Princeton Neuroscience Institute, Princeton University, Princeton, 08544, USA.
Howard Hughes Medical Institute, Princeton University, Princeton, 08544, USA.
Nat Commun. 2018 Oct 15;9(1):4265. doi: 10.1038/s41467-018-06561-y.
Decision making in dynamic environments requires discounting old evidence that may no longer inform the current state of the world. Previous work found that humans discount old evidence in a dynamic environment, but do not discount at the optimal rate. Here we investigated whether rats can optimally discount evidence in a dynamic environment by adapting the timescale over which they accumulate evidence. Using discrete evidence pulses, we exactly compute the optimal inference process. We show that the optimal timescale for evidence discounting depends on both the stimulus statistics and noise in sensory processing. When both of these components are taken into account, rats accumulate and discount evidence with the optimal timescale. Finally, by changing the volatility of the environment, we demonstrate experimental control over the rats' accumulation timescale. The mechanisms supporting integration are a subject of extensive study, and experimental control over these timescales may open new avenues of investigation.
在动态环境中进行决策需要对可能不再反映当前世界状态的旧证据进行贴现。先前的工作发现，人类在动态环境中对旧证据进行贴现，但贴现率不是最优的。在这里，我们通过调整积累证据的时间尺度来研究老鼠是否可以在动态环境中最优地贴现证据。使用离散的证据脉冲，我们可以精确地计算出最优的推理过程。我们表明，证据贴现的最优时间尺度取决于刺激统计和感觉处理中的噪声。当考虑到这两个因素时，老鼠会以最优的时间尺度积累和贴现证据。最后，通过改变环境的波动性，我们证明了对老鼠积累时间尺度的实验控制。支持整合的机制是广泛研究的课题，对这些时间尺度的实验控制可能开辟新的研究途径。
