Extending Statistical Learning Farther and Further: Long-Distance Dependencies, and Individual Differences in Statistical Learning and Language

Abstract

While statistical learning (SL) and language acquisition have been perceived as intertwined, such a view must contend with theoretical and empirical challenges.Against the backdrop of criticism leveled at early associationist efforts to account for language, a key concern for current SL approaches is whether it may suffice to enable the detection of long-distance relationships akin to those ubiquitously abounding in natural language.In Experiment 1, we extend results from previous work on the learning of nonadjacent dependencies to the learning of long-distance relations spanning three intervening elements; such learning is shown to obtain under two separate contexts.In Experiment 2, we additionally test the strength of SL and language's proposed relatedness by documenting the nature of correlations in individual differences between the two.Both experiments support the thesis that SL may overlap with mechanisms for language, while raising questions as to the singularity or duality of such underlying mechanism(s).

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