Cognitive Neurobiology and Helmholtz Institute, Department of Psychology, Utrecht University, Utrecht, The Netherlands.
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
Neurosci Biobehav Rev. 2017 Oct;81(Pt B):238-246. doi: 10.1016/j.neubiorev.2016.12.021. Epub 2016 Dec 22.
Artificial grammar learning is a popular paradigm to study syntactic ability in nonhuman animals. Subjects are first trained to recognize strings of tokens that are sequenced according to grammatical rules. Next, to test if recognition depends on grammaticality, subjects are presented with grammar-consistent and grammar-violating test strings, which they should discriminate between. However, simpler cues may underlie discrimination if they are available. Here, we review stimulus design in a sample of studies that use particular sounds as tokens, and that claim or suggest their results demonstrate a form of sequence rule learning. To assess the extent of acoustic similarity between training and test strings, we use four simple measures corresponding to cues that are likely salient. All stimulus sets contain biases in similarity measures such that grammatical test stimuli resemble training stimuli acoustically more than do non-grammatical test stimuli. These biases may contribute to response behaviour, reducing the strength of grammatical explanations. We conclude that acoustic confounds are a blind spot in artificial grammar learning studies in nonhuman animals.
人工语法学习是一种研究非人类动物句法能力的流行范式。研究对象首先被训练识别根据语法规则排序的标记字符串。接下来，为了测试识别是否依赖于语法性，研究对象会被呈现语法一致和语法不一致的测试字符串，他们应该在这些字符串之间进行区分。然而，如果存在更简单的线索，它们可能会成为区分的基础。在这里，我们回顾了一组使用特定声音作为标记的研究中的刺激设计，这些研究声称或表明他们的结果证明了一种序列规则学习形式。为了评估训练和测试字符串之间的声学相似性程度，我们使用了四个简单的度量标准，这些度量标准对应于可能显著的线索。所有刺激集都存在相似性度量中的偏差，即语法测试刺激在声学上比非语法测试刺激更类似于训练刺激。这些偏差可能会影响反应行为，从而降低语法解释的强度。我们得出结论，在非人类动物的人工语法学习研究中，声学混淆是一个盲点。
