英文标题：
《Explicit moments of decision times for single- and double-threshold
  drift-diffusion processes》
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作者：
Vaibhav Srivastava and Philip Holmes and Patrick Simen
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最新提交年份：
2016
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英文摘要：
  We derive expressions for the first three moments of the decision time (DT) distribution produced via first threshold crossings by sample paths of a drift-diffusion equation. The \"pure\" and \"extended\" diffusion processes are widely used to model two-alternative forced choice decisions, and, while simple formulae for accuracy, mean DT and coefficient of variation are readily available, third and higher moments and conditioned moments are not generally available. We provide explicit formulae for these, describe their behaviors as drift rates and starting points approach interesting limits, and, with the support of numerical simulations, discuss how trial-to-trial variability of drift rates, starting points, and non-decision times affect these behaviors in the extended diffusion model. Both unconditioned moments and those conditioned on correct and erroneous responses are treated. We argue that the results will assist in exploring mechanisms of evidence accumulation and in fitting parameters to experimental data.
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中文摘要：
我们推导了漂移扩散方程的样本路径通过第一阈值交叉产生的决策时间（DT）分布的前三个矩的表达式。“纯”扩散过程和“扩展”扩散过程被广泛用于模拟两种替代的强迫选择决策，虽然精度、平均DT和变异系数的简单公式很容易获得，但三阶矩和更高阶矩以及条件矩通常不可用。我们提供了明确的公式，描述了它们在漂移率和起始点接近有趣极限时的行为，并在数值模拟的支持下，讨论了漂移率、起始点和非决定时间的试验间变化如何影响扩展扩散模型中的这些行为。无论是无条件的时刻，还是以正确和错误的反应为条件的时刻，都会得到处理。我们认为，这些结果将有助于探索证据积累的机制，并将参数与实验数据进行拟合。
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Neurons and Cognition        神经元与认知
分类描述：Synapse, cortex, neuronal dynamics, neural network, sensorimotor control, behavior, attention
突触，皮层，神经元动力学，神经网络，感觉运动控制，行为，注意
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一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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一级分类：Quantitative Finance        数量金融学
二级分类：Mathematical Finance        数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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