Tovar Ángel E, Westermann Gert
Department of Psychology, Lancaster University, Lancaster, United Kingdom.
Facultad de Psicología, Universidad Nacional Autónoma de México, Ciudad de Mexico, Mexico.
Front Psychol. 2017 Oct 18;8:1848. doi: 10.3389/fpsyg.2017.01848. eCollection 2017.
A stimulus class can be composed of perceptually different but functionally equivalent stimuli. The relations between the stimuli that are grouped in a class can be learned or derived from other stimulus relations. If stimulus A is equivalent to B, and B is equivalent to C, then the equivalence between A and C can be derived without explicit training. In this work we propose, with a neurocomputational model, a basic learning mechanism for the formation of equivalence. We also describe how the relatedness between the members of an equivalence class is developed for both trained and derived stimulus relations. Three classic studies on stimulus equivalence are simulated covering typical and atypical populations as well as nodal distance effects. This model shows a mechanism by which certain stimulus associations are selectively strengthened even when they are not co-presented in the environment. This model links the field of equivalence classes to accounts of Hebbian learning and categorization, and points to the pertinence of modeling stimulus equivalence to explore the effect of variations in training protocols.
一个刺激类可以由感知上不同但功能上等效的刺激组成。在一个类别中被归为一组的刺激之间的关系可以通过学习获得，也可以从其他刺激关系中推导出来。如果刺激A与B等效，且B与C等效，那么A和C之间的等效性无需明确训练即可推导出来。在这项工作中，我们使用一个神经计算模型提出了一种形成等效性的基本学习机制。我们还描述了对于经过训练的和推导出来的刺激关系，等效类成员之间的相关性是如何发展的。模拟了三项关于刺激等效性的经典研究，涵盖了典型和非典型人群以及节点距离效应。该模型展示了一种机制，通过这种机制，某些刺激关联即使在环境中不同时出现时也会被选择性地加强。该模型将等效类领域与赫布学习和分类的理论联系起来，并指出对刺激等效性进行建模对于探索训练方案变化的影响具有相关性。
