Probabilistic motor sequence learning in a virtual reality serial reaction time task

Florian Sense and Hedderik van Rijn

PLOS ONE, 2018, vol. 13, issue 6, 1-9

Abstract: The serial reaction time task is widely used to study learning and memory. The task is traditionally administered by showing target positions on a computer screen and collecting responses using a button box or keyboard. By comparing response times to random or sequenced items or by using different transition probabilities, various forms of learning can be studied. However, this traditional laboratory setting limits the number of possible experimental manipulations. Here, we present a virtual reality version of the serial reaction time task and show that learning effects emerge as expected despite the novel way in which responses are collected. We also show that response times are distributed as expected. The current experiment was conducted in a blank virtual reality room to verify these basic principles. For future applications, the technology can be used to modify the virtual reality environment in any conceivable way, permitting a wide range of previously impossible experimental manipulations.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0198759

DOI: 10.1371/journal.pone.0198759

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