title: The neural correlates of statistical learning in a word segmentation task: An fMRI study.
abstract: Functional magnetic resonance imaging (fMRI) was used to assess neural activation as participants learned to segment continuous streams of speech containing syllable sequences varying in their transitional probabilities. Speech streams were presented in four runs, each followed by a behavioral test to measure the extent of learning over time. Behavioral performance indicated that participants could discriminate statistically coherent sequences (words) from less coherent sequences (partwords). Individual rates of learning, defined as the difference in ratings for words and partwords, were used as predictors of neural activation to ask which brain areas showed activity associated with these measures. Results showed significant activity in the pars opercularis and pars triangularis regions of the left inferior frontal gyrus (LIFG). The relationship between these findings and prior work on the neural basis of statistical learning is discussed, and parallels to the frontal/subcortical network involved in other forms of implicit sequence learning are considered.
authors: Department of Brain and Cognitive Sciences, University of Rochester, Meliora Hall, Box 270268, Rochester, NY 14627, USA. Electronic address: ekaruza@bcs.rochester.edu.
authors: Elisabeth A
authors: EA
authors: Karuza
authors: Elissa L
authors: EL
authors: Newport
authors: Richard N
authors: RN
authors: Aslin
authors: Sarah J
authors: SJ
authors: Starling
authors: Madalina E
authors: ME
authors: Tivarus
authors: Daphne
authors: D
authors: Bavelier
mesh_terms: D000293:Adolescent; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D005260:Female; D006801:Humans; D007802:Language; D007858:Learning / Q000502:physiology*; D008279:Magnetic Resonance Imaging; D008297:Male; D011930:Reaction Time / Q000502:physiology; D013060:Speech / Q000502:physiology*; D055815:Young Adult
keywords: Artificial language; Broca’s area; LIFG; Sequence learning; Statistical learning; Word segmentation; fMRI