Lack of Automatic Vocal Response Learning While Reading Aloud

Knowledge of Statistics or Statistical Learning? Readers Prioritize the Statistics of their Native Language Over the Learning of Local Regularities

A large body of evidence suggests that people spontaneously and implicitly learn about regularities present in the visual input. Although theorized as critical for reading, this ability has been demonstrated mostly with pseudo-fonts or highly atypical artificial words. We tested whether local statistical regularities are extracted from materials that more closely resemble one’s native language. In two experiments, Italian speakers saw a set of letter strings modelled on the Italian lexicon and guessed which of these strings were words in a fictitious language and which were foils. Unknown to participants, words could be distinguished from foils based on their average bigram frequency. Surprisingly, in both experiments, we found no evidence that participants relied on this regularity. Instead, lexical decisions were guided by minimal bigram frequency, a cue rooted in participants’ native language. We discuss the implications of these findings for accounts of statistical learning and visual word processing.

Day versus night consolidation of implicit sequence learning using manual and oculomotor activation versions of the serial reaction time task: reaction time and anticipation measures

This study presents two experiments that explored consolidation of implicit sequence learning based on two dependent variables-reaction time (RT) and correct anticipations to clarify the role of sleep, and whether the manual component is necessary for consolidation processes. Experiment 1 (n = 37) explored the performance of adults using an ocular variant of the serial reaction time task (O-SRT) with manual activation (MA), and Experiment 2 (n = 37) used the ocular activation (OA) version of the task. Each experiment consisted of a Day and a Night group that performed two sessions of the O-SRT with an intervening 12-h offline period (morning/evening in Day group, evening/following morning in Night group). Night offline had an advantage only when manual response was required and when correct anticipations (i.e., accuracy) but not RT (i.e., speed) were measured. We associated this finding with the dual-learning processes required in the MA O-SRT that led to increased sequence specific learning overnight. When using the OA O-SRT, both groups demonstrated similar rates after offline in RT and correct anticipations. We interpreted this finding to reflect stabilization, which confirmed our hypothesis. As expected, all the groups demonstrated reduced performance when another sequence was introduced, thus reflecting sequence-specific learning. This study used a powerful procedure that allows measurement of implicit sequence learning in several ways: by evaluating two different measures (RT, correct anticipations) and by isolating different aspects of the task (i.e., with/without the manual learning component, more/less general skill learning), which are known to affect learning and consolidation.