Right hemisphere dominance in visual statistical learning

Matthew E. Roser, J. Fiser, Richard N. Aslin, Michael S. Gazzaniga

Research output: Contribution to journalArticle

35 Citations (Scopus)

Abstract

Several studies report a right hemisphere advantage for visuospatial integration and a left hemisphere advantage for inferring conceptual knowledge from patterns of covariation. The present study examined hemispheric asymmetry in the implicit learning of new visual feature combinations. A split-brain patient and normal control participants viewed multishape scenes presented in either the right or the left visual fields. Unbeknownst to the participants, the scenes were composed from a random combination of fixed pairs of shapes. Subsequent testing found that control participants could discriminate fixed-pair shapes from randomly combined shapes when presented in either visual field. The split-brain patient performed at chance except when both the practice and the test displays were presented in the left visual field (right hemisphere). These results suggest that the statistical learning of new visual features is dominated by visuospatial processing in the right hemisphere and provide a prediction about how fMRI activation patterns might change during unsupervised statistical learning.

Original languageEnglish
Pages (from-to)1088-1099
Number of pages12
JournalJournal of Cognitive Neuroscience
Volume23
Issue number5
DOIs
Publication statusPublished - May 2011

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Split-Brain Procedure
Visual Fields
Learning
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Cognitive Neuroscience

Cite this

Right hemisphere dominance in visual statistical learning. / Roser, Matthew E.; Fiser, J.; Aslin, Richard N.; Gazzaniga, Michael S.

In: Journal of Cognitive Neuroscience, Vol. 23, No. 5, 05.2011, p. 1088-1099.

Research output: Contribution to journalArticle

Roser, Matthew E. ; Fiser, J. ; Aslin, Richard N. ; Gazzaniga, Michael S. / Right hemisphere dominance in visual statistical learning. In: Journal of Cognitive Neuroscience. 2011 ; Vol. 23, No. 5. pp. 1088-1099.
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