Statistical learning in a serial reaction time task: Access to separable statistical cues by individual learners

The ability of adult learners to exploit the joint and conditional probabil ities in a serial reaction time task containing both deterministic and prob abilistic information was investigated. Leamers used the statistical inform ation embedded in a continuous input stream to improve their performance fo r certain transitions by simultaneously exploiting differences in the predi ctability of 2 or more underlying statistics. Analysis of individual learne rs revealed that although most acquired the underlying statistical structur e veridically, others used an alternate strategy that was partially predict ive of the sequences. The findings show that learners possess a robust lear ning device well suited to exploiting the relative predictability of more t han I source of statistical information at the same time. This work expands on previous studies of statistical learning, as well as studies of artific ial grammar learning and implicit sequence learning.