Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

Article English OPEN
Vasiliki eFolia ; Vasiliki eFolia ; Karl Magnus ePetersson ; Karl Magnus ePetersson ; Karl Magnus ePetersson (2014)
  • Publisher: Frontiers Media S.A.
  • Journal: Frontiers in Psychology (issn: 1664-1078)
  • Related identifiers: doi: 10.3389/fpsyg.2014.00041/full, doi: 10.3389/fpsyg.2014.00041
  • Subject: fMRI | implicit learning | artificial grammar learning | inferior frontal gyrus | artificial syntax | structural mere-exposure | Psychology | BF1-990

In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.
Share - Bookmark