We found that stimulus features could be reliably decoded from all four networks and, importantly, that subregions within each attentional network maintained coherent representations.
#Bottom up processing trial#
Within studies, we manipulated which stimulus features were goal relevant (i.e., whether gender or affect was relevant) and task switching (i.e., whether the goal on the current trial matched the goal on the prior trial). Across studies, we interrupted bottom-up visual input using backward masks. In a pair of pattern-based fMRI studies, male and female human subjects made perceptual decisions about face images that varied along two independent dimensions: gender and affect. Specifically, we tested whether representations of stimulus features across these networks are differentially sensitive to bottom-up and top-down factors. Here, we assessed how perceptual stimuli are represented across large-scale frontoparietal and visual networks. However, recent evidence suggests that frontoparietal regions actively represent perceptual stimuli.
The traditional view is that these networks support visual attention by biasing and evaluating sensory representations in visual cortical regions. Visual attention is thought to be supported by three large-scale frontoparietal networks: the frontoparietal control network (FPCN), the dorsal attention network (DAN), and the ventral attention network (VAN).
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