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Anna Byers, John Serences; Learning to attend induces an increased response to unattended stimuli. Journal of Vision 2011;11(11):1001. doi: 10.1167/11.11.1001.
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© ARVO (1962-2015); The Authors (2016-present)
Traditional perceptual learning tasks employ just a single stimulus feature, making it difficult to parse out the differential effects of low-level sensory plasticity (i.e. Seitz et al., 2009) and top-down attentional gain modulations (i.e. Fahle, 2009) on observed changes in behavior and neural activity. Here, we evaluated the relationship between learning and top-down attentional gain using feature-selective fMRI techniques and a task that required discriminating one of ten possible orientations (instead of only a single orientation, as is typically employed in perceptual learning studies). Given that perceptual learning has been documented to occur without attention (Seitz et al., 2009), we expected to see an increase in the amplitude of orientation-selective response profiles in V1 after training on both an orientation-attended and an orientation-unattended task. Five subjects participated in an initial fMRI scan session, 10 behavioral training sessions, and a final scan session. For all sessions, subjects performed four blocks of an orientation discrimination task and four blocks of a rapid serial visual presentation (RSVP) letter task. Before training, the orientation-selective response profile in V1 had higher amplitude during the orientation-attended task compared to the orientation-unattended (RSVP) task. However, after training, the amplitude of the orientation-selective response profile increased, particularly when orientation was ignored (i.e. during the RSVP task). These results indicate that practice improves feature-selective representations of stimuli in early visual cortex, even when the stimulus is not being actively attended. Moreover, since our experiment involved multiple orientations, our subjects must have been learning to modulate sensory gain in a general sense, as opposed to optimizing gain to process a single, highly trained stimulus feature.
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