A physiologically-inspired model of numerical classification based on graded stimulus coding.
A physiologically-inspired model of numerical classification based on graded stimulus coding.
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DOI：
10.3389/neuro.08.001.2010
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发表时间：
2010
影响因子：
3
通讯作者：
Raghavachari S
中科院分区：
文献类型：
--
作者：
Pearson J;Roitman JD;Brannon EM;Platt ML;Raghavachari S
在大多数自然的决策环境中，在竞争行为中进行选择的过程是在信息丰富但可能模糊的刺激存在的情况下进行的。关于大小的决定--时间、长度和亮度等线性排序的量--构成了这类决定的一个重要子类。人们早就知道，对这些量的感知判断遵循韦伯定律，其中大小的刚好可察觉的差异与大小本身成比例。目前生理启发模型的数值分类假设歧视是通过一个标记的线代码的神经元选择性调谐的数字，观察到的模式在腹侧顶内区（VIP）的猕猴的神经元的放电率。相比之下，在连续的外侧顶内区（LIP）的神经元信号的数量在一个分级的方式，这表明的可能性，数字分类可以实现在没有神经元调谐的数量。在这里，我们考虑的性能的决策模型的基础上，这种模拟编码方案在一个聚合的歧视任务-数字二分法。我们证明了一个基本的两个神经元分类器模型，来自实验测量的LIP神经元的单调响应，是足以重现猴子的数字二分法行为，并且分类器的阈值可以通过简单的学习规则由奖励最大化来设置。此外，我们的模型预测偏离韦伯定律标度的选择行为在高数值。总之，这些结果表明，这两个通用的神经元框架的幅度为基础的决定和奖励应急在分类的作用，这样的刺激。
In most natural decision contexts, the process of selecting among competing actions takes place in the presence of informative, but potentially ambiguous, stimuli. Decisions about magnitudes – quantities like time, length, and brightness that are linearly ordered – constitute an important subclass of such decisions. It has long been known that perceptual judgments about such quantities obey Weber's Law, wherein the just-noticeable difference in a magnitude is proportional to the magnitude itself. Current physiologically inspired models of numerical classification assume discriminations are made via a labeled line code of neurons selectively tuned for numerosity, a pattern observed in the firing rates of neurons in the ventral intraparietal area (VIP) of the macaque. By contrast, neurons in the contiguous lateral intraparietal area (LIP) signal numerosity in a graded fashion, suggesting the possibility that numerical classification could be achieved in the absence of neurons tuned for number. Here, we consider the performance of a decision model based on this analog coding scheme in a paradigmatic discrimination task – numerosity bisection. We demonstrate that a basic two-neuron classifier model, derived from experimentally measured monotonic responses of LIP neurons, is sufficient to reproduce the numerosity bisection behavior of monkeys, and that the threshold of the classifier can be set by reward maximization via a simple learning rule. In addition, our model predicts deviations from Weber Law scaling of choice behavior at high numerosity. Together, these results suggest both a generic neuronal framework for magnitude-based decisions and a role for reward contingency in the classification of such stimuli.
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影响因子：
3.2
作者：
DEHAENE, S;CHANGEUX, JP
通讯作者：
CHANGEUX, JP
影响因子：
25
作者：
Lo, Chung-Chuan;Wang, Xiao-Jing
通讯作者：
Wang, Xiao-Jing
影响因子：
16.2
作者：
Piazza, M;Izard, V;Dehaene, S
通讯作者：
Dehaene, S
影响因子：
64.8
作者：
Platt, ML;Glimcher, PW
通讯作者：
Glimcher, PW
DOI：
10.1037/0097-7403.9.2.160
发表时间：
1983-01-01
期刊：
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-ANIMAL BEHAVIOR PROCESSES
影响因子：
--
作者：
PLATT, JR;DAVIS, ER
通讯作者：
DAVIS, ER