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Statistical learning is a mechanism for detecting associations among co-occurring elements in many domains and species. A key controversy is whether it leads to memory for discrete chunks composed of these associated elements, or merely to pairwise associations among elements. Critical evidence for the mere-association view comes from the “phantom-...
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Context 1
... words from phantom-words As shown in Table 2, phantom-words were generated following the design in Endress and Mehler (2009) and Endress and Langus (2017). Specifically, I reserved 12 shapes to generate two sets of two phantom-words each. ...Context 2
... each set of phantom-words, I reserved another set of three shapes to generate the actual words, by replacing one shape at a time. For example, and as shown in Table 2, if ABC and DEF are two phantom-words (where each letter represents a shape), the corresponding actual words would be GBC and GEF (replacing the first element of the phantom-words), AHC and DHF (replacing the middle element of the phantom-words), as well as ABI and DEI (replacing the last element of the phantom-words). I generated ten different random assignments between shapes and units, corresponding to different "languages" in statistical learning tasks. ...