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The older the better: a fourth-order adaptive network model for reward-driven choices of emotion regulation strategies over time
Applied Network Science ( IF 1.3 ) Pub Date : 2020-06-12 , DOI: 10.1007/s41109-020-00267-1
Nimat Ullah , Jan Treur

The choice of which emotion regulation strategy to use changes depending on context, which within Psychology is referred to as ‘flexibility’. Besides that, choices of emotion regulation strategies are prone to various other factors, ranging from culture to gender, expectations of their effect, age, etc. This paper considers the phenomenon where choices of emotion regulation strategies change adaptively with age. In addition, the choices within specific age frames are driven by some kind of reward that affects in an adaptive manner the learning of a specific emotion regulation strategy. These adaptive phenomena involve plasticity or metaplasticity of different orders. They have been modeled by a fourth-order adaptive mental network model where the choice of emotion regulation strategies is motivated by reward prediction, and different age phases have their own adaptive influences. Simulation results are discussed for evaluation of the adaptive network model. The fourth-order adaptive network model presented here extends a second-order adaptive network model previously addressed in a paper at the conference COMPLEX NETWORKS 2019.

中文翻译:

年龄越大越好:随着时间的推移,奖励调节情绪调节策略的选择的四阶自适应网络模型

使用哪种情绪调节策略的选择根据环境而变化,在心理学中这被称为“灵活性”。除此之外,情绪调节策略的选择还容易受到其他因素的影响,从文化到性别,对其效果的期望,年龄等。本文考虑了情绪调节策略的选择会随着年龄的变化而自适应变化的现象。另外,特定年龄范围内的选择受某种奖励的驱动,这些奖励以自适应方式影响特定情绪调节策略的学习。这些适应性现象涉及不同阶的可塑性或可塑性。他们是通过四阶自适应心理网络模型建模的,其中情绪调节策略的选择受奖励预测的激励,不同的年龄阶段都有各自的适应性影响。讨论了仿真结果,以评估自适应网络模型。本文介绍的四阶自适应网络模型扩展了先前在会议COMPLEX NETWORKS 2019上一篇论文中讨论的二阶自适应网络模型。
更新日期:2020-06-12
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