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Dependent Measure and Time Constraints Modulate the Competition Between Conflicting Feature-Based and Rule-Based Generalization Processes

机译:依赖性测量和时间约束调制基于特征和规则的泛化过程之间的竞争

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In our study, we tested the hypothesis that feature-based and rule-based generalization involve different types of processes that may affect each other producing different results depending on time constraints and on how generalization is measured. For this purpose, participants in our experiments learned cue-outcome relationships that followed the opposites rule: Single cues that signaled the same outcome (e.g., A-1/B-1) predicted the opposite outcome when presented in compound (e.g., AB-2). Some cues were only presented in compound during training (e.g., EF-1) to see if at test participants tended to generalize according to rule-based (i.e., E-2/F-2) or according to feature-based generalization ( i.e.,E-1/F-1). The generalization test used 2 different tasks: a predictive judgment task, and a cued-response priming task. In Experiment 1, participants' verbal ratings were consistent with rule-based generalization. However, participants' reaction times (RTs) in the cued-response priming task were consistent with feature-based generalization. Experiment 2 replicated the results from Experiment 1, and it also provided evidence consistent with feature-based or rule-based generalization depending on whether a short stimulus onset asynchrony (SOA; 200 ms) or a long SOA (1300 ms), respectively, was used in the priming task. Our results are interpreted as supporting the idea that feature-based generalization process relies on fast, associative processes, whereas rule-based generalization is slow and depends on executive control resources. The latter generalization process would inhibit the former when enough time and resources are available. Otherwise, feature-based generalization would take control of responses.
机译:在我们的研究中,我们测试了特征和规则的泛化的假设涉及不同类型的过程,该过程可能根据时间限制而产生不同的结果,并测量泛型。为此目的,我们的实验中的参与者学习了遵循对立面规则的提示关系:用信号处理相同的结果(例如,A-1 / B-1)的单个提示预测了在化合物中呈现的相反结果(例如,ab- 2)。一些线索仅在培训期间(例如,EF-1)呈现在化合物中,看看是否在测试参与者倾向于根据基于规则的(即E-2 / F-2)或根据基于特征的概括(即,e-1 / f-1)。泛化测试使用了2个不同的任务:预测判断任务和CUED响应启动任务。在实验1中,参与者的口头评级与基于规则的概括一致。然而,参与者在CUED响应启动任务中的反应时间(RTS)与基于特征的泛化一致。实验2通过实验1复制结果,并且还提供了与基于特征的或规则的概括一致的证据,具体取决于短刺激发作异步(SOA; 200毫秒)或长SOA(1300毫秒)是用于引发任务。我们的结果被解释为支持基于特征的泛化进程依赖于快速,关联过程的想法,而基于规则的泛化速度较慢,并且取决于执行控制资源。后一概括的过程将在有足够的时间和资源时禁止前者。否则,基于特征的泛化将控制响应。

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