自形冲动:神经网络模型的一些探索

IF 1.3 4区 生物学 Q4 BEHAVIORAL SCIENCES
Miguel Aguayo-Mendoza, Jonathan Buriticá, José E. Burgos
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引用次数: 0

摘要

本研究评估了巴甫洛夫或然条件中强化的延迟和幅度的影响,扩展了对阿尔卡拉论文(2017 年)和布尔戈斯与加西亚-雷尔论文(2015 年)中描述的自形冲动现象的理解。根据弥散差异模型,我们分析了添加追踪间隔对冲动选择的维持反应的影响,冲动选择被视为对小的和即时的强化物的偏好,而不是对大的和延迟的强化物的偏好,并分析了情境单元以及抑制单元的作用。在 "模拟 "中,我们使用了带有抑制单元的模型,在两种具有不同延迟和强化幅度的信号中进行训练,随后在没有强化也没有学习的选择任务中同时呈现,采用 ABA 受试者内设计。总的来说,DD 模型成功地模拟了自形冲动现象,这与 Alcalá 的论文(2017 年)、Burgos 和 García-Leal (2015 年)以及 Picker 和 Poling (1982 年)的研究一致。它还预测了在引入追踪间隔后这种效应(自形冲动)的消除。本文讨论了观察到的结果及其影响,以及未来可能对动物和人类进行的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Autoshaped impulsivity: Some explorations with a neural network model

This study evaluated the effect of delay and magnitude of reinforcement in Pavlovian contingencies, extending the understanding of the phenomenon of autoshaped impulsivity as described in Alcalá's thesis (2017) and Burgos and García-Leal (2015). The effects of adding a trace interval were analyzed on the maintained responses of impulsive choice, seen as the preference of a small and immediate reinforcer over a larger and delayed one, and the role of the contextual unit, as well as the inhibitory units according to the Diffuse Discrepancy Model. In the Simulation, the model with inhibitory units was used, trained in two signals with different delays and reinforcement magnitudes, and subsequently presented concurrently in choice tasks without reinforcement nor learning, using an ABA within-subject design. In general, the DD model successfully simulated the phenomenon of autoshaped impulsivity, consistent with studies from Alcalá's thesis (2017), Burgos and García-Leal (2015), and Picker and Poling (1982). It also predicted the elimination of this effect (autoshaped impulsivity) after introducing a trace interval. The observed results and their implications are discussed, as well as possible future studies with animals and humans.

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来源期刊
Behavioural Processes
Behavioural Processes 生物-动物学
CiteScore
2.70
自引率
7.70%
发文量
144
审稿时长
4-8 weeks
期刊介绍: Behavioural Processes is dedicated to the publication of high-quality original research on animal behaviour from any theoretical perspective. It welcomes contributions that consider animal behaviour from behavioural analytic, cognitive, ethological, ecological and evolutionary points of view. This list is not intended to be exhaustive, and papers that integrate theory and methodology across disciplines are particularly welcome.
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