Functional differences between statistical learning with and without explicit training

Abstract

Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and prepare for incoming input. In this study, we ask whether the function of statistical learning may be enhanced through supplementary explicit training, in which underlying regularities are explicitly taught rather than simply abstracted through exposure. Learners were randomly assigned either to an explicit group or an implicit group. All learners were exposed to a continuous stream of repeating nonsense words. Prior to this implicit training, learners in the explicit group received supplementary explicit training on the nonsense words. Statistical learning was assessed through a speeded reaction-time (RT) task, which measured the extent to which learners used acquired statistical knowledge to optimize online processing. Both RTs and brain potentials revealed significant differences in online processing as a function of training condition. RTs showed a crossover interaction; responses in the explicit group were faster to predictable targets and marginally slower to less predictable targets relative to responses in the implicit group. P300 potentials to predictable targets were larger in the explicit group than in the implicit group, suggesting greater recruitment of controlled, effortful processes. Taken together, these results suggest that information abstracted through passive exposure during statistical learning may be processed more automatically and with less effort than information that is acquired explicitly.

Figure 1.

Summary of experimental design. Pretraining (for explicit group only) included auditorily presenting the six three-syllable nonsense words (babupu, bupada, dutaba, patubi, pidabu, tutibu) in isolation, with the written representation of each word shown visually. All participants (explicit group and implicit group) then completed the exposure, recognition, and target-detection tasks. The exposure task consisted of 21 min of continuous auditory exposure to the six repeating nonsense words. For the recognition task, each trial was composed of a word and nonword foil, presented auditorily. Participants indicated which item was more familiar, and provided a metamemory judgment. For the target-detection task, participants detected target syllables embedded in a continuous auditory speech stream composed of the six nonsense words. The syllable assigned as the target was rotated across trials.

Figure 2.

Behavioral results from the target-detection task. (A) RTs as a function of syllable position, by group. A significant crossover interaction was found. Error bars represent SEM. (B) Number of early responses (0–200 msec) to each target as a function of syllable position, by group. Error bars represent SEM.

Figure 3.

ERP results from the target-detection task. (A) ERPs timelocked to targets occurring in word-initial, word-medial, and word-final positions in the speeded target-detection task, as a function of group. Only correctly detected targets are included in these averages. The bar graph displays mean ERP amplitudes across all electrodes as a function of target position. Error bars represent SEM. (B) ERPs to each of the three-syllable targets are directly compared between implicit and explicit groups.

Figure 4.

Behavioral results from the recognition judgment task. (A) Accuracy on the recognition judgment task as a function of metamemory judgment, by group. Only participants with responses in all three metamemory conditions are included in these averages, reflecting statistical analyses reported in the paper (n = 17 implicit group, n = 13 explicit group). Note that overall means from all participants are very similar (<2% discrepancy per value). Chance performance on this task is 50%. Error bars represent SEM. (B) Proportion of each metamemory response by group. All participants are included. Error bars represent SEM.

Figure 5.

ERP results from the recognition judgment task. (A) ERPs timelocked to words and nonword foils in the recognition judgment task, by group. Only correct trials are included in these averages. Scalp topographies of the early positivity and LPC are shown on the right. (B) ERPs timelocked to words and nonword foils that were not correctly recognized. All participants with a sufficient number of incorrect trials are grouped together in this average (20 implicit-group participants and five explicit-group participants).