In a recent article, Jamieson and Mewhort (2009) proposed a novel account of artificial grammar learning (AGL), which is based on a multitrace model of episodic memory, the Minerva 2 model. According to this account, test performance in AGL is based on an assessment of global similarity of the test strings to the memory traces of the training strings. In this article, simulation studies are presented, showing for three different AGL experiments that the predictions of the Minerva 2 model strikingly deviate from participants' performance. It is argued that participants' test performance is not generally based on general similarity.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/17470211003718713 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!