Three challenges for connecting model to mechanism in decision-making.
Three challenges for connecting model to mechanism in decision-making.
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DOI：
10.1016/j.cobeha.2016.06.008
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发表时间：
2016-10
影响因子：
5
通讯作者：
Kiani R
中科院分区：
文献类型：
--
作者：
Churchland AK;Kiani R
近年来，人们对理解支持决策的神经机制越来越感兴趣。用于测量和操纵神经元的新工具的出现，以及多种新动物模型和感觉系统的出现，导致了许多新颖数据集的生成。这些新方法限制决策模型的潜力是前所未有的。在这里，我们认为要充分利用这些新方法，必须应对三个挑战。首先，实验者必须设计控制良好的行为实验，以便能够区分竞争的行为策略。其次，神经反应的分析应该超越单个神经元，考虑到单次试验与试验平均方法的权衡。最后，应该使用定量模型比较，但必须考虑常见的障碍。
Recent years have seen a growing interest in understanding the neural mechanisms that support decision-making. The advent of new tools for measuring and manipulating neurons, alongside the inclusion of multiple new animal models and sensory systems has led to the generation of many novel datasets. The potential for these new approaches to constrain decision-making models is unprecedented. Here, we argue that to fully leverage these new approaches, three challenges must be met. First, experimenters must design well-controlled behavioral experiments that make it possible to distinguish competing behavioral strategies. Second, analyses of neural responses should think beyond single neurons, taking into account tradeoffs of single-trial versus trial-averaged approaches. Finally, quantitative model comparisons should be used, but must consider common obstacles.