Exploiting statistical regularities in implicit sequence learning

Meier, Beat (26 May 2017). Exploiting statistical regularities in implicit sequence learning (Unpublished). In: 6th Implicit Learning Seminar. Eötvös Loránd University, Budapest, Hungary. 25.05.-26.05.2017.

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Despite the long research tradition it is not clear what is learned in implicit sequence learning. Is learning based simply on the sensitivity to the frequencies of sequence element transitions (i.e., statistical learning of sequence transitions) or is it based on the built up of a more comprehensive sequence representation (i.e., a kind of “melody”)? The purpose of this study was to distinguish between these two possibilities. In one condition the target sequence (a 12-elements SOC) was presented repeatedly without interruption and surrounded by other 12-element SOCs at the beginning and the end of each learning block. In the other condition, the same target sequence was presented twice a time, alternating with the other 12-element SOCs. Importantly, across the two conditions, frequencies of sequence element transitions were kept constant across eight learning blocks. If only the transition probabilities are learned one would expect the same learning effect across conditions. In contrast, if a more comprehensive sequence representation is built up one would expect a learning advantage for the former condition. The results are consistent with the second hypothesis. This can be interpreted as evidence that the human cognitive system can exploit regularities in the environment beyond simple sequence element transitions.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	07 Faculty of Human Sciences > Institute of Psychology > Psychological and Behavioral Health
UniBE Contributor:	Meier, Beat
Subjects:	100 Philosophy > 150 Psychology 600 Technology > 610 Medicine & health
Language:	English
Submitter:	Beat Meier
Date Deposited:	23 Apr 2018 15:34
Last Modified:	29 Mar 2023 23:35
URI:	https://boris.unibe.ch/id/eprint/110480