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Katherine Moore, Do-Joon Yi, Samuel Cartmell, Marvin Chun; The role of attention in repetition attenuation and pattern similarity during visual learning. Journal of Vision 2012;12(9):380. doi: https://doi.org/10.1167/12.9.380.
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We investigated the role of attention in two measures of stimulus-specific learning: repetition attenuation, and pattern similarity. Repetition attenuation refers to the decreased BOLD fMRI signal in sensory regions when a stimulus is repeated and is sensitive to manipulations of attention and task demands (Yi & Chun, 2005). In pattern similiarity, researchers use multi-voxel pattern analysis to examine the similarity of the pattern of neural response to repeated presentations of a stimulus. More similarity across presentations is related to better learning (Xue et al, 2010). Though both neural measures index learning, the relationship between them is not understood, and the role of attention in pattern similarity has not been studied. Hence, we examined the relationship of these two fMRI measures. We manipulated attention by instructing participants to attend to either the face or scene dimension of composite face-scene images while performing a change detection task. Consistent with Yi and Chun (2005), we observed attenuation in the scene-sensitive parahippocampal place area (PPA) only when a scene was attended during both initial presentation and upon repetition, indicating that attention is important for repetition attenuation. Likewise, we observed more similarity between patterns of activity for repeated pairs of scenes when both instances were attended than when either or both were ignored. Additionally, there was a small positive correlation between the degree of repetition attenuation and the similarity of the pattern across repeated scenes, indicating a weak relationship between repetition attenuation and pattern similarity. We conclude that attention is important for both repetition attenuation and pattern similarity, but also that the relationship between the two measures is weak, and that they may reflect different neural properties of learning.
Meeting abstract presented at VSS 2012
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