Gary A Kane1, Ryan A Senne2, Benjamin B Scott1
1Department of Psychological and Brain Sciences and Center for Systems Neuroscience, Boston University, Boston, Massachusetts, United States.
Journal of neurophysiology
|October 9, 2024
概括
新的研究揭示了运动如何反映正在进行的决策过程. 一种新的基于运动的漂移扩散模型 (mDDM) 通过将运动数据与证据积累相结合,更好地解释了动物的选择.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 动物行为 动物行为
背景情况:
- 感知决策整合了感官证据,规划和运动执行.
- 决策过程和运动执行之间的相互作用仍然不完全理解.
- 一些模型认为决策先于运动,而另一些模型则认为运动反映了正在进行的决策.
研究的目的:
- 研究决策动力学与导致选择的运动行为之间的关系.
- 开发和验证一种新型模型,将移动数据纳入决策模型.
- 通过包括运动参数来增强决策模型的预测能力.
主要方法:
- 在小鼠身上使用了基于脉冲的自由响应证据积累任务.
- 使用视频姿势估计开发了一种基于运动的漂移扩散模型 (mDDM).
- 限制性决策参数试验逐试验使用运动变量.
主要成果:
- 与传统的漂移扩散模型相比,mDDM对老鼠选择行为提供了更好的适应.
- 观察到选择前的一段头部不动的时期与决策边界相关.
- 在不运动期间呈现的刺激对选择选择产生了最显著的影响.
结论:
- 内部决策动态体现在可观察到的运动中.
- 将运动参数集成到扩散到结合模型中,可以显著提高它们的性能.
- 在证据积累任务中,mDDM提供了更准确的动物选择行为的描述.
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