Linear-Nonlinear-Poisson models of primate choice dynamic
Linear-Nonlinear-Poisson models of primate choice dynamic
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DOI：
10.1901/jeab.2005.23-05
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发表时间：
2005-11-01
影响因子：
2.7
通讯作者：
Newsome, WT
中科院分区：
文献类型：
--
作者：
Corrado, GS;Sugrue, LP;Newsome, WT
传统上，匹配行为的均衡现象是在静态环境中研究的。在这里，我们试图通过研究高度动态的觅食环境中的行为来揭示导致匹配的本地选择机制。在我们的实验中，两只恒河猴(Macacca Mulatta)通过对电脑显示器上呈现的两个彩色图标中的一个进行眼动来寻找果汁奖励，每个图标都按照动态可变间隔时间表进行奖励。利用Wiener核分析的推广，我们以线性-非线性-泊松模型的形式对过去报酬对未来选择的影响进行了紧凑的机制描述。我们通过严格的预测性和生成性测试来验证该模型。与我们之前使用相同数据集所做的工作相比，该模型被证明是对选择行为的更好描述，并且与假定的神经值信号更紧密地关联。对以前模型的改进包括对过去回报的双曲(而不是指数)时间贴现，以及对期权价值的差异化(相对于分数)比较。通过数值模拟我们发现，在这类策略中，动物所使用的模型参数与最大化奖励收获效率的模型参数非常接近。
The equilibrium phenomenon of matching behavior traditionally has been studied in stationary environments. Here we attempt to uncover the local mechanism of choice that gives rise to matching by studying behavior in a highly dynamic foraging environment. In our experiments, 2 rhesus monkeys (Macacca mulatta) foraged for juice rewards by making eye movements to one of two colored icons presented on a computer monitor, each rewarded on dynamic variable-interval schedules. Using a generalization of Wiener kernel analysis, we recover a compact mechanistic description of the impact of past reward on future choice in the form of a Linear-Nonlinear-Poisson model. We validate this model through rigorous predictive and generative testing. Compared to our earlier work with this same data set, this model proves to be a better description of choice behavior and is more tightly correlated with putative neural value signals. Refinements over previous models include hyperbolic (as opposed to exponential) temporal discounting of past rewards, and differential (as opposed to fractional) comparisons of option value. Through numerical simulation we find that within this class of strategies, the model parameters employed by animals are very close to those that maximize reward harvesting efficiency.