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Age-dependent and coordinated shift in performance between implicit and explicit skill learning

Age-dependent and coordinated shift in performance between implicit and explicit skill learning

Nemeth, Dezso, Janacsek, Karolina and Fiser, József (2013) Age-dependent and coordinated shift in performance between implicit and explicit skill learning. Frontiers in Computational Neuroscience, 7:147. ISSN 1662-5188 (Online) (doi:https://doi.org/10.3389/fncom.2013.00147)

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Abstract

It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N=288), replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

Item Type: Article
Uncontrolled Keywords: probabilistic sequence learning, associative learning, development, model-based vs. model free learning
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Faculty / Department / Research Group: Faculty of Education, Health & Human Sciences
Faculty of Education, Health & Human Sciences > Department of Psychology, Social Work & Counselling
Last Modified: 20 Jan 2020 13:49
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/25700

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