Associative models of discrimination and generalisation: an evaluation in Pavlovian conditoning and causal judgement paradigms

歧视和泛化的联想模型：巴甫洛夫条件作用和因果判断范式的评估

• 批准号: 55170469
• 负责人: Professor Dr. Harald Lachnit
• 金额: --
• 依托单位: Abteilung Assoziatives Lernen
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2007
• 资助国家: 德国
• 起止时间: 2006-12-31 至 2009-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/55170469?language=en
• 关键词: Associative; models; discrimination; generalisation; evaluation

Learning is fundamental to humans from basic survival to everyday live. This ubiquity is matched in nature where animals in all parts of the evolutionary scale demonstrate learning. Successful scientific study of learning involves identification of the target behaviour and development of suitable study procedures. Our project is concerned with how people learn to predict events and uses convergent operations to measure performance. Based upon Pavlov's seminal contribution to use salivary reflexes to measure learning, associative theory has now been extended way beyond the study of reflexes in animals, showing that very different aspects of human behaviour can be addressed by associative models. One of the key problems in associative theory is to specify how multiple stimuli are perceived and processed. For example, Pavlov's bell occurred in a context containing numerous background sounds and visual stimuli. Furthermore, responses to any stimulus depend on the context. Responding differently to the same stimulus in different compounds (or contexts) is fundamental to the solution of many problems. Our proposal aims to test the predictions of competing associative models for the representation of stimulus compounds in Pavlovian eyeblink conditioning and causal judgement paradigms. These superficially very different procedures, one based on simple reflexes the other on "higher-order" cognitive processes, share many attributes. By using these different paradigms we will test the generality of our conclusions.

学习是人类从基本生存到日常生活的根本。这种普遍性在自然界中是匹配的，在进化规模的所有部分的动物都表现出学习。成功的学习科学研究包括确定目标行为和制定适当的学习程序。我们的项目关注人们如何学习预测事件，并使用收敛运算来衡量性能。基于巴甫洛夫对使用唾液反射来测量学习的开创性贡献，联想理论现在已经扩展到动物反射的研究之外，表明人类行为的非常不同的方面可以通过联想模型来解决。联想理论的关键问题之一是如何确定多个刺激是如何被感知和加工的。例如，巴甫洛夫的钟声发生在一个包含许多背景声音和视觉刺激的环境中。此外，对任何刺激的反应都取决于环境。在不同的化合物（或背景）中对相同刺激做出不同的反应是解决许多问题的基础。我们的建议旨在测试竞争联想模型的预测代表的刺激化合物在巴甫洛夫眨眼条件反射和因果判断范式。这些表面上非常不同的程序，一个基于简单的反射，另一个基于“高阶”认知过程，共享许多属性。通过使用这些不同的范例，我们将测试我们的结论的一般性。