Range effects of an irrelevant dimension on classification
Range effects of an irrelevant dimension on classification
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DOI：
10.3758/bf03213123
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发表时间：
1999-11-01
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影响因子：
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通讯作者：
Lockhead, GR
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文献类型：
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作者：
Huettel, SA;Lockhead, GR
在单变量分类任务中，受试者根据唯一变化的属性对刺激进行分类。在正交分类任务（通常称为过滤任务）中，受试者被指示忽略的不相关属性中还存在试验与试验之间的差异。过滤任务的性能通常比单变量控制任务慢。我们在实验中研究了不相关的试对试的变化范围如何影响音高/响度分类任务的反应。实验1使用两个级别的音高和响度作为刺激，重复了先前的工作，表明当不相关维度的范围变大时，反应会更慢。同样在实验1中，序列分析表明，反应时间既取决于序列，也取决于独立于序列的刺激集。实验2和3在不相关的维度上使用了几个层次，结果表明，在不同的音调差异较大的情况下，对响度进行分类的反应会更慢，但只有在反应重复的情况下才会如此。当响应发生变化时，性能基本上不受试验与试验无关的变化的影响。这种相互作用支持了这样一个结论，即在正交分类任务中，平均表现变慢，即加纳干扰，不是由于受试者在过滤刺激属性方面存在困难。这是由于被试处理连续刺激差异的方式。我们要求更频繁地报告顺序分析，因为这些报告可以揭示从数据平均中无法获得的信息。
In univariate classification tasks, subjects sort stimuli on the basis of the only attribute that varies. In orthogonal classification tasks, often called filtering tasks, there additionally are trial-to-trial variations in irrelevant attributes that the subjects are instructed to ignore. Performance is generally slower in filtering tasks than in univariate control tasks. We investigated this slowing in experiments of how the range of irrelevant trial-to-trial variation affects responses in pitch/loudness classification tasks. Using two levels of pitch and of loudness as stimuli, Experiment 1 replicated prior work showing that responses are slowed more when the range of the irrelevant dimension is made larger. Also in Experiment 1, sequential analyses showed that response time depends both on sequence and on the stimulus set independent of sequence. Experiments 2 and 3 used several levels on the irrelevant dimension and showed that responses to categorize loudness are slowed more by larger trial-to-trial pitch differences, but only on trials when the response repeats. When the response changes, performance is essentially unaffected by trial-to-trial irrelevant variation. This interaction supports the conclusion that slowed average performance in orthogonal classification tasks, which is known as Garner interference, is not due to difficulties that subjects have in filtering stimulus attributes. It is due to how subjects process successive stimulus differences. We call for more frequent reports of sequential analyses, because these can reveal information that is not available from data averages.