Synaptic theory of replicator-like melioration.
Synaptic theory of replicator-like melioration.
复制标题
DOI：
10.3389/fncom.2010.00017
复制
发表时间：
2010
影响因子：
3.2
通讯作者：
Loewenstein Y
中科院分区：
文献类型：
--
作者：
Loewenstein Y
根据改良理论，在重复选择环境中，生物体会改变其选择偏好，以支持提供最高回报的替代品。本文的目的是解释这种学习行为如何从突触功效的微观变化中出现，在两个选择重复选择实验的背景下。我考虑了一大类突触可塑性规则，其中突触功效的变化是由奖励和神经活动之间的协方差驱动的。我构建了一个通用的框架，预测任何决策神经网络的学习动态，实现这种突触可塑性规则，并表明，改善自然出现在这样的网络。此外，由此产生的学习动力学遵循复制方程，该方程通常用于从现象学上描述操作性条件反射实验中的行为变化。几个例子演示了网络的学习速率如何受到其属性和可塑性规则的影响。这些结果有助于弥合细胞生理学和学习行为之间的差距。
According to the theory of Melioration, organisms in repeated choice settings shift their choice preference in favor of the alternative that provides the highest return. The goal of this paper is to explain how this learning behavior can emerge from microscopic changes in the efficacies of synapses, in the context of a two-alternative repeated-choice experiment. I consider a large family of synaptic plasticity rules in which changes in synaptic efficacies are driven by the covariance between reward and neural activity. I construct a general framework that predicts the learning dynamics of any decision-making neural network that implements this synaptic plasticity rule and show that melioration naturally emerges in such networks. Moreover, the resultant learning dynamics follows the Replicator equation which is commonly used to phenomenologically describe changes in behavior in operant conditioning experiments. Several examples demonstrate how the learning rate of the network is affected by its properties and by the specifics of the plasticity rule. These results help bridge the gap between cellular physiology and learning behavior.
登录
查看更多内容
影响因子：
2.5
作者：
Farries, Michael A.;Fairhall, Adrienne L.
通讯作者：
Fairhall, Adrienne L.
影响因子：
2.9
作者：
Baras, Dorit;Meir, Ron
通讯作者：
Meir, Ron
影响因子：
8.6
作者：
Fiete, Ila R.;Seung, H. Sebastian
通讯作者：
Seung, H. Sebastian
影响因子：
2.9
作者：
Loewenstein, Yonatan;Prelec, Drazen;Seung, H. Sebastian
通讯作者：
Seung, H. Sebastian
影响因子：
25
作者：
Law, Chi-Tat;Gold, Joshua I.
通讯作者：
Gold, Joshua I.