Metrical presentation boosts implicit learning of artificial grammar

PLoS One. 2014 Nov 5;9(11):e112233. doi: 10.1371/journal.pone.0112233. eCollection 2014.

Abstract

The present study investigated whether a temporal hierarchical structure favors implicit learning. An artificial pitch grammar implemented with a set of tones was presented in two different temporal contexts, notably with either a strongly metrical structure or an isochronous structure. According to the Dynamic Attending Theory, external temporal regularities can entrain internal oscillators that guide attention over time, allowing for temporal expectations that influence perception of future events. Based on this framework, it was hypothesized that the metrical structure provides a benefit for artificial grammar learning in comparison to an isochronous presentation. Our study combined behavioral and event-related potential measurements. Behavioral results demonstrated similar learning in both participant groups. By contrast, analyses of event-related potentials showed a larger P300 component and an earlier N2 component for the strongly metrical group during the exposure phase and the test phase, respectively. These findings suggests that the temporal expectations in the strongly metrical condition helped listeners to better process the pitch dimension, leading to improved learning of the artificial grammar.

Publication types

  • Comparative Study
  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Female
  • Humans
  • Language*
  • Learning / physiology*
  • Male
  • Pitch Perception / physiology*
  • Temporal Lobe / physiology*

Grants and funding

This research was supported by a grant from EBRAMUS ITN (Europe BRAin and MUSic) (Grant Agreement number 238157). The team “Auditory cognition and psychoacoustics” is part of the LabEx CeLyA (“Centre Lyonnais d’Acoustique”, ANR-10-LABX-60). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.